New Generation Transport - Model Validation Report · 2.2 The NGT Scheme The NGT scheme is a modern trolleybus service operating north / south through the urban area of Leeds. It

Transportation METRO March 2012

New Generation Transport Model Validation Report

Prepared by: ............................................................. Checked by: ........................................................................ Masood Hashmi Simon Deakin Consultant Principal Consultant Approved by: ............................................................. Stuart Dalgleish Associate Director New Generation Transport Model Validation Report

Rev No Comments Checked by Approved by

Date

4 Revised for March 2012 Submission – Modelling NGT Chapter Removed

SD 28/03/11

3 Revised draft following DfT comments and updated base year model SJD SD 31/08/11

2 2nd

Draft following internal comments SD 11/05/11

1 Draft for internal comment SD 06/05/11

5th Floor, 2 City Walk, Leeds, LS11 9AR Telephone: 0113 391 6800 Website: http://www.aecom.com Job No 60157085 Reference Date Created March 2012 This document is confidential and the copyright of AECOM Limited. Any unauthorised reproduction or usage by any person other than the addressee is strictly prohibited. f:\projects\transport planning - leeds ngt modelling\reports\ngt lmvr v3.docx

1 Introduction ....................................................................................................................................................................... 3

2 The NGT Scheme .............................................................................................................................................................. 5

3 Leeds Transport Model ..................................................................................................................................................... 7

4 Observed Data ................................................................................................................................................................. 18

5 Model Acceptability Guidelines ..................................................................................................................................... 31

6 Validation of Highway Assignment Model .................................................................................................................... 34

7 Highway Model Behaviour in Outer Simulation Area ................................................................................................... 54

8 Validation of Public Transport Assignment Model ...................................................................................................... 59

9 Conclusion ....................................................................................................................................................................... 61

Appendix A – Model Zones .......................................................................................................................................................... 63

Appendix B – Base Year Highway Flow Comparisons .............................................................................................................. 65 Table 1 – Model Demand Segments ............................................................................................................................................ 11 Table 2 – Car Counts along the NGT Corridor ........................................................................................................................... 21 Table 3 – Accuracy of Counts on the NGT Route ...................................................................................................................... 25 Table 4 – Observed Journey Times (seconds) ........................................................................................................................... 27 Table 5 – Passenger Counts ........................................................................................................................................................ 28 Table 6 – Acceptability Guidelines for Highway Flows ............................................................................................................. 31 Table 7 – Acceptability Guidelines for Highway Flows Crossing Short Screenlines ............................................................. 31 Table 8 – Acceptability Guideline for highway Journey Time................................................................................................... 31 Table 9 – Difference between Total Screenline Count and Modelled Flow (Cars) .................................................................. 35 Table 10 – Individual Count Summary ........................................................................................................................................ 37 Table 11 – Observed and Modelled Highway Journey Times (seconds) ................................................................................. 43 Table 12 – Modelled Passenger Flows ........................................................................................................................................ 59 Table 13 – Difference between Observed and Modelled Passenger Flows ............................................................................. 59 Table 14 - Flow Difference at individual count sites .................................................................................................................. 65 Figure 1 – Leeds Transport model Structure ...............................................................................................................................7 Figure 2 – Model Zones - National .................................................................................................................................................8 Figure 3 – Model Zones in West Yorkshire ...................................................................................................................................9 Figure 4 – Model Zones in Leeds (Main Urban Area) ................................................................................................................. 10 Figure 5 – Model Time Periods .................................................................................................................................................... 11 Figure 6 – Choice Model Structure .............................................................................................................................................. 12 Figure 7 – Modelled Highway Network ....................................................................................................................................... 14 Figure 8 – Modelled Public Transport Network .......................................................................................................................... 16 Figure 9 – Location of Traffic Screenlines crossing the NGT route ......................................................................................... 20 Figure 10 – Location of Journey Time Routes ........................................................................................................................... 26 Figure 11 – Location of Public Transport Passenger Counts ................................................................................................... 28 Figure 12 – Flows and Journey Times 0700 ............................................................................................................................... 46 Figure 13 – Flows and Journey Times 0800 ............................................................................................................................... 47 Figure 14 – Flows and Journey Times 0900 ............................................................................................................................... 48 Figure 15 – Flows and Journey Times Inter-Peak ...................................................................................................................... 49 Figure 16 – Flows and Journey Times 1600 ............................................................................................................................... 50 Figure 17 – Flows and Journey Times 1700 ............................................................................................................................... 51 Figure 18 – Flows and Journey Times 1800 ............................................................................................................................... 52

Table of Contents

Figure 19 – 2031 0800-0900 Delay Comparison ......................................................................................................................... 55 Figure 20 – 2031 Interpeak Delay Comparison........................................................................................................................... 56 Figure 21 – 2031 1700-1800 Delay Comparison ......................................................................................................................... 57

Introduction

AECOM New Generation Transport Model Validation Report 3

Capabilities on project:

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1.1 Purpose of Report

This report has been prepared to describe the performance of the Leeds Transport Model (LTM) along the New Generation

Transport (NGT) corridor and show that it is adequate for modelling the NGT scheme. It then goes on to describe how the NGT

scheme has been modelled within LTM.

1.2 Background

The LTM has been developed as a general purpose transport model capable of modelling a wide range of transport interventions

and policies. It is to be used to test the NGT scheme and therefore it is important that the model is shown to be fit for this

purpose.

Separate Model Validation Reports have been prepared for the highway, public transport and demand models that comprise the

LTM. These describe how the model has been constructed and the level of validation achieved across the whole of the model

area. A report of survey has also been prepared detailing the data that was collected and subsequently used in developing this

model. These reports have not been reproduced within this report although a very brief summary of the key elements of the

model are contained in Chapter 3.

While the overall model reports demonstrate the quality of data, rigour of development and level of validation of the LTM it is

necessary also to review the model within the area local to the NGT scheme in order to judge the suitability of the model for the

purpose of testing the particular NGT scheme being promoted by METRO. Within this report a more detailed comparison

between observed and modelled data is undertaken within the corridors where NGT is proposed to operate.

The validation data presented in this report has been extracted from an interim version of the highway and public transport

assignment models. These results may therefore change as the models are finalised but we do not envisage that any changes

will be significant.

1.3 Structure of Report

This report is divided into a number of chapters.

Chapter 2 – The NGT Scheme

Chapter 3 – The Leeds Transport Model

Chapter 4 – Observed data

Chapter 5 – Validation Acceptability Guidelines

Chapter 6 – Validation of Highway Assignment Model within LTM

Chapter 7 – Highway Model Behaviour In Outer Simulation Area

Chapter 8 – Validation of Public Transport Assignment Model within LTM

Chapter 9 – Conclusions

Appendix A – Model Zones

Appendix B – Base Year Highway Flow Comparisons

1 Introduction

The NGT Scheme



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2.1 Introduction

This chapter sets out the type and geographical extents of the NGT scheme and draws conclusions on which areas of LTM are

relevant for the appraisal of the scheme.

2.2 The NGT Scheme

The NGT scheme is a modern trolleybus service operating north / south through the urban area of Leeds. It is made up of several

components and these are described in the following sections.

Type of Service

It is proposed that the NGT network will be operated by modern trolleybuses. Trolleybuses run on rubber tyres like a regular bus

but they are powered by electricity from overhead wires. They have fast, smooth acceleration and are clean, quiet and don’t

pollute the local environment

Route

The route of NGT runs from Holt Park in the North to Stourton in the south passing through Bodington, Lawnswood, Headingly,

Woodhouse, The City Centre, Clarence Dock and Hunslet Road. The main corridors used by the scheme are the A660 Otley

Road / Headingly Lane and the A61 Hunslet Road / Low Road.

Park and Ride

Two new Park and Ride sites are being developed as part of the NGT scheme. These are located at Bodington (just outside the

Outer Ring Road to the north of Leeds and at Stourton just off J7 of the M621 to the south.

Fares

The exact fare level for NGT is not yet confirmed. In order to make it competitive it may be advantageous to have fares at the

same level as other bus services. Alternatively, in order to maximise fare box revenue it may be possible to charge premium

fares to reflect the higher quality that NGT will bring compared to other bus services.

Service Quality

NGT is expected to be a high quality service. The vehicles will be new, with disabled access as standard. They will run on

dedicated lanes for a substantial proportion of their journey providing a quicker and more reliable journey time. High quality stops

will be provided with shelters and real-time information showing passengers when NGT services are due to arrive.

2.3 Implications for modelling

NGT passengers are likely to be drawn from two sources.

Local Area – There are those travellers living or working within walking distance of the proposed stops. NGT users from

these areas are likely to be existing bus users although some could be existing car drivers / passengers or currently

using active modes. There is also a possibility that a small number of existing rail users could be attracted to NGT from

around the Burley Park area.

Wider Area – Through the development of Park and Ride sites, NGT is likely to become attractive to some car drivers

and passengers (particularly those who have to pay for parking at their destination) who approach the city from outside

the main urban area.

In order to model NGT it is important that the base model has an accurate representation of the demand that is likely to use the

scheme. Based on the analysis above it is likely that the demand will be drawn from local trips along the NGT route and highway

trips from the north and south travelling to the City Centre.

It should be noted that while active modes are included within NGT these have not been calibrated or validated. The main

question regarding the model suitability, however, relates to the sensitivity of the modal response to public transport

improvements, rather than the existing representation of active mode trips along the corridor and this is set out in the LTM

Demand Model Report which states that “Active-mode (walk and cycle) demand is included within LTM_D. LTM_D is suitable for

broad assessment of global interventions designed to affect pedestrians and cyclists”

2 The NGT Scheme

Leeds Transport Model



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3.1 Introduction

This chapter sets out a brief description of the Leeds Transport Model (LTM), drawing out specific areas of interest to NGT. A

fuller description of LTM and how it was developed can be found in the model development reports covering the three main

elements of LTM (Highway Assignment Model, Public Transport Assignment Model and Demand Model).

3.2 General Description

LTM has been developed with the aim of being compliant with WebTAG. It has three main components with linkages between

them as shown in Figure 1. Parking choice is represented as part of the demand model. For park and ride sites the choice is

represented as an alternative to City Centre parking, with the demand of the car and public transport stages of the journey

allocated to both assignment models.

Figure 1 – Leeds Transport model Structure

3.3 Model Zone System

The model zones are common to all three main elements of LTM. There are a total of 830 zones in the model. These cover the

whole country but just over 530 of these are within Leeds District. A further 250 cover the districts surrounding Leeds with the

remaining 50 covering the rest of the country. The model zones are shown in Figure 2, Figure 3 and Figure 4.

Costs Costs

Demand Demand

Journey Times

Demand Model

PT Model Highway Model

3 Leeds Transport Model



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Figure 2 – Model Zones - National



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Figure 3 – Model Zones in West Yorkshire



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Figure 4 – Model Zones in Leeds (Main Urban Area)

Approx Line of NGT Route



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3.4 Model Time Periods

The model operates on a 24 hour day with some variation in time periods in each of the sub models. These are shown in Figure

5. The figure shows the time periods for which validated models exist. In addition there are un-validated off peak highway and

public transport models which provide costs to enable the demand model to operate at a 24hour level.

