24, March 2014

24, March 2014

Queue Length Estimation Based on Point Traffic Detector Data and Automatic Vehicle Identification Data

Contents

Detector Data

AVI data

Case Study 1

Case Study 2

Methods

FIU/UCF Joint Project Joint project between FIU and UCF

Mohammed Hadi, Ph.D., P.E. (PI) Haitham Al-Deek, Ph.D., P.E. (UCF PI) Omer Tatari, Ph.D (Co-PI) Yan Xiao (Co-PI) Somaye Fakharian (FIU Ph.D. student) Frank A. Consoli, P.E. (UCF Ph.D. Student) John Rogers, P.E. (UCF Ph.D. Student)

Progress Diagram

Phase 1 Phase 2 Phase 3

Turnpike , 1.8 Mile4 detectorsAll methods

Real World Data

SR 826(0.947, Detectors,0311 mile

Simulation (CORSIM)Real worldComparison of

simulation and real world

Estimation of Density .

Detector Data

Speed Based Base on speed, the link is 1: Fully congested, if the speed based on both detectors< 40

M/Hr 2: Uncongested: if the speed based on both detectors >= 40 3: Partially Congested: If the speed based on one detector < 40 Volume Based

Arrival vehicle > Departure Vehicle

AVI Data

Speed Based 1: Average Speed for the segment < 40 is totally

congested 2: Average Speed>= 40 is totally Uncongested

Combination of Detector and AVI Data

Speed Based 1: For fully congested(based on Detector), average

speed based on AVI 2: For totally uncongested (based on Detector):

average speed based on AVI 3: Partially Congested: base on relationship sped and

travel time, the partial queue is estimated.

Combination of Detector and AVI Data

Travel Time Based 1: For fully congested(based on AVI), average travel

time is calculated 2: For totally uncongested (based on AVI): average

travel time is calculated 3: Partially Congested: the linear regression for each

travel time between fully congested and fully uncongested.

Methods For Queue Length Estimation

AVI (Average Speed)

Combination of AVI and Detector(Travel Time and Speed)

Detector (Average Speed and Volume)

Queue Length Estimation

Case Study 1: (Turnpike)

Table (Turnpike)Time Tag Detector TT based Speed based6:00:00 0 0 0 06:05:00 0 0 0 06:10:00 0 0 0 06:15:00 0 0 0 06:20:00 0 0 0 06:25:00 0 0 0 06:30:00 0 0 0 06:35:00 0 0 0 06:40:00 0 0 0 06:45:00 0 0 0 06:50:00 1.8 0 0 06:55:00 1.8 0 0 07:00:00 1.8 0.9 0.313948632 0.1462956927:05:00 1.8 0.9 0.507030324 0.3122237667:10:00 1.8 0.9 0.876124726 0.5423039697:15:00 1.8 0.9 1.110667473 0.9821246147:20:00 1.8 0.9 1.407908931 1.2616106817:25:00 1.8 1.8 1.8 1.87:30:00 1.8 1.8 1.8 1.87:35:00 1.8 1.8 1.8 1.87:40:00 1.8 1.8 1.8 1.87:45:00 1.8 1.8 1.8 1.87:50:00 1.8 0.9 1.458528331 0.912547:55:00 1.8 0.9 1.103458913 0.83528:00:00 1.8 0.9 1.141650021 0.6713558:05:00 0 0.9 0.719855752 0.698128:10:00 0 0.9 0.520868962 0.562438:15:00 0 0.9 0.470737984 0.5021338:20:00 0 0.9 0.373952654 0.4990572538:25:00 0 0.9 0.314383157 0.383725828:30:00 0 0.9 0.060792632 0.3127415558:35:00 0 0.9 0.041185117 0.0105577568:40:00 0 0 0 08:45:00 0 0 0 08:50:00 0 0 0 08:55:00 0 0 0 09:00:00 0 0 0 09:05:00 0 0 0 09:10:00 0 0 0 09:15:00 0 0 0 09:20:00 0 0 0 09:25:00 0 0 0 09:30:00 0 0 0 09:35:00 0 0 0 09:40:00 0 0 0 09:45:00 0 0 0 09:50:00 0 0 0 09:55:00 0 0 0 010:00:00 0 0 0 010:05:00 0 0 0 010:10:00 0 0 0 010:15:00 0 0 0 010:20:00 0 0 0 010:25:00 0 0 0 010:30:00 0 0 0 010:35:00 0 0 0 010:40:00 0 0 0 010:45:00 0 0 0 010:50:00 0 0 0 010:55:00 0 0 0 011:00:00 0 0 0 011:05:00 0 0 0 011:10:00 0 0 0 011:15:00 0 0 0 011:20:00 0 0 0 011:25:00 0 0 0 011:30:00 0 0 0 011:35:00 0 0 0 011:40:00 0 0 0 011:45:00 0 0 0 011:50:00 0 0 0 011:55:00 0 0 0 012:00:00 0 0 0 012:05:00 0 0 0 012:10:00 0 0 0 012:15:00 0 0 0 012:20:00 0 0 0 012:25:00 0 0 0 012:30:00 0 0 0 012:35:00 0 0 0 012:40:00 0 0 0 012:45:00 0 0 0 012:50:00 0 0 0 012:55:00 0 0 0 013:00:00 0 0 0 013:05:00 0 0 0 013:10:00 0 0 0 013:15:00 0 0 0 013:20:00 0 0 0 013:25:00 0 0 0 013:30:00 0 0 0 013:35:00 0 0 0 013:40:00 0 0 0 013:45:00 0 0 0 013:50:00 0 0 0 013:55:00 0 0 0 014:00:00 0 0 0 014:05:00 0 0 0 014:10:00 0 0 0 014:15:00 0 0 0 014:20:00 0 0 0 014:25:00 0 0 0 014:30:00 0 0 0 014:35:00 0 0 0 014:40:00 0 0 0 014:45:00 0 0 0 014:50:00 0 0 0 014:55:00 0 0 0 015:00:00 0 0 0 015:05:00 0 0 0 015:10:00 0 0 0 015:15:00 0 0 0 015:20:00 0 0 0 015:25:00 0 0 0 015:30:00 0 0 0 015:35:00 0 0 0 015:40:00 0 0 0 015:45:00 0 0 0 015:50:00 0 0 0 015:55:00 0 0 0 016:00:00 0 0 0 016:05:00 0 0 0 016:10:00 0 0 0 016:15:00 0 0 0 016:20:00 0 0 0 016:25:00 0 0 0 016:30:00 0 0 0 016:35:00 0 0 0 016:40:00 0 0 0 016:45:00 0 0 0 016:50:00 0 0 0 016:55:00 0 0 0 017:00:00 0 0 0 017:05:00 0 0 0 0

