SATURN and DIADEMPractical Experience

Toni Dichev

31st Oct 2008

What is DIADEM?

DIADEM Approach

Model Requirements

Realism Tests / Convergence Criteria

Issues & Solutions

Practical Example

Summary: Lessons Learned & Conclusions

Overview

Variable Demand Modelling Advice (VADMA) – WebTAG Guidance

Any change to transport conditions will, in principle, cause a change in demand. The purpose of variable demand modelling is to predict and quantify these changes

Trip Frequency

Trip Distribution

Mode Choice

Time of Day Choice

DIADEM (Dynamic Integrated Assignment, and Demand Modelling) software - allows you to implement variable demand modelling as recommended by WebTAG

DIADEM and Variable Demand

Specify Demand Model Structure

Select Model Parameters and Realism Test

Prepare Forecast Networks and Reference Trip Matrices for Demand Model

Assignments

Run DIADEM for different Time Periods

Identify Best Iteration &

Reassign networks with best matrices

Demand Modelling Using DIADEM

Model needs to have appropriate split by journey purpose

Which Responses to Include?

Circumstances and Policy interests of assessment;Availability of Data;

Dft Guidance what responses to consider

DIADEM Demand Model Structure

Realism Tests - The Essentials

Base Year Validated Network

Base Year Revised Network

Demand Segments

Base Year Assigned Model

DIADEM RUN

Calculate Elasticities

Fuel Price

Journey Time

Ask Questions

Realistic?

Reasonable?

Experience from Past Studies Judgement (subjective) Take advise from the expert Contact the supplier

Select Parameters

Select/Tweak Sensitivity (Lambda) Parameters

Yes

Realistic? – Is it in accordance with general experience?

Reasonable?- a subjective judgement with which you can “convince” others

No

Base Validated Matrix

Problems

Running times – can be extensive

High number of computers (one for each time period/year/scenario)

Difficult to reach convergence specifically for future years – unacceptable Gap values (0.2% recommended - new Guidance 0.15%)

Mode Choice modelling (can’t cope with the nested Mode Choice, doesn’t pass the changes in speeds etc. to PT)

Help with SATURN Convergence

Importance of well converged SATURN assignment (Delta <0.1%)

MASL,NITA,NITA_M – convergence parameters

MONACO = T – reduces problems with blocking back at single lane junctions (right turners)

NUC => 50 – improves accuracy (hence instability) of signals

Latest versions of SATURN help greatly in achieving convergence

Help with DIADEM Convergence

Change the assignment method

Increase the maximum number of iterations

Decrease the stopping values for the gap values

Decrease the value of the ‘maximum flow change’ parameter

Improve your assignment convergence

Help with DIADEM run time

Skimming minimum costs within DIADEM (only if SATURN assignment convergence < 0.1%) SAVEIT = F

Assignment Method Algorithm 1 tends to converge quicker

Use of the best (high spec) machines

NITA = 10 MASL = 100 AUTOK = T KOMBI = 0NITA_M = 5 DIDDLE = T

DIADEM – Future Year Assignments

The same convergence criteria is required – can be difficult to achieve

The same structure of the files as for the Realism Test

Can significantly increased the running times due to assignment and DIADEM convergence

Best matrices are reassigned to produce the final assignment

Example – Strategic Motorway LinkSATURN assignment

Large model with assignment times > 1.5 hours

Six journey purposes

AM, IP and PM models

Three modelled years and 4 scenarios

DIADEM – distribution and frequency responses only considered (no mode choice), WebTAG guidance used for the Lamda Values, Method of Successive Averages

Practical ExperienceIssue Solution Positive Effect Negative Effect

SATURN assignment Delta > 0.15%

Increased MASL/NITA etc.

Delta < 0.04% Potential to use minimum costs Improved GAP in DIADEM

Significantly increased the running time of the SATURN assignment

DIADEM GAP > 0.2 As above plus increased the number of iterations and change of the DIADEM algorithm

Reduce DIADEM GAP < 0.2

Significantly increased the running time of the DIADEM

Lamda Values WebTAG recommended not providing sensible results

Decrease the Lamda Values

Improve the DIADEM convergence and the elasticises

Not within WebTAG guidance, however excepted by the client

Issues with elasticity (average < -0.3)

Indentify local area conditions (make up of the local journey purpose split)

Able to demonstrate sensible elasticises for the model area

Not within WebTAG guidance, however excepted by the client

Run times too high Higher spec computers and Cordon the model

Reduce run times Costs

Summary

Lessons Learned

• Aware of the guidance• How to select sensitivity parameters• Convergence Criteria• Running Times

SATURN and DIADEMPractical Experience

Toni Dichev

31st Oct 2008