Figure 5 – Model Time Periods

The LTM is a tour based model whereby the outbound and return legs of each trip are linked between the outbound time period

and the return time period in such a way that the demand responses take into account the return journey costs and the

responses are applied to the return trip as a complete entity rather than separate responses to each leg of the journey.

3.5 Demand Segmentation

Demand within LTM is segmented into 14 categories as set out in Table 1. These cover journey purpose, income and vehicle

type. Some segments are combined in the assignment models. In the PT model there is an additional level of segmentation:

concessionary and non concessionary travellers. This segmentation was set up to allow a wide range of scheme and policy

testing to be undertaken using LTM. This segmentation is considered to be sufficient for testing NGT and offers the option of

presenting the distributional impacts of the scheme.

Table 1 – Model Demand Segments

Journey Purpose Income Band Demand Model

Segment

Highway Model

Segment

PT Model Segment

Concessionary Non

Concessionary

Commuting

Low 1 1

1 2

Med 2 2

High 3 3

Home Based Other

Low 4 1

Med 5 2

High 6 3

Non Home based Other

Low 7 1

Med 8 2

High 9 3

Education All 10 2

Home Based All 11 4 2

00

:00

01

:00

02

:00

03

:00

04

:00

05

:00

06

:00

07

:00

08

:00

09

:00

10

:00

11

:00

12

:00

13

:00

14

:00

15

:00

16

:00

17

:00

18

:00

19

:00

20

:00

21

:00

22

:00

23

:00

Demand Model

07

:00

08

:00

09

:00

16

:00

17

:00

18

:00

Highway Model

07

:00

08

:00

09

:00

16

:00

17

:00

18

:00

PT Model

Off Peak

Inter Peak

AM Inter Peak PM

Off Peak Inter Peak



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Business

Non Home Based Business

All 12 4

LGV All 13 5 N/A N/A

HGV All 14 6

3.6 Demand Model

The demand model operates above the highway and public transport models. It is a hierarchical logit model, and thus contains a

number of different modules that deal with different aspects of traveller choice. They are implemented in increasing order of

sensitivity; this structure is necessary to ensure that higher-level modules do not have an inconsistent effect on lower-level ones,

and is in accordance with guidance in WebTAG Unit 3.10.3, Section 1.9.

The choice structure used in the LTM_D is illustrated in Figure 6 below. This is applicable to car-available trips. No-car-available

and freight demand segments have simplified choice structures.

Figure 6 – Choice Model Structure

The NGT scheme is principally aimed at mode shift from car although it could also be attractive to existing bus users. It will also

make the city centre more attractive as a destination thus increasing demand to the city centre. The NGT scheme includes a park

Motorised Mode Choice(car vs. public transport)

Trip Frequency

Car-available trips

Parking Choice

PublicTransport Car

Time Period Choice

Trip Distribution

PNR

Trip Distribution

Public Transport Mode Choice(rail vs. bus)

Short-term

Long-term

Rail

BusCUBE

VOYAGER

EMME

Time Period Choice

Active Mode Choice(motorised vs. active)

Time Period Choice

Walk+Cycle

Trip Distribution

Park-and-Ride



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and ride element therefore modelling of these types of mixed mode trip is also required. The structure of the demand model

provides for all these choices and therefore the demand model structure is adequate for testing the NGT scheme.

A re-calibration of the demand model is currently underway following some updates to the highway and public transport models.

We are confident that we will be able to show that the calibration of this will be acceptable and make the model adequate for

testing NGT.

3.7 Highway Assignment Model

The highway network coverage within Leeds includes all roads of M. A and B classification. In addition unclassified roads have

been included where they offer a through route. Figure 7 shows the network that is included within the highway model. All the

roads within Leeds are coded using SATURN simulation coding. This provides capacity restraint at a junction level. Some further

capacity restraint is modelled through the use of mid link capacities with cruise speeds on urban roads and speed – flow

relationships on grade separated roads and rural links.

The highway demand matrices were developed from a set of over 100 roadside interview surveys, four of which were on the NGT

corridor. A gravity model was then developed, and calibrated to the observed data, to infill the unobserved movements.

The highway network modelled in SATURN in the Leeds area is shown in Figure 7 with the approximate line of the NGT route

indicated in blue.



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Figure 7 – Modelled Highway Network



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3.8 Public Transport Assignment Model

The public transport assignment model includes all bus and train services within the Leeds district. These are shown in Figure 8.

Services are coded on a headway basis with a crowding penalty applied to rail services. Demand for public transport is assigned

in two segments; concessionary travellers and non concessionary travellers. Fares are represented in the assignment model with

fare tables included in the base year model (Rail, Bus – First, Bus Arriva and Bus free). The resulting fares paid are then

averaged (by demand) across the two segments for use in the demand model.



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Figure 8 – Modelled Public Transport Network

Observed Data



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4.1 Introduction

This chapter sets out the observed data that has been used to assess the validation of the LTM within the corridors that NGT is

proposed to operate in.

The following data has been collected along the NGT corridors:

- Highway Traffic Flows (both as individual counts on the NGT route and across screenlines incorporating the NGT corridor.

- Highway Journey Times along the NGT route

- Public Transport Passenger counts on the NGT route

4.2 Highway Traffic Flows

There are a total of 6 screenlines which LTM has been calibrated and validated against. Of these 4 cross the northern NGT route and 2 cross the southern route as shown in Figure 9. These counts come from a number of sources across several years. All

counts have been adjusted to an average weekday in October 2008 to match the base year / month of the model. The adjustment factors are listed in the Highway Assignment Model Development and Validation report and are based on long term automatic traffic counts across the Leeds area. Where both a Manual Classified Count (MCC) and Automatic Traffic Count (ATC) have been undertaken the MCC is only used to provide vehicle type proportions that are then applied to disaggregate the ATC into vehicle types. Where there was no manual count the ATC was disaggregated using average vehicle type splits developed from other MCCs on roads of a similar type. For the purposes of the comparisons within this report we have only considered car flows as these are the potential target market for NGT.

The screenlines provide a good coverage of the demand of traffic approaching and leaving the central Leeds area that might be affected by the scheme. The screenlines do not, however, provide information on traffic flows within the city centre. While it is envisaged that the scheme traffic impacts will primarily be along the radials, this will need to be analysed to determine whether the scheme significantly affects city centre traffic.

4 Observed Data



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Table 2 below presents the observed flow for the inbound and the outbound direction for all individual sites on the screenlines

crossing the NGT corridors. Highlighted counts are on the proposed NGT route.



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Figure 9 – Location of Traffic Screenlines crossing the NGT route



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Table 2 – Car Counts along the NGT Corridor

ScreenLine Site Direction 0700 0800 0900 IP 1600 1700 1800 12 Hour

RSI01 LDSJ31 IN 1524 1749 1159 690 700 660 734 10663

RSI01 LDSJ32 IN 1009 1179 803 497 443 407 424 7247

RSI01 LDSJ33 IN 156 297 225 238 306 291 283 2989

RSI01 LDSJ34 IN 908 917 712 556 559 581 555 7568

RSI01 LDSJ35CALI IN 200 368 223 167 226 200 197 2419

RSI01 Proxy345 IN 552 612 503 358 277 265 356 4713

RSI01 LDSJ36 IN 92 140 106 92 106 107 97 1200

RSI01 Proxy346 IN 1714 1564 1198 945 1119 1137 1137 13538

RSI01 LDSJ31 OUT 462 503 495 628 1296 1404 1111 9038

RSI01 LDSJ32 OUT 221 368 366 587 1100 1191 956 7725

RSI01 LDSJ33 OUT 167 374 280 270 340 349 335 3466

RSI01 LDSJ34 OUT 361 524 492 531 729 918 796 7004

RSI01 LDSJ35CALI OUT 65 138 160 179 373 430 326 2564

RSI01 Proxy345 OUT 240 321 319 409 480 476 430 4722

RSI01 LDSJ36 OUT 61 86 81 100 245 302 143 1517

RSI01 Proxy346 OUT 887 1033 957 1018 1744 1628 1482 13839

RSI10 NWL7 IN 865 650 673 610 720 749 710 8029

RSI10 LDS4CALI IN 481 606 448 446 423 471 408 5509

RSI10 LDS5 IN 427 411 276 316 401 517 366 4295

RSI10 Proxy312 IN 69 124 81 80 119 110 105 1087

RSI10 LDS35 IN 324 316 297 155 165 181 163 2378

RSI10 LDS6 IN 492 585 342 260 300 310 273 3860

RSI10 LDS7 IN 921 987 657 503 619 577 575 7356

RSI10 LDS8 IN 388 506 316 210 234 205 233 3144

RSI10 LDS9 IN 723 861 721 495 548 548 541 6915

RSI10 LDS10 IN 1005 1056 821 649 827 879 942 9426

RSI10 LDS11 IN 360 428 355 255 306 359 359 3698

RSI10 NWL7 OUT 643 673 555 656 919 1050 891 8669

RSI10 LDS4CALI OUT 303 489 349 402 549 578 537 5217

RSI10 LDS5 OUT 164 242 172 288 430 522 413 3674

RSI10 Proxy312 OUT 100 243 155 183 280 288 217 2381

RSI10 LDS35 OUT 180 246 229 181 333 359 287 2717

RSI10 LDS6 OUT 135 255 167 269 432 558 479 3638

RSI10 LDS7 OUT 418 457 441 499 716 813 754 6592



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RSI10 LDS8 OUT 127 229 149 221 381 484 438 3136

RSI10 LDS9 OUT 274 458 376 532 821 862 848 6829

RSI10 LDS10 OUT 893 792 609 744 1088 1246 1209 10303

RSI10 LDS11 OUT 252 451 271 260 429 477 410 3850

CAL15 I118 IN 891 732 657 529 636 662 572 7322

CAL15 2008_333 IN 290 296 192 157 178 199 160 2259

CAL15 2008_335 IN 320 367 334 299 458 454 369 4098

CAL15 2009_264 IN 619 764 437 295 362 354 290 4597

CAL15 I235 IN 854 661 728 619 732 771 723 8180

CAL15 CP979265 IN 345 457 200 160 208 185 185 2538

CAL15 I208 IN 369 549 405 327 346 364 365 4362

CAL15 2005_310 IN 294 562 295 226 273 274 261 3317

CAL15 2007_561 IN 2 3 3 4 4 4 4 47

CAL15 I118 OUT 412 565 436 513 825 867 819 7005

CAL15 2008_333 OUT 82 138 127 157 244 234 229 1996

CAL15 2008_335 OUT 332 379 254 300 448 452 411 4076

CAL15 2009_264 OUT 130 192 176 236 537 601 433 3482

CAL15 I235 OUT 489 656 578 643 907 975 930 8396

CAL15 CP979265 OUT 71 179 132 190 433 501 350 2804

CAL15 I208 OUT 236 336 299 376 471 418 411 4425

CAL15 2005_310 OUT 158 374 202 254 537 684 530 4007

CAL15 2007_561 OUT 7 21 12 12 25 24 23 184

VAL14 I201 IN 849 900 700 571 640 582 556 7652

VAL14 I414 IN 172 354 162 122 167 160 127 1871

VAL14 I413 IN 134 188 148 124 127 113 117 1568

VAL14 I412 IN 527 536 434 349 401 415 368 4774

VAL14 I411 IN 1648 1514 1203 1035 1149 1103 1108 13935

VAL14 I201 OUT 420 573 538 550 803 946 721 7299

VAL14 I414 OUT 60 96 120 133 302 363 206 1942

VAL14 I413 OUT 50 91 95 125 297 418 197 1900

VAL14 I412 OUT 382 463 407 435 665 623 522 5671

VAL14 I411 OUT 977 1080 1015 1077 1715 1542 1400 14192

RSI03 LDSJ10 IN 93 109 70 73 49 46 38 846

RSI03 LDSJ12ELLR IN 956 902 755 640 633 725 728 8542

RSI03 LDSJ7ELLR IN 1154 1221 1014 751 875 946 678 10397

RSI03 Proxy26 IN 215 264 157 116 165 154 78 1728



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RSI03 LDSJ5 IN 245 379 173 146 198 211 162 2246

