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