Diagram (Cumulative Volume)

Diagram (Volume)

Case Study 2: (SR 826- Simulation CORSIM)

Based on simulation Sensitivity multiplier by 200% Two link are congested Link 1: o.48 mile Link 2: 0.46 Detector 1: 0.387 mile from upstream Detector 2: 0.23

Case Study 2: (SR 826- Simulation CORSIM)

Time Queue Length (speed 30) Queue Length (speed 35) Queue Length (speed 40)10:00:00 0.22219697 0.22219697 0.30837121210:05:00 0.22219697 0.22219697 0.30837121210:10:00 0.22219697 0.22219697 0.30837121210:15:00 0.22219697 0.22219697 0.30837121210:20:00 0.214393939 0.231818182 0.30837121210:25:00 0 0 010:30:00 0 0 010:35:00 0 0 010:40:00 0 0 010:45:00 0 0 010:50:00 0 0 010:55:00 0 0 011:00:00 0 0 011:05:00 0 0 011:10:00 0 0 011:15:00 0 0 011:20:00 0 0 011:25:00 0 0 011:30:00 0 0 011:35:00 0 0 011:40:00 0 0 011:45:00 0 0 011:50:00 0 0 011:55:00 0 0 012:00:00 0 0 012:05:00 0 0 012:10:00 0 0 012:15:00 0 0 012:20:00 0 0 012:25:00 0 0 012:30:00 0 0 012:35:00 0 0 012:40:00 0 0 012:45:00 0 0 012:50:00 0 0 012:55:00 0 0 013:00:00 0 0 013:05:00 0 0 013:10:00 0 0 013:15:00 0 0 013:20:00 0 0 013:25:00 0 0 013:30:00 0 0 013:35:00 0 0 013:40:00 0 0 013:45:00 0 0 0

Case Study 2: (SR 826- Simulation CORSIM)

Case Study 2: (SR 826- Real world

Based on detector data Based on AVI data, matching each individual

vehicle from link 1 to link 2 All methods are used for Turnpike(Detector, AVI,

Combination of detector and AVI) Cumulative volume (Based on detector data)

Case Study 2: (SR 826- Real World)

Diagram (Cumulative Volume)

Case Study 2: (SR 826- Comparison of Simulation and Real World)

Density Estimation

Question?

AVI Detector

Combination