RSI03 LDSJ6 IN 377 565 440 443 467 434 369 5309

RSI03 Proxy82 IN 4346 3565 2781 1892 2671 2938 2473 30125

RSI03 LDSJ10 OUT 59 93 79 104 115 127 58 1152

RSI03 LDSJ12ELLR OUT 407 594 499 657 1114 1174 900 8633

RSI03 LDSJ7ELLR OUT 573 649 492 656 939 900 677 8165

RSI03 Proxy26 OUT 214 234 131 142 239 238 129 2036

RSI03 LDSJ5 OUT 105 151 112 148 227 251 154 1890

RSI03 LDSJ6 OUT 148 203 296 363 508 605 428 4366

RSI03 Proxy82 OUT 2793 2291 1563 2188 4823 4853 3286 32740

RSI12 LDS18 IN 910 1023 744 725 848 935 823 9633

RSI12 LDS19 IN 767 650 649 510 602 656 600 6984

RSI12 LDS20 IN 892 751 465 243 157 117 204 4045

RSI12 LDS21 IN 928 773 604 300 276 277 271 4927

RSI12 Proxy318 IN 4632 3141 2674 1829 2302 2854 2364 28941

RSI12 LDS22 IN 535 736 241 170 209 241 200 3181

RSI12 LDSA1 IN 239 298 136 201 453 627 365 3325

RSI12 LDS18 OUT 800 805 717 686 719 814 800 8768

RSI12 LDS19 OUT 372 476 395 519 760 720 718 6557

RSI12 LDS20 OUT 146 154 174 308 414 165 340 3242

RSI12 LDS21 OUT 268 277 257 349 861 797 546 5099

RSI12 Proxy318 OUT 2452 2033 1545 1925 4901 4157 2839 29475

RSI12 LDS22 OUT 120 129 115 166 255 258 204 2078

RSI12 LDSA1 OUT 386 413 254 180 247 287 287 2954

RSI08 LDSB1 IN 1421 1636 1320 1071 1310 1542 1522 15175

RSI08 LDSB1 OUT 1328 1438 1269 1110 1273 1380 1334 14683

RSI08 LDSB2 IN 914 1013 713 558 713 810 859 8368

RSI08 LDSB2 OUT 576 649 544 656 1012 1071 897 8683

RSI08 LDSB3 IN 375 507 329 323 478 500 463 4590

RSI08 LDSB3 OUT 391 491 363 436 826 931 660 6277

4.3 Count Accuracy

The confidence that we have in individual counts is important in understanding how much reliance we can place on them. Clearly

any traffic count, manual or automatic, is subject to counting errors as well as (in the case of MCCs) day to day variation. The

level of error is generally greater for MCC data however; the errors associated with car counts are lower than those associated

with goods vehicles. DMRB sets out the level of confidence that is typical for a manual and automatic traffic count. These are +/-

10% for manual car counts and +/- 5% for hourly totals automatic traffic counts. In an ideal situation there will be both a manual



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count (to provide vehicle type proportions) and an automatic count (to provide overall volume) and the two will be used together

as set out earlier in this chapter.

The age of the count and the month in which it was undertaken also have a bearing on the confidence we can have in the count.

We have less confidence in counts that need to be factored to adjust for age or seasonal variation.

Table 3 sets out the source of each of the counts along the NGT route i.e. those highlighted in



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Table 2 above.

Table 3 – Accuracy of Counts on the NGT Route

Site Manual Count Automatic Count Comments

LDS7 Single 12 hour count on day of RSI Tue 23/09/2008

2 Weeks ATC around the time of the RSI (Sept 2008)

MCC used to provide vehicle type proportions. ATC average excludes day of RSI due to possible traffic disruption. No factoring required for age or seasonal variation.

I235 No One month – October 2008 Average vehicle type for urban main roads (in Leeds) used to split ATC into vehicle types. No factoring required for age or seasonal variation

LDSJ34 Single 12 hour count on day of RSI Tue 19/05/2009

2 Weeks around the time of the RSI (May 2009)

MCC used to provide vehicle type proportions. ATC average excludes day of RSI due to possible traffic disruption. Factoring of count required for age (0.99) and seasonal variation (1.01).

I201 No One month – June 2008 Average vehicle type for urban main roads (in Leeds) used to split ATC into vehicle types. No factoring required for age or seasonal variation.

LDSJ7ELLR Single 12 hour count on day of RSI Tue 02/06/2009

2 Weeks around the time of the RSI (June 2009)

MCC used to provide vehicle type proportions. ATC average excludes day of RSI due to possible traffic disruption. Factoring of count required for age (0.99) but no seasonal variation factor required. Additional adjustments required to take account of traffic re-routing resulting from the opening of the East Leeds Link Road and Inner Ring Road Stage 7. This was based on traffic counts on this corridor before and after the opening of these schemes. Because of these adjustments, the confidence that we have in this count is therefore less than the other counts in this table.

LDS21 Single 12 hour count on day of RSI Wed 08/10/2008

2 Weeks around the time of the RSI (October 2008)

MCC used to provide vehicle type proportions. ATC average excludes day of RSI due to possible traffic disruption. No factoring required for age or seasonal variation.

Proxy318 No One month – September 2008 Average vehicle type for urban main roads (in Leeds) used to split ATC into vehicle types. No factoring required for age or seasonal variation.

4.4 Highway Journey Times

Journey times in the LTM have been validated through a comparison between modelled and observed journey times along 20

two directional routes. Two of these routes are used by the NGT service or compete directly with it. These are shown in Figure



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10. The proposed northern NGT route uses existing highway network (albeit with improved priority measures) for the majority of

the route. The journey time route therefore follows this from the outer ring road to the inner ring road. The proposed southern

NGT route is a mixture of on highway and off highway. In setting up the journey time comparison we have therefore used the

main highway route where the NGT service uses the highway along with the main road that runs parallel to the off road sections.

Figure 10 – Location of Journey Time Routes

The journey times along these routes are shown in Table 4. These data were obtained from TrafficMaster (via DfT and Leeds

City Council). It has been averaged over 2007/2008 after removing bank holidays, school holidays and weekends. Table 4

contains only data for 1 route, the second route being on the A61. This has not been included in the assessment as the observed

journey time data for this route spanned the period of the construction of East Leeds Link road and IRR stage 7 (journey times



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were materially affected by the road works associated by these schemes). AECOM have requested Leeds City Council to provide

the 2009 journey time data after the scheme construction had been completed; this journey time has been used to validate the

2009 base year model. Clearly, we will need to demonstrate that these results are acceptable as part of the overall adequacy of

the model for testing NGT.

The journey times on the A660 route is based on a minimum of 100 observations on each of the links in each of the time periods.

In many case there are over 300 observations – an average of more than one per day over the year. Some analysis of the data

shows that between 0700 and 0800 there is a high proportion of observations in the early part of the hour (69% before 07:30).

This is unlikely to be a true representation of the demand profile over the hour. In all other time periods the profile of observations

is spread more evenly across the hour.

Table 4 – Observed Journey Times (seconds)

Route Direction 07:00 08:00 09:00 IP 16:00 17:00 18:00

A660 Inbound 649 1125 785 754 862 759 720

Outbound 624 863 737 811 1228 1352 1011

A61 Inbound 369 387 362 365 408 430 391

Outbound 380 383 380 366 420 483 363

4.5 Public Transport Passenger Counts

The LTM Public Transport Assignment model has been calibrated to passenger counts that form a cordon around the city centre.

Two of these counts cross the NGT route – one on the northern route (Woodhouse Lane) and the other in the southern route

(Hunslet Road). The location of these two counts is shown in Figure 11. Not all bus routes operating in the northern NGT corridor

cross the cordon at Woodhouse Lane therefore it is appropriate to also include the counts on the two adjacent corridors

(Meanwood Road and Moorland Road) in this analysis.



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Figure 11 – Location of Public Transport Passenger Counts

These counts were collected as on vehicle counts. The surveys were carried out for one complete 12 hour day at each cordon

crossing point. As a result of the single day count the level of confidence that we have in this data is not as great as it would have

been if the count had been repeated over several days. The passenger counts are shown in Table 5.

Table 5 – Passenger Counts

Location Direction AM Peak IP PM Peak

Woodhouse Lane Inbound 1045 627 405

Outbound 342 697 1450

Meanwood Road Inbound 280 168 135

Outbound 82 147 345

Meanwood Rd Scothall Rd

Chapeltown Rd Roundhay Rd

Harehills Rd

Compton Rd

A64 York Rd

Lavender Wlk

Hunslet Rd

Dewsbury Rd Top Moor Side

Domestic Rd

Wellington Rd

Armley Rd

Kirkstall Rd

Burley Rd

Moorland Rd

Woodhouse Ln

NGT Route



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Moorland Road Inbound 292 200 136

Outbound 39 174 357

Hunslet Road Inbound 852 490 450

Outbound 313 569 1025

Model Acceptability Guidelines



Error! Reference source not found.

5.1 Introduction

This chapter sets out the Design Manual for Roads and Bridges (DMRB) and WebTAG acceptability guidelines on model

validation.

It should be noted that models which meet these guidelines are not necessarily fit for purpose and conversely models which don’t

meet them may be fit for purpose. It also depends on the way in which the model has been built and the ability of the observed

data to provide an realistic picture of typical travel conditions for the movements that are likely to be influenced by the scheme.

5.2 Highway Flow Validation

DMRB Volume 12, Section 2, Part 1, Chapter 4 provides acceptability guidelines for the validation of highway assignment model

flows. These are reproduced in Table 6 below.

Table 6 – Acceptability Guidelines for Highway Flows

Criteria Acceptability Guideline

Screenlines Differences between modelled flows and counts should be less than 5% of the counts

All or nearly all screenlines

Individual Count Locations Individual flows within 100 veh/h of counts for flows less than 700 veh/h

> 85% of cases

Individual flows within 15% of counts for flows from 700 to 2,700 veh/h

> 85% of cases

Individual flows within 400 veh/h of counts for flows more than 2,700 veh/

> 85% of cases

The criterion for screenlines assumes that there are at least 5 count locations forming the screenline. In some cases there was

not sufficient data to achieve this and some of the screenlines reported in the previous chapter have three and four count

locations. In these cases it is appropriate to accept a wider variation as the total flow is likely to be somewhere between that of a

single count site and the typical flow crossing a screenline. Where a single count is considered the acceptable margin is 15%.

Where a screenline has 5 count locations the acceptable margin reduces to 5%. It is therefore appropriate to assume that

screenlines with less than 5 locations should aim to achieve a margin between the two. If we apply a straight line between the

two extremes we get the acceptability guidelines as set out in Table 7.

Table 7 – Acceptability Guidelines for Highway Flows Crossing Short Screenlines

Number of Count

locations in

Screenline

Acceptable Difference

Between Modelled

Flow and Count

5 5%

4 7.5%

3 10%

2 12.5%

5.3 Highway Journey Time

The same chapter of DMRB also provides an acceptability guideline in relation to highway assignment model journey times. This

is reproduced in Table 8.

Table 8 – Acceptability Guideline for highway Journey Time

Criteria Acceptability Guideline

Modelled times along routes should be within 15% of surveyed times (or 1 minute, if higher)

> 85% of routes

5 Model Acceptability Guidelines



Error! Reference source not found.

5.4 Public Transport Model Passenger Flows

Acceptability guidelines in respect of public transport passenger flows in a public transport assignment model are set out in

WebTAG Unit 3.11.2, Paragraph 10.1.6. This has been reproduced below.

“Across modelled screenlines, modelled flows should, in total, be within 15% of the observed values. On individual links in the network, modelled flows should be within 25% of the counts, except where observed flows are particularly low (less

than 150).”

Validation of Highway Assignment

Model



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6.1 Introduction

This chapter provides a comparison between the observed and modelled highway flows and journey times in line with the

acceptability guidelines set out in Chapter 5.

6.2 Highway Screenline Flows

The flow comparison has been undertaken using screenline counts using the data set out in chapter 4 with that from the base

year model. The results of this comparison are shown in Table 9. Highlighted cells denote those screenlines falling within the

DMRB guidance criterion of within 5% of the modelled count. The proportion of screenlines meeting this criterion is summarised

at the bottom of the table.

6 Validation of Highway

Assignment Model



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Table 9 – Difference between Total Screenline Count and Modelled Flow (Cars)

Screenline and Direction

07:00 08:00 09:00 Inter-Peak

16:00 17:00 18:00 12 Hour

RSI10 IN Count 6056 6530 4986 3980 4664 4905 4676 55697

Observed 5985 6273 5037 3993 4687 4947 4442 55329

Diff -70 -258 51 13 23 42 -234 -368

%diff -1% -4% 1% 0% 1% 1% -5% -1%

RSI10 OUT Count 3488 4532 3473 4235 6379 7236 6484 57005

Observed 3073 4061 3369 4263 6182 7033 6302 55597

Diff -415 -471 -104 28 -197 -204 -182 -1408

%diff -12% -10% -3% 1% -3% -3% -3% -2%

CAL15 IN Count 3982 4392 3251 2617 3199 3266 2929 36720

Observed 3962 4203 3267 2624 3192 3255 2925 36547

Diff -20 -189 16 7 -7 -11 -4 -173

%diff 0% -4% 0% 0% 0% 0% 0% 0%

CAL15 OUT Count 1918 2840 2217 2680 4428 4756 4136 36374

Observed 1859 2621 2062 2494 4442 4805 4110 34865

Diff -59 -218 -155 -186 14 49 -27 -1510

%diff -3% -8% -7% -7% 0% 1% -1% -4%

RSI01 IN Count 6154 6826 4929 3543 3737 3649 3784 50336

Observed 5972 6573 5249 3830 3897 3733 3637 52042

Diff -182 -253 320 287 161 84 -147 1706

%diff -3% -4% 6% 8% 4% 2% -4% 3%

RSI01 OUT Count 2465 3347 3149 3722 6306 6699 5579 49876

Observed 2589 3519 3192 4199 6623 6873 5949 53936

Diff 123 172 43 477 316 174 369 4060

%diff 5% 5% 1% 13% 5% 3% 7% 8%

VAL14 IN Count 3330 3492 2648 2200 2484 2373 2276 29800

Observed 3178 3325 2682 2141 2332 2146 2095 28605

Diff -152 -167 34 -58 -152 -227 -180 -1195

%diff -5% -5% 1% -3% -6% -10% -8% -4%



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VAL14 OUT Count 1889 2303 2176 2319 3783 3892 3046 31003

Observed 1908 2544 2228 2630 3773 3910 3154 33296

Diff 20 241 52 311 -10 19 108 2293

%diff 1% 10% 2% 13% 0% 0% 4% 7%

RSI03 IN Count 7388 7005 5390 4062 5058 5454 4526 59193

Observed 7348 7278 5486 4142 5140 5435 4504 60045

Diff -39 273 96 80 82 -19 -22 852

%diff -1% 4% 2% 2% 2% 0% 0% 1%

RSI03 OUT Count 4298 4214 3172 4258 7965 8149 5632 58981

Observed 4329 4251 3362 4225 8167 8470 5761 59689

Diff 30 37 190 -34 202 321 129 708

%diff 1% 1% 6% -1% 3% 4% 2% 1%

RSI12 IN Count 8903 7373 5512 3977 4849 5707 4826 61035

Observed 8905 8029 5656 4042 4911 5481 4800 62031

Diff 2 655 143 64 62 -226 -26 996

%diff 0% 9% 3% 2% 1% -4% -1% 2%

RSI12 OUT Count 4544 4287 3458 4132 8158 7199 5734 58173

Observed 4785 4301 3473 4191 8209 8000 5909 59825

Diff 240 14 16 59 51 802 175 1652

%diff 5% 0% 0% 1% 1% 11% 3% 3%

RSI08 IN Count 2710 3156 2362 1951 2501 2853 2843 28133

Observed 2706 3013 2357 1993 2564 2790 2763 28152

Diff -5 -143 -5 42 63 -63 -80 19

%diff 0% -5% 0% 2% 3% -2% -3% 0%

RSI08 OUT Count 2294 2577 2176 2202 3111 3382 2892 29642

Observed 2390 2526 2104 2343 3306 3599 3056 31037

Diff 95 -51 -72 141 195 218 164 1394

%diff 4% -2% -3% 6% 6% 6% 6% 5%

Screenlines Passing

11 9 11 9 11 11 11 12

% Passing

79% 64% 79% 64% 79% 79% 79% 86%

Highlighted cells indicate those passing the DMRB Acceptability Guidelines



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The final two rows in Table 9 show how the screenline flows compare across the various model time periods. It can be seen that,

typically, nearly 80% of the screenlines in question have modelled flows within 5% of the observed flows. The exceptions to this

are 0800-0900 and Interpeak where 64% of screenlines meet the 5% criterion. It can further be seen that many of the screenlines

that fail to meet the 5% criterion only fail by a small number of percentage points.

More detail on the quality of model fit at individual screenline level is provided below:

- North Route

- RSI 10: the 5% criterion is satisfied for all but two hours (0700 and 0800 outbound).

- CAL 15: the 5% criterion is satisfied for all but three model hours, 0800, 0900 and interpeak outbound, all of which are just

7-8% different from the observed counts.

- RSI 01: half of the modelled hours fail to meet the 5% criterion. Those directions/hours failing to meet the criterion generally

fail by relatively small margins – typically 5-8% - with only interpeak (outbound) failing by more than 10%.

- VAL 14: five of the 14 modelled hours fail to meet the criteria. Three of these five have modelled flows over 10% different to

the observed counts.

- RSI 08: This screenline generally represents the observed counts well. Whilst four of the outbound hours fail to meet the

5% criterion, all four have modelled flows 6% different to those observed, failing by only a narrow margin.

- South Route

- RSI 03: This screenline generally represents the observed flows very well. Only one hour/direction fall outside the 5%

criterion – 0900, outbound – and, with modelled flows 6% different to those observed, it only fails by a very small margin.

- RSI 12: Of the three hours/directions that fail to meet the 5% criterion, only one fails by more than 10%.

It can be seen from Table 9 and the discussion above that, at screenline level, the model generally represents flows reasonably

well in the NGT corridors. Of the individual screenlines, only one, VAL14, has a significant number of hours/directions where the

modelled flow is more than 10% different to the observed flow. All other screenlines, whilst including a small number of

screenlines/directions where the 5% criterion is not met, generally only fail to meet the criterion by a small amount for the majority

of cases.

Individual Count Comparison

Comparisons between the individual counts along the NGT route and the modelled flows at these points have also been

undertaken. Detailed results are shown in Appendix B showing the observed, modelled and difference between counts for each

time period. Table 10 shows how the individual counts perform against the DMRB criteria highlighted in the previous section.

Shaded counts are those directly on the NGT route.

It can be seen that between 63% and 77% of counts meet the DMRB criterion in each time period. The 0800 period performs

worst with the earlier and later hours of each individual peak period generally providing the best overall performance. The shaded

counts on the NGT routes themselves generally perform very well, with most passing the DMRB criterion in all time periods and

only one count, CAL15, I235 failing in more than one time period.

Table 10 – Individual Count Summary

ScreenLine Site Direction 700 800 900 IP 1600 1700 1800

RSI01 LDSJ31 IN PASS PASS FAIL FAIL FAIL FAIL FAIL

RSI01 LDSJ32 IN PASS PASS PASS PASS PASS PASS PASS

RSI01 LDSJ33 IN PASS FAIL PASS PASS PASS PASS PASS

RSI01 LDSJ34 IN PASS PASS PASS PASS PASS PASS PASS

RSI01 LDSJ35CALI IN FAIL PASS FAIL PASS PASS PASS PASS

RSI01 Proxy345 IN PASS FAIL FAIL FAIL PASS PASS FAIL

RSI01 LDSJ36 IN FAIL FAIL FAIL FAIL PASS PASS FAIL



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RSI01 Proxy346 IN FAIL PASS PASS PASS PASS FAIL PASS

RSI01 LDSJ31 OUT PASS FAIL FAIL FAIL PASS PASS FAIL

RSI01 LDSJ32 OUT PASS PASS PASS PASS PASS PASS PASS



RSI01 LDSJ35CALI OUT PASS PASS PASS PASS PASS FAIL FAIL

RSI01 Proxy345 OUT PASS PASS PASS PASS FAIL FAIL FAIL

RSI01 LDSJ36 OUT PASS PASS PASS FAIL PASS PASS FAIL

RSI01 Proxy346 OUT PASS PASS PASS PASS PASS PASS PASS

RSI10 NWL7 IN PASS PASS PASS PASS PASS PASS PASS

RSI10 LDS4CALI IN FAIL FAIL FAIL FAIL PASS PASS PASS

RSI10 LDS5 IN FAIL FAIL FAIL FAIL PASS PASS PASS

RSI10 Proxy312 IN PASS PASS PASS PASS PASS PASS PASS

RSI10 LDS35 IN FAIL PASS PASS FAIL FAIL FAIL FAIL

RSI10 LDS6 IN PASS PASS PASS FAIL FAIL FAIL FAIL

RSI10 LDS7 IN PASS PASS PASS PASS PASS PASS PASS



RSI10 LDS10 IN PASS FAIL PASS PASS PASS PASS PASS

RSI10 LDS11 IN PASS FAIL FAIL PASS FAIL PASS FAIL

RSI10 NWL7 OUT PASS PASS PASS PASS PASS PASS PASS

RSI10 LDS4CALI OUT PASS PASS PASS FAIL FAIL PASS FAIL

RSI10 LDS5 OUT FAIL FAIL FAIL FAIL FAIL FAIL FAIL

RSI10 Proxy312 OUT PASS FAIL PASS PASS FAIL PASS PASS

RSI10 LDS35 OUT PASS PASS PASS FAIL FAIL FAIL FAIL

RSI10 LDS6 OUT PASS PASS PASS FAIL FAIL FAIL FAIL

RSI10 LDS7 OUT PASS PASS PASS PASS PASS PASS PASS



RSI10 LDS10 OUT FAIL FAIL PASS PASS PASS FAIL FAIL

RSI10 LDS11 OUT FAIL FAIL PASS PASS PASS PASS PASS

CAL15 I118 IN PASS FAIL FAIL FAIL PASS PASS PASS

CAL15 2008_333 IN FAIL FAIL PASS PASS PASS PASS PASS

CAL15 2008_335 IN PASS PASS PASS PASS PASS PASS PASS

CAL15 2009_264 IN PASS FAIL FAIL FAIL PASS PASS PASS



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CAL15 I235 IN PASS FAIL FAIL FAIL PASS PASS PASS

CAL15 CP979265 IN FAIL PASS PASS PASS PASS PASS PASS

CAL15 I208 IN PASS FAIL PASS FAIL PASS PASS PASS

CAL15 2005_310 IN PASS FAIL PASS FAIL PASS PASS PASS

CAL15 2007_561 IN PASS PASS PASS PASS PASS PASS PASS

CAL15 I118 OUT PASS PASS PASS PASS FAIL FAIL PASS

CAL15 2008_333 OUT PASS PASS PASS PASS PASS PASS PASS

CAL15 2008_335 OUT PASS PASS PASS PASS FAIL FAIL FAIL


CAL15 I235 OUT PASS PASS PASS PASS PASS PASS PASS

CAL15 CP979265 OUT PASS PASS PASS PASS PASS PASS PASS

CAL15 I208 OUT FAIL FAIL FAIL FAIL FAIL FAIL FAIL

CAL15 2005_310 OUT PASS PASS PASS PASS FAIL FAIL FAIL


CAL26 2009_439 IN PASS FAIL FAIL FAIL PASS PASS PASS

CAL26 2007_024 IN FAIL FAIL FAIL FAIL PASS PASS PASS

CAL26 5879Site13_C IN PASS PASS PASS PASS PASS PASS PASS

CAL26 2009_439 OUT PASS FAIL PASS PASS PASS PASS PASS


CAL26 5879Site13_C OUT PASS PASS PASS PASS PASS FAIL PASS

VAL14 I201 IN PASS PASS PASS PASS PASS PASS PASS

VAL14 I414 IN PASS PASS PASS PASS PASS PASS PASS

VAL14 I413 IN FAIL FAIL FAIL FAIL FAIL FAIL PASS

VAL14 I412 IN PASS FAIL PASS FAIL FAIL FAIL FAIL

VAL14 I411 IN FAIL PASS PASS PASS PASS PASS PASS

VAL14 I201 OUT PASS FAIL PASS PASS PASS PASS PASS

VAL14 I414 OUT PASS PASS PASS PASS PASS PASS PASS

VAL14 I413 OUT FAIL FAIL FAIL FAIL PASS PASS PASS

VAL14 I412 OUT PASS FAIL PASS PASS PASS FAIL PASS

VAL14 I411 OUT PASS PASS PASS PASS PASS PASS PASS

RSI03 LDSJ10 IN FAIL FAIL PASS PASS PASS PASS PASS

RSI03 LDSJ12ELLR IN PASS PASS PASS PASS PASS PASS PASS

RSI03 LDSJ7ELLR IN PASS PASS PASS PASS PASS PASS PASS

RSI03 Proxy26 IN FAIL FAIL PASS PASS PASS PASS PASS

RSI03 LDSJ5 IN PASS FAIL PASS FAIL FAIL FAIL FAIL



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RSI03 LDSJ6 IN PASS FAIL FAIL FAIL FAIL FAIL FAIL

RSI03 Proxy82 IN PASS PASS PASS PASS PASS PASS PASS

RSI03 LDSJ10 OUT FAIL FAIL FAIL FAIL FAIL FAIL FAIL

RSI03 LDSJ12ELLR OUT FAIL FAIL FAIL FAIL PASS FAIL FAIL

RSI03 LDSJ7ELLR OUT PASS PASS PASS PASS PASS PASS PASS


RSI03 LDSJ5 OUT PASS PASS PASS PASS PASS FAIL PASS

RSI03 LDSJ6 OUT PASS PASS PASS PASS PASS FAIL PASS


RSI12 LDS18 IN PASS PASS FAIL FAIL FAIL FAIL FAIL

RSI12 LDS19 IN PASS PASS FAIL FAIL FAIL FAIL FAIL

RSI12 LDS20 IN PASS FAIL PASS PASS PASS PASS PASS


RSI12 Proxy318 IN PASS FAIL PASS PASS PASS PASS PASS

RSI12 LDS22 IN FAIL FAIL PASS PASS PASS PASS PASS

RSI12 LDSA1 IN FAIL FAIL PASS PASS FAIL FAIL PASS

RSI12 LDS18 OUT FAIL FAIL FAIL FAIL FAIL FAIL FAIL

RSI12 LDS19 OUT FAIL FAIL FAIL FAIL FAIL PASS FAIL

RSI12 LDS20 OUT PASS PASS PASS PASS PASS PASS FAIL

RSI12 LDS21 OUT PASS PASS PASS PASS FAIL FAIL PASS

RSI12 Proxy318 OUT PASS PASS PASS PASS PASS FAIL PASS


RSI12 LDSA1 OUT PASS PASS PASS PASS PASS PASS PASS

RSI08 LDSB1 IN PASS PASS PASS PASS PASS PASS PASS

RSI08 LDSB1 OUT PASS PASS PASS PASS PASS PASS PASS


RSI08 LDSB2 OUT PASS PASS PASS PASS PASS PASS PASS


RSI08 LDSB3 OUT PASS PASS PASS FAIL FAIL FAIL FAIL

Proportion meeting DMRB Criterion 77% 63% 77% 69% 75% 71% 73%



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6.3 Highway Journey Times

A comparison between observed and modelled journey times has been undertaken for two routes. The results are shown in It

can be seen that the model generally exhibits a good fit to the observed data. The A61 Hunslet Road corridor meets the DMRB

criterion of modelled journey times being within 15% or 60 seconds of those observed for all time periods in both the inbound and

outbound directions. The A660 Otley Road corridor meets the criterion in all but three cases, all of which are in the AM peak

period. For two of these time periods/directions where the criterion is not met, the failure is only marginal, being 20% and 21%

respectively. It is worth noting, however, that the model exhibits an excellent fit against observed journey times in the 0800 hour,

modelled journey times being just 1% (inbound) and 3% (outbound) different to observed times.



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Table 11.

It can be seen that the model generally exhibits a good fit to the observed data. The A61 Hunslet Road corridor meets the DMRB

criterion of modelled journey times being within 15% or 60 seconds of those observed for all time periods in both the inbound and

outbound directions. The A660 Otley Road corridor meets the criterion in all but three cases, all of which are in the AM peak

period. For two of these time periods/directions where the criterion is not met, the failure is only marginal, being 20% and 21%

respectively. It is worth noting, however, that the model exhibits an excellent fit against observed journey times in the 0800 hour,

modelled journey times being just 1% (inbound) and 3% (outbound) different to observed times.



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Table 11 – Observed and Modelled Highway Journey Times (seconds)

A660 Otley Road A61 Hunslet Road

Inbound Outbound Inbound Outbound

07:00

Obs 649 624 369 380

Model 929 749 365 378

Diff 280 125 -4 -3

% Diff 43% 20% -1% -1%

DMRB? FAIL FAIL PASS PASS

08:00

Obs 1125 863 387 383

Model 1133 887 368 375

Diff 8 24 -19 -8

% Diff 1% 3% -5% -2%

DMRB? PASS PASS PASS PASS

09:00

Obs 785 737 362 380

Model 950 830 352 366

Diff 165 93 -10 -14

% Diff 21% 13% -3% -4%

DMRB? FAIL PASS PASS PASS

Inter-Peak

Obs 754 811 365 366

Model 850 780 349 380

Diff 96 -31 -16 14

% Diff 13% -4% -4% 4%


16:00

Obs 862 1228 408 420

Model 876 1118 377 441

Diff 14 -110 -31 21

% Diff 2% -9% -8% 5%


17:00

Obs 759 1352 430 483

Model 847 1341 369 418

Diff 88 -12 -61 -65

% Diff 12% -1% -14% -13%


18:00

Obs 720 1011 391 363

Model 827 1007 361 364

Diff 107 -4 -30 1

% Diff 15% 0% -8% 0%




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6.4 Model Analysis by Time Period

This section provided a more detailed view of the performance of the model across all time periods. Figures 12 – 18 provide a

schematic view of the NGT corridors with observed and modelled flows and journey times on the various sections shown.

Time Period 0700

Figure 12 shows that during the 07:00 hour the inbound flow on the northern route is low on the approach to the Outer Ring

Road but high between the ring road and the city centre. The modelled inbound journey time is higher than the observed value.

In the outbound direction the flow comparison shows some high and some low modelled flows. Again the modelled journey time

is too high. On the southern route the inbound modelled flow is close to the observed level in the inbound direction but high in the

outbound.

Time Period 0800

Figure 13 shows that the modelled flow approaching the Outer Ring Road is lower than the observed value with the flow on the

rest of the inbound section of the northern route is too high, particularly between the outer ring road and Hyde Park. Outbound

the modelled flow is a mixture of above and below the observed values. On the southern route the modelled flows generally

represent the observed flows reasonably well although modelled flows are low on the A61 inbound section. Journey times are

well represented in all time periods.

Time Period 0900

Figure 14 demonstrates that In the 09:00 time period the modelled flows outside the Outer Ring Road are very close to the

observed values. The inbound flow from the north is generally a little high whereas the outbound is variable. Journey times are

longer than observed both inbound and outbound. On the southern route the outbound flow is slightly high while the inbound is

generally slightly low. Journey times are within DMRB criteria both inbound and outbound.

Time Period Inter-Peak

From Figure 15 it can be seen that during the inter-peak the modelled flows outside the Outer Ring Road are almost identical to

the observed ones. In the rest of the inbound direction of the northern route the flows are higher than observed but generally

exhibit a good fit in the outbound direction. The modelled journey time in both directions are both within the DMRB limits. On the

southern route the inbound flow is lower than observed but very close to observed values outbound. Flows on the M621 are very

close to the observed values. Journey times on the southern route are both well within DMRB criteria.

Time Period 1600

Figure 16 shows that during the 16:00 hour the modelled flows outside the Outer Ring road are very close to the observed

values. On the rest of the Northern inbound corridor the modelled flows are very close to the observed values at two of the three

sites with the remaining site being a little low. In the outbound direction the modelled flows are higher than the observed close to

the city centre but exhibit a good fit beyond Hyde Park. The modelled journey times are well within the DMRB criteria. On the

southern route the inbound modelled flows very close to the observed values at the inner end of the route in both directions but

there is some variation further towards the route terminus. Modelled flows on the M621 are very close to the observed values.

Modelled journey times on the southern section represent a good fit against those observed.

Time Period 1700

Figure 17 shows that during 1700 the modelled flows on most sections of the northern route are close to the observed values,

the main exception being inbound close to the city centre where modelled flows are below the observed values. The journey

times are within the DMRB criteria. On the southern route there is a mixed picture with the outer outbound flows and inner

inbound modelled flows both being below the observed . The modelled flows on the M621 are close to the observed values.

Modelled journey times are below observed in both directions but within DMRB criteria.

Time Period 1800

Figure 18 demonstrates that, in the 18:00 hour, the modelled flows on the northern route are generally close to the observed

values with the exception of the inner count close to the city centre where modelled flows are low (inbound) and high (outbound).

Modelled journey times are within DMRB criteria but the some 15% higher inbound. On the southern route a generally moxed



Transportation

picture is seen with inbound modelled flows being generally more variable, including being 12% below the observed on the inner

section. There is a good fit on the M621. Modelled journey times are both comfortably within DMRB criteria.

Overall comments

The analysis in this section shows a generally good fit between modelled and observed car flows along the NGT corridor with a

high proportion of the count locations meeting the DMRB criteria in each time period. There is some variation between adjacent

count sites but this is generally within the confidence limits of the counts.

During the AM hours there is a tendency for the modelled flows in the inbound direction of the northern route to be too high and

the inbound modelled journey time in the 07:00 and 08:00 hours doesn’t match the observed data as well as in other hours.

However, the overall fit is considered to be good enough to enable the model to be used for the testing of NGT.



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Figure 12 – Flows and Journey Times 0700



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Figure 15 – Flows and Journey Times Inter-Peak



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Highway Model Behaviour in Outer

Simulation Area



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7.1 Response of Highway Model to NGT Scheme

A fuller description of the testing undertaken for the NGT scheme will be reported elsewhere in the business case. However, we

are aware of the need to provide some indication of the operation of the highway model in the area outside of Leeds. There is an

area mainly to the south and west of Leeds which is fully modelled but where only a limited amount of validation has taken place.

While this area lies outside of the main area of influence of the NGT scheme it is possible that some trips attracted to the park

and ride element of NGT could pass through these areas.

Our analysis of this issue is based upon inspection of the change in delays in the Highway Model between the “Core Scenario”

and “with NGT” scenarios in the outer areas of Leeds to understand the likely nature and level of cost changes. Where there are

significant changes to delays in these areas then significant benefits/dis-benefits in the economic appraisal of the scheme are

likely to be arise. Since the validation of the model is less comprehensive in these outer areas less confidence can be attributed

to results from these areas. Therefore, it is useful to understand the changes to delays in these areas to understand the likely

scale of impact on the overall economic appraisal results.

The 2031 model has been used to analyse these impacts. The scale of change is likely to be amplified with the greater traffic

demands in this year and it also has a greater impact on the overall 60 year appraisal result. Models from the 0800, interpeak

and 1700 hours are compared. The “bandwidths” on each link show where there is a difference in delay between the Core and

NGT scenarios in excess of 20 seconds. The shaded area is the approximate area of the model where the calibration/validation

is considered to be of a good standard.

Figure 19 shows the comparison for the 0800-0900 hour. It can be seen that the changes in delay are generally along the

corridors directly affected by the NGT scheme with further impacts generally close to the outer ring road. There are minimal

changes further beyond the outer ring road.

Figure 20 shows the same comparison for the interpeak period. Given the generally lower traffic demands in this time period it is,

perhaps, unsurprising to see that the scale and location of delays is generally smaller and restricted almost exclusively to the

NGT affected corridor.

Figure 21 shows the comparison for the 1700-1800 period. It is notable that there are further large delays in the north-western

section of Leeds. However, these are generally restricted to the area within, or very close to, the outer ring road where the level

of model validation is relatively comprehensive.

In general, it can be seen that the scale and location of changes to delay is generally relatively small and restricted to the areas

within and close to the outer ring road in the north of the city. South of the city, beyond the M1 and M621, there are few places

where delays change substantially.

Overall, the analysis here shows that the impact of the NGT scheme on general traffic is largely restricted to the corridors where

it might logically be expected. There is relatively little impact in those areas of the model beyond the outer ring road where the

level of model validation is less comprehensive.

7 Highway Model Behaviour in

Outer Simulation Area



Transportation

Figure 19 – 2031 0800-0900 Delay Comparison



Transportation

Figure 20 – 2031 Interpeak Delay Comparison



Transportation

Figure 21 – 2031 1700-1800 Delay Comparison

Validation of Public Transport

Assignment Model



Transportation

8.1 Introduction

This chapter sets out the comparison between observed and modelled passenger flows in the NGT corridor.

8.2 Passenger Flows

Comparisons have been made between the observed passenger flows and modelled flows at two locations along the NGT route.

These are shown in Table 12and Table 13.

Table 12 – Modelled Passenger Flows

Location Direction AM Peak IP PM Peak

Woodhouse Lane Inbound 961 663 395

Outbound 331 649 1173

Meanwood Road Inbound 220 149 50

Outbound 69 138 288

Moorland Road Inbound 228 200 73

Outbound 120 159 297

Hunslet Road Inbound 828 582 432

Outbound 274 562 1177

Table 13 – Difference between Observed and Modelled Passenger Flows

Location Direction Acceptability

Criteria AM Peak IP PM Peak

Woodhouse Lane Inbound +/-25% -8% +6% -3%

Outbound +/-25% -3% -7% -19%

Meanwood Road Inbound +/-25% -21% -11% N/A

Outbound +/-25% N/A N/A -17%

Moorland Road Inbound +/-25% -22% 0% N/A

Outbound +/-25% N/A -9% -17%

Hunslet Road Inbound +/-25% -3% +19% -4%

Outbound +/-25% -12% -1% +15%

Highlighted values meet WebTAG acceptability criteria or the observed flow is below the limit at which the criteria apply.

These results show that 100% of the passenger flows meet the WebTAG acceptability criteria and in most cases are well within

the criteria. This exceeds the acceptability guidelines within WebTAG.The largest percentage differences are on the more minor

routes adjacent to the northern NGT corridor rather than on the NGT route itself.

8 Validation of Public Transport

Assignment Model

Conclusion



Transportation

9.1 Introduction

The purpose of the report so far is to demonstrate that the Leeds Transport Model (LTM) has been built and validated sufficiently

well to reflect base year travel conditions within the NGT corridor. This chapter sets out the conclusions from the previous

chapters.

9.2 Overall Model

The overall model specification and the manner in which it has been built is set out in separate model development reports. In

addition a report of survey is has also been prepared. Between them these reports set out the overall standard of validation

achieved in the model. We believe that these reports show that the specification of LTM is a substantial improvement on the

model that has previously been used to assess NGT. It has been constructed with the purpose of being able to test schemes

such as NGT.

The demand model has been built to include all the necessary choices to enable the model to be used to test NGT. The

validation of the demand model is set out in the Demand Model Report. The demand model is currently being re-calibrated but

we are confident that we will be able to demonstrate that it is adequate for testing NGT.

9.3 Highway Assignment Model Validation

It can be seen from Section 6 that, depending upon the time period in question, 64% - 79% of screenlines have a modelled count

that matches the relevant DMRB criterion. The PM peak gives a stronger overall result being at 79% for all three modelled hours

in this peak. It terms of individual counts, between 63% and 77% of counts match the DMRB criterion.

When looking at the model at individual time periods the modelled flows generally match well when compared with the observed

values. A high proportion of them meet DMRB criteria in each time period and while the proportion meeting DMRB criteria

doesn’t meet the acceptability level in all time periods we consider that it is close enough to make the model adequate for testing

NGT.

In terms of journey times, it can be seen that the model generally exhibits a good fit to the observed data. The A61 Hunslet Road

corridor meets the DMRB criterion for all time periods in both the inbound and outbound directions. The A660 Otley Road corridor

meets the criterion in all but three cases, all of which are in the AM peak period. For two of these time periods/directions where

the criterion is not met, the failure is only marginal. The model exhibits an excellent fit against observed journey times in the 0800

hour, modelled journey times being just 1% (inbound) and 3% (outbound) different to observed times.

We believe that the data presented in this report shows that the highway model has been built and validated to the base year

travel conditions sufficiently well along the NGT corridor to enable the model to be used to test the NGT scheme. Traffic flows are

within, or close to, the DMRB acceptability guidelines and the journey times are also very close to meeting the acceptability

guidelines.

9.4 Public Transport Assignment Model Validation

The passenger flow validation along the two corridors in which NGT is proposed to operate and in the adjacent corridors of the

northern route all meet the acceptability criteria. We therefore consider that the Public Transport Assignment Model is suitable for

testing the NGT scheme.

9 Conclusion



Transportation




Transportation


Appendix B – Base Year Highway Flow Comparison



Transportation

Table 14 - Flow Difference at individual count sites

ScreenLine Site Direction 07:00 08:00 09:00 IP 16:00 17:00 18:00

RSI10 LDS10 IN

Observed 1005 1056 821 649 827 879 942

Model 933 838 933 700 936 974 842

Difference -72 -218 112 51 109 95 -101

% Difference -7% -21% 14% 8% 13% 11% -11%

RSI10 LDS11 IN

Observed 360 428 355 255 306 359 359

Model 264 284 237 204 201 268 213

Difference -96 -145 -117 -51 -106 -91 -147

% Difference -27% -34% -33% -20% -34% -25% -41%

RSI10 LDS35 IN

Observed 324 316 297 155 165 181 163

Model 437 362 375 358 417 461 393

Difference 114 46 78 202 252 280 230

% Difference 35% 15% 26% 130% 152% 155% 141%

RSI10 LDS4CA

LI IN

Observed 481 606 448 446 423 471 408

Model 368 417 238 327 404 469 369

Difference -113 -189 -210 -119 -19 -2 -39

% Difference -23% -31% -47% -27% -4% 0% -10%

RSI10 LDS5 IN

Observed 427 411 276 316 401 517 366

Model 690 750 505 444 406 457 392

Difference 262 339 229 128 5 -60 26

% Difference 61% 82% 83% 41% 1% -12% 7%

RSI10 LDS6 IN

Observed 492 585 342 260 300 310 273

Model 410 581 275 63 71 93 52

Difference -82 -5 -67 -197 -229 -217 -221

% Difference -17% -1% -19% -76% -76% -70% -81%

RSI10 LDS7 IN

Observed 921 987 657 503 619 577 575

Model 825 900 662 495 588 572 558

Difference -96 -87 5 -8 -31 -5 -17

% Difference -10% -9% 1% -2% -5% -1% -3%

RSI10 LDS8 IN

Observed 388 506 316 210 234 205 233

Model 423 532 321 212 234 198 239

Difference 35 26 5 1 0 -7 6

% Difference 9% 5% 2% 1% 0% -3% 3%

RSI10 LDS9 IN Observed 723 861 721 495 548 548 541

Appendix B – Base Year Highway

Flow Comparisons



Transportation

Model 745 929 740 506 567 572 541

Difference 21 68 19 10 18 24 0

% Difference 3% 8% 3% 2% 3% 4% 0%

RSI10 NWL7 IN

Observed 865 650 673 610 720 749 710

Model 835 627 691 610 735 738 725

Difference -30 -23 18 0 15 -10 14

% Difference -3% -4% 3% 0% 2% -1% 2%

RSI10 Proxy312 IN

Observed 69 124 81 80 119 110 105

Model 55 53 60 74 128 145 118

Difference -14 -71 -21 -6 8 35 13

% Difference -20% -58% -26% -7% 7% 31% 12%

RSI10 LDS10 OUT

Observed 893 792 609 744 1088 1246 1209

Model 621 579 557 729 927 920 1011

Difference -272 -213 -52 -15 -161 -326 -198

% Difference -30% -27% -8% -2% -15% -26% -16%

RSI10 LDS11 OUT

Observed 252 451 271 260 429 477 410

Model 142 177 197 282 360 457 392

Difference -110 -274 -74 22 -70 -20 -18

% Difference -44% -61% -27% 8% -16% -4% -4%

RSI10 LDS35 OUT

Observed 180 246 229 181 333 359 287

Model 172 314 316 344 548 644 509

Difference -8 69 87 163 216 285 222

% Difference -4% 28% 38% 90% 65% 79% 77%

RSI10 LDS4CA

LI OUT

Observed 303 489 349 402 549 578 537

Model 221 389 261 300 445 504 388

Difference -82 -99 -88 -102 -104 -73 -149

% Difference -27% -20% -25% -25% -19% -13% -28%

RSI10 LDS5 OUT

Observed 164 242 172 288 430 522 413

Model 291 486 353 491 643 679 662

Difference 127 244 181 203 212 157 249

% Difference 77% 101% 105% 70% 49% 30% 60%

RSI10 LDS6 OUT

Observed 135 255 167 269 432 558 479

Model 125 183 81 113 251 386 285

Difference -10 -72 -86 -155 -180 -172 -194

% Difference -8% -28% -52% -58% -42% -31% -41%

RSI10 LDS7 OUT Observed 418 457 441 499 716 813 754



Transportation

Model 397 478 442 503 699 811 755

Difference -21 21 2 4 -17 -2 1

% Difference -5% 5% 0% 1% -2% 0% 0%

RSI10 LDS8 OUT

Observed 127 229 149 221 381 484 438

Model 127 224 151 223 388 495 445

Difference 0 -5 2 2 6 11 7

% Difference 0% -2% 1% 1% 2% 2% 2%

RSI10 LDS9 OUT

Observed 274 458 376 532 821 862 848

Model 289 466 397 532 837 904 853

Difference 15 8 21 1 16 42 5

% Difference 5% 2% 6% 0% 2% 5% 1%

RSI10 NWL7 OUT

Observed 643 673 555 656 919 1050 891

Model 636 679 543 662 927 1043 882

Difference -7 7 -12 6 7 -7 -9

% Difference -1% 1% -2% 1% 1% -1% -1%

RSI10 Proxy312 OUT

Observed 100 243 155 183 280 288 217

Model 54 86 71 84 159 190 119

Difference -47 -157 -84 -99 -122 -99 -98

% Difference -47% -65% -54% -54% -43% -34% -45%

CAL15 2005_31

0 IN

Observed 294 562 295 226 273 274 261

Model 349 454 340 352 273 302 339

Difference 55 -108 46 125 0 28 78

% Difference 19% -19% 16% 55% 0% 10% 30%

CAL15 2007_56

1 IN

Observed 2 3 3 4 4 4 4

Model 0 0 0 0 0 0 0

Difference -2 -3 -3 -4 -4 -4 -4

% Difference -100% -100% -100% -100% -100% -100% -100%

CAL15 2008_33

3 IN

Observed 290 296 192 157 178 199 160

Model 169 125 99 100 134 132 113

Difference -121 -171 -93 -57 -44 -67 -47

% Difference -42% -58% -48% -36% -25% -34% -29%

CAL15 2008_33

5 IN

Observed 320 367 334 299 458 454 369

Model 333 422 337 251 458 505 327

Difference 13 55 3 -49 0 51 -42

% Difference 4% 15% 1% -16% 0% 11% -11%

CAL15 2009_26 IN Observed 619 764 437 295 362 354 290



Transportation

4 Model 651 607 331 145 368 386 266

Difference 32 -157 -106 -150 6 32 -24

% Difference 5% -21% -24% -51% 2% 9% -8%

CAL15 CP97926

5 IN

Observed 345 457 200 160 208 185 185

Model 244 373 205 197 207 215 179

Difference -101 -84 5 37 -1 30 -6

% Difference -29% -18% 2% 23% -1% 16% -3%

CAL15 I118 IN

Observed 891 732 657 529 636 662 572

Model 968 913 775 651 677 647 668

Difference 78 181 118 123 41 -16 96

% Difference 9% 25% 18% 23% 7% -2% 17%

CAL15 I208 IN

Observed 369 549 405 327 346 364 365

Model 269 447 338 188 354 368 288

Difference -100 -102 -66 -139 8 5 -77

% Difference -27% -19% -16% -42% 2% 1% -21%

CAL15 I235 IN

Observed 854 661 728 619 732 771 723

Model 980 861 842 740 720 700 746

Difference 127 200 113 121 -12 -71 23

% Difference 15% 30% 16% 20% -2% -9% 3%

CAL15 2005_31

0 OUT

Observed 158 374 202 254 537 684 530

Model 217 314 226 323 831 928 718

Difference 59 -60 24 70 294 244 188

% Difference 37% -16% 12% 28% 55% 36% 35%

CAL15 2007_56

1 OUT

Observed 7 21 12 12 25 24 23

Model 0 0 0 0 0 0 0

Difference -7 -21 -12 -12 -25 -24 -23

% Difference -100% -100% -100% -100% -100% -100% -100%

CAL15 2008_33

3 OUT

Observed 82 138 127 157 244 234 229

Model 67 107 98 126 217 205 225

Difference -16 -31 -29 -31 -27 -28 -4

% Difference -19% -22% -23% -20% -11% -12% -2%

CAL15 2008_33

5 OUT

Observed 332 379 254 300 448 452 411

Model 299 357 224 237 289 307 306

Difference -33 -22 -30 -63 -159 -145 -105

% Difference -10% -6% -12% -21% -35% -32% -25%

CAL15 2009_26

4 OUT

Observed 130 192 176 236 537 601 433

Model 84 157 134 182 524 613 465



Transportation

Difference -46 -34 -41 -54 -13 12 32

% Difference -35% -18% -24% -23% -2% 2% 7%

CAL15 CP97926

5 OUT

Observed 71 179 132 190 433 501 350

Model 97 179 108 176 498 566 439

Difference 26 0 -24 -13 65 65 89

% Difference 37% 0% -18% -7% 15% 13% 26%

CAL15 I118 OUT

Observed 412 565 436 513 825 867 819

Model 464 621 498 603 986 1011 917

Difference 52 56 62 89 161 144 98

% Difference 13% 10% 14% 17% 20% 17% 12%

CAL15 I208 OUT

Observed 236 336 299 376 471 418 411

Model 128 166 107 119 198 219 197

Difference -108 -170 -192 -257 -272 -199 -214

% Difference -46% -51% -64% -68% -58% -48% -52%

CAL15 I235 OUT

Observed 489 656 578 643 907 975 930

Model 504 720 666 729 898 956 843

Difference 14 64 87 86 -9 -20 -87

% Difference 3% 10% 15% 13% -1% -2% -9%

RSI01 LDSJ31 IN

Observed 1524 1749 1159 690 700 660 734

Model 1690 1813 1452 1094 1053 992 856

Difference 166 65 293 404 353 332 122

% Difference 11% 4% 25% 59% 50% 50% 17%

RSI01 LDSJ32 IN

Observed 1009 1179 803 497 443 407 424

Model 979 1042 804 506 463 442 468

Difference -30 -138 1 9 20 35 44

% Difference -3% -12% 0% 2% 4% 9% 10%

RSI01 LDSJ33 IN

Observed 156 297 225 238 306 291 283

Model 72 142 136 159 240 319 204

Difference -84 -155 -89 -79 -66 28 -79

% Difference -54% -52% -40% -33% -22% 10% -28%

RSI01 LDSJ34 IN

Observed 908 917 712 556 559 581 555

Model 939 968 753 573 567 499 545

Difference 32 51 41 17 7 -82 -9

% Difference 3% 6% 6% 3% 1% -14% -2%

RSI01 LDSJ35C

ALI IN

Observed 200 368 223 167 226 200 197

Model 95 277 112 132 157 161 131



Transportation

Difference -105 -91 -111 -35 -69 -40 -66

% Difference -52% -25% -50% -21% -30% -20% -33%

RSI01 LDSJ36 IN

Observed 92 140 106 92 106 107 97

Model 243 538 396 210 186 185 198

Difference 151 398 290 119 80 77 101

% Difference 165% 284% 273% 129% 76% 72% 104%

RSI01 Proxy345 IN

Observed 552 612 503 358 277 265 356

Model 536 402 391 244 226 187 227

Difference -17 -209 -112 -114 -51 -78 -130

% Difference -3% -34% -22% -32% -18% -29% -36%

RSI01 Proxy346 IN

Observed 1714 1564 1198 945 1119 1137 1137

Model 1419 1390 1205 912 1006 948 1007

Difference -295 -173 8 -33 -114 -188 -130

% Difference -17% -11% 1% -4% -10% -17% -11%

RSI01 LDSJ31 OUT

Observed 462 503 495 628 1296 1404 1111

Model 503 685 662 841 1480 1456 1357

Difference 41 182 167 213 184 52 246

% Difference 9% 36% 34% 34% 14% 4% 22%

RSI01 LDSJ32 OUT

Observed 221 368 366 587 1100 1191 956

Model 240 417 403 587 1149 1201 1018

Difference 18 50 37 -1 48 10 63

% Difference 8% 13% 10% 0% 4% 1% 7%

RSI01 LDSJ33 OUT

Observed 167 374 280 270 340 349 335

Model 173 402 209 217 272 319 250

Difference 6 28 -71 -53 -68 -30 -85

% Difference 3% 7% -25% -20% -20% -9% -25%

RSI01 LDSJ34 OUT

Observed 361 524 492 531 729 918 796

Model 351 468 463 556 816 875 789

Difference -10 -57 -29 26 88 -43 -7

% Difference -3% -11% -6% 5% 12% -5% -1%

RSI01 LDSJ35C

ALI OUT

Observed 65 138 160 179 373 430 326

Model 100 155 149 194 276 296 203

Difference 35 17 -11 15 -96 -134 -123

% Difference 53% 12% -7% 8% -26% -31% -38%

RSI01 LDSJ36 OUT

Observed 61 86 81 100 245 302 143

Model 112 148 147 252 282 342 265

Difference 51 62 66 152 38 40 122



Transportation

% Difference 83% 72% 82% 152% 15% 13% 85%

RSI01 Proxy345 OUT

Observed 240 321 319 409 480 476 430

Model 220 234 249 473 756 792 632

Difference -20 -87 -70 64 276 316 202

% Difference -8% -27% -22% 16% 57% 66% 47%

RSI01 Proxy346 OUT

Observed 887 1033 957 1018 1744 1628 1482

Model 891 1010 910 1079 1591 1592 1433

Difference 4 -23 -47 61 -153 -36 -49

% Difference 0% -2% -5% 6% -9% -2% -3%

VAL14 I201 IN

Observed 849 900 700 571 640 582 556

Model 925 1003 743 537 559 497 480

Difference 76 103 43 -34 -81 -86 -76

% Difference 9% 11% 6% -6% -13% -15% -14%

VAL14 I411 IN

Observed 1648 1514 1203 1035 1149 1103 1108

Model 1373 1357 1200 1000 1117 1053 1050

Difference -275 -157 -3 -35 -32 -51 -57

% Difference -17% -10% 0% -3% -3% -5% -5%

VAL14 I412 IN

Observed 527 536 434 349 401 415 368

Model 519 363 346 246 225 171 224

Difference -8 -173 -88 -103 -176 -243 -144

% Difference -1% -32% -20% -29% -44% -59% -39%

VAL14 I413 IN

Observed 134 188 148 124 127 113 117

Model 265 324 281 226 274 265 210

Difference 131 137 133 103 146 152 93

% Difference 98% 73% 90% 83% 115% 134% 79%

VAL14 I414 IN

Observed 172 354 162 122 167 160 127

Model 95 277 112 132 157 161 131

Difference -77 -76 -50 11 -9 1 4

% Difference -45% -22% -31% 9% -6% 1% 3%

VAL14 I201 OUT

Observed 420 573 538 550 803 946 721

Model 347 449 454 565 921 987 793

Difference -73 -124 -85 16 118 41 72

% Difference -17% -22% -16% 3% 15% 4% 10%

VAL14 I411 OUT

Observed 977 1080 1015 1077 1715 1542 1400

Model 976 1082 970 1043 1472 1436 1267

Difference -1 2 -46 -34 -243 -106 -133



Transportation

% Difference 0% 0% -5% -3% -14% -7% -9%

VAL14 I412 OUT

Observed 382 463 407 435 665 623 522

Model 288 350 343 493 753 824 599

Difference -94 -113 -65 58 88 201 77

% Difference -25% -24% -16% 13% 13% 32% 15%

VAL14 I413 OUT

Observed 50 91 95 125 297 418 197

Model 197 508 313 335 349 367 292

Difference 148 417 218 209 53 -51 95

% Difference 297% 459% 229% 167% 18% -12% 48%

VAL14 I414 OUT

Observed 60 96 120 133 302 363 206

Model 100 155 149 194 276 296 203

Difference 40 59 30 61 -26 -67 -3

% Difference 68% 61% 25% 46% -9% -18% -1%

RSI03 LDSJ10 IN

Observed 93 109 70 73 49 46 38

Model 240 227 92 134 58 54 59

Difference 147 117 22 61 9 8 21

% Difference 158% 107% 31% 83% 19% 16% 54%

RSI03 LDSJ12E

LLR IN

Observed 956 902 755 640 633 725 728

Model 827 944 725 587 613 709 695

Difference -130 42 -30 -53 -20 -17 -32

% Difference -14% 5% -4% -8% -3% -2% -4%

RSI03 LDSJ5 IN

Observed 245 379 173 146 198 211 162

Model 311 556 250 267 411 388 296

Difference 66 178 77 121 213 177 134

% Difference 27% 47% 45% 83% 107% 84% 82%

RSI03 LDSJ6 IN

Observed 377 565 440 443 467 434 369

Model 308 427 334 306 322 257 249

Difference -69 -137 -105 -137 -145 -176 -120

% Difference -18% -24% -24% -31% -31% -41% -33%

RSI03 LDSJ7EL

LR IN

Observed 1154 1221 1014 751 875 946 678

Model 1180 1093 973 671 847 834 597

Difference 26 -129 -41 -81 -27 -112 -80

% Difference 2% -11% -4% -11% -3% -12% -12%

RSI03 Proxy26 IN

Observed 215 264 157 116 165 154 78

Model 69 122 161 153 233 224 116

Difference -146 -142 4 37 68 70 38



Transportation

% Difference -68% -54% 3% 32% 41% 46% 48%

RSI03 Proxy82 IN

Observed 4346 3565 2781 1892 2671 2938 2473

Model 4414 3908 2950 2024 2655 2969 2492

Difference 67 344 169 132 -16 31 19

% Difference 2% 10% 6% 7% -1% 1% 1%

RSI03 LDSJ10 OUT

Observed 59 93 79 104 115 127 58

Model 212 268 195 241 319 377 274

Difference 153 175 116 138 203 251 216

% Difference 258% 190% 147% 133% 177% 198% 376%

RSI03 LDSJ12E

LLR OUT

Observed 407 594 499 657 1114 1174 900

Model 258 409 384 519 957 973 690

Difference -149 -185 -115 -139 -157 -201 -210

% Difference -37% -31% -23% -21% -14% -17% -23%

RSI03 LDSJ5 OUT

Observed 105 151 112 148 227 251 154

Model 133 175 177 216 283 418 169

Difference 28 25 65 68 56 167 15

% Difference 26% 16% 58% 46% 25% 67% 10%

RSI03 LDSJ6 OUT

Observed 148 203 296 363 508 605 428

Model 122 177 234 286 460 482 423

Difference -26 -25 -62 -77 -48 -124 -6

% Difference -17% -13% -21% -21% -9% -20% -1%

RSI03 LDSJ7EL

LR OUT

Observed 573 649 492 656 939 900 677

Model 659 677 540 648 953 895 734

Difference 87 28 48 -8 15 -5 57

% Difference 15% 4% 10% -1% 2% -1% 8%

RSI03 Proxy26 OUT

Observed 214 234 131 142 239 238 129

Model 125 208 92 105 213 222 126

Difference -89 -26 -39 -37 -26 -16 -3

% Difference -41% -11% -30% -26% -11% -7% -2%

RSI03 Proxy82 OUT

Observed 2793 2291 1563 2188 4823 4853 3286

Model 2819 2337 1740 2210 4982 5103 3346

Difference 27 46 177 22 158 250 59

% Difference 1% 2% 11% 1% 3% 5% 2%

RSI12 LDS18 IN

Observed 910 1023 744 725 848 935 823

Model 1038 974 888 1007 1146 1248 1095

Difference 129 -48 144 282 297 312 272



Transportation

% Difference 14% -5% 19% 39% 35% 33% 33%

RSI12 LDS19 IN

Observed 767 650 649 510 602 656 600

Model 686 700 509 231 371 400 347

Difference -82 50 -140 -279 -231 -256 -253

% Difference -11% 8% -22% -55% -38% -39% -42%

RSI12 LDS20 IN

Observed 892 751 465 243 157 117 204

Model 1022 882 560 300 146 138 196

Difference 129 131 95 57 -11 21 -8

% Difference 15% 17% 20% 23% -7% 18% -4%

RSI12 LDS21 IN

Observed 928 773 604 300 276 277 271

Model 995 773 523 270 314 278 298

Difference 67 0 -81 -30 38 1 27

% Difference 7% 0% -13% -10% 14% 0% 10%

RSI12 LDS22 IN

Observed 535 736 241 170 209 241 200

Model 367 371 151 144 239 276 219

Difference -168 -365 -90 -26 30 35 20

% Difference -31% -50% -38% -15% 14% 15% 10%

RSI12 LDSA1 IN

Observed 239 298 136 201 453 627 365

Model 384 420 228 229 344 395 346

Difference 145 122 92 28 -110 -232 -19

% Difference 60% 41% 67% 14% -24% -37% -5%

RSI12 Proxy318 IN

Observed 4632 3141 2674 1829 2302 2854 2364

Model 4413 3907 2798 1862 2351 2746 2298

Difference -218 766 124 33 48 -107 -66

% Difference -5% 24% 5% 2% 2% -4% -3%

RSI12 LDS18 OUT

Observed 800 805 717 686 719 814 800

Model 1120 1083 949 1041 1237 1265 1359

Difference 320 278 232 356 518 452 559

% Difference 40% 35% 32% 52% 72% 56% 70%

RSI12 LDS19 OUT

Observed 372 476 395 519 760 720 718

Model 239 214 169 169 645 618 208

Difference -134 -262 -227 -350 -115 -102 -510

% Difference -36% -55% -57% -67% -15% -14% -71%

RSI12 LDS20 OUT

Observed 146 154 174 308 414 165 340

Model 192 192 207 352 328 247 450

Difference 47 39 33 44 -86 81 110

% Difference 32% 25% 19% 14% -21% 49% 32%



Transportation

RSI12 LDS21 OUT

Observed 268 277 257 349 861 797 546

Model 232 239 235 340 681 618 495

Difference -36 -38 -22 -9 -180 -179 -51

% Difference -13% -14% -9% -3% -21% -22% -9%

RSI12 LDS22 OUT

Observed 120 129 115 166 255 258 204

Model 161 172 115 119 222 221 164

Difference 41 43 0 -47 -33 -37 -40

% Difference 34% 33% 0% -28% -13% -14% -20%

RSI12 LDSA1 OUT

Observed 386 413 254 180 247 287 287

Model 349 375 256 226 287 352 331

Difference -37 -38 2 46 40 65 43

% Difference -10% -9% 1% 26% 16% 23% 15%

RSI12 Proxy318 OUT

Observed 2452 2033 1545 1925 4901 4157 2839

Model 2491 2025 1544 1945 4809 4679 2903

Difference 39 -8 -1 20 -92 522 64

% Difference 2% 0% 0% 1% -2% 13% 2%

RSI08 LDSB1 IN

Observed 1421 1636 1320 1071 1310 1542 1522

Model 1403 1532 1319 1074 1350 1456 1380

Difference -18 -104 -1 4 40 -87 -142

% Difference -1% -6% 0% 0% 3% -6% -9%

RSI08 LDSB1 OUT

Observed 1328 1438 1269 1110 1273 1380 1334

Model 1355 1400 1210 1116 1335 1414 1372

Difference 28 -38 -59 6 61 34 38

% Difference 2% -3% -5% 1% 5% 2% 3%

RSI08 LDSB2 IN

Observed 914 1013 713 558 713 810 859

Model 918 1012 709 555 710 807 875

Difference 4 -1 -4 -3 -2 -3 16

% Difference 0% 0% -1% -1% 0% 0% 2%

RSI08 LDSB2 OUT

Observed 576 649 544 656 1012 1071 897

Model 599 674 555 656 1014 1094 895

Difference 24 26 11 0 2 24 -2

% Difference 4% 4% 2% 0% 0% 2% 0%

RSI08 LDSB3 IN

Observed 375 507 329 323 478 500 463

Model 384 469 328 364 504 528 508

Difference 9 -39 0 41 25 28 46

% Difference 2% -8% 0% 13% 5% 6% 10%



Transportation

RSI08 LDSB3 OUT

Observed 391 491 363 436 826 931 660

Model 435 451 339 571 957 1091 789

Difference 43 -39 -24 135 131 160 128

% Difference 11% -8% -7% 31% 16% 17% 19%

Sites highlighted are located on the NGT corridor.

Documents

New Generation Transport - Model Validation Report · 2.2 The NGT Scheme The NGT scheme is a modern trolleybus service operating north / south through the urban area of Leeds. It