Sensor technologies and data requirements for ITS

Beginning with descriptions of parameters that characterize the flow of vehicles on freeways, arterial roads and feeder routes, this hands-on manual examines intrusive and non-intrusive traffic sensors and associated technologies that measure traffic flow and assist in the management of congestion. It contains information about sensors that provide wider coverage areas and a larger variety of traffic flow parameters than the more conventional inductive loops. The operating characteristics of these measuring devices is illuminated through detailed discussions of traffic-responsive arterial signal control, freeway incident detection, ramp metering, electronic toll and traffic management, commercial vehicle operations, advanced traveller information systems, and sensor installation and maintenance issues.

Author Notes

Lawrence A. Klein, Ph.D. received his B.E.E. from the City College of New York, his M.S. in Electrical Engineering from the University of Rochester (NY), and his Ph.D. in Electrical Engineering from New York University.

Dr. Klein is currently a private consultant and was commended by the U.S. Federal Highway Administration for his performance while with the Hughes Aircraft Company as principal investigator on the Detection Technology for Intelligent Vehicle Highway Systems program. He is a member of the Freeway Operations Committee of TRB, member of ASTM E17 Group V Â ITS, senior member of the IEEE, was co-chair of the SPIE Collision Avoidance and Automated Traffic Management Sensors Conference, and has published 3 other books and over 50 technical papers.

050

Preface	p. xix
1 Sensors in Modern Traffic Management Systems	p. 1
1.1 Prevalence of Recurring Congestion	p. 5
1.2 Impact of Traffic Management Strategies on Congestion	p. 8
1.3 Impact of Congestion on Accident Rates	p. 14
1.4 Impact of Congestion Mitigation on Fuel Consumption and Pollution Emissions	p. 17
1.5 Optimizing the Existing Transportation Network Through Information Gathering and Dissemination	p. 23
1.6 Sensors as Part of an Intelligent Transportation Traffic Management System	p. 25
1.7 Evolution of Sensor Requirements	p. 28
1.8 Chapter Synopses	p. 32
References	p. 34
2 Traffic Flow Characterization	p. 37
2.1 Traffic Parameters For Uninterrupted Flow	p. 37
2.2 Traffic Parameters for Interrupted Flow	p. 44
2.3 Traffic Parameters as Measures of Effectiveness	p. 45
2.4 Traffic Flow Parameter Definitions	p. 45
2.5 Measures of Data Uniformity	p. 74
2.6 Statistical Measures of Data	p. 77
2.7 Summary	p. 88
Exercises	p. 89
References	p. 90
3 Applications of Sensor Data to Traffic Management	p. 93
3.1 Traffic Signal Timing Parameters	p. 94
3.2 Local Isolated Intersection Signal Control	p. 94
3.3 Interconnected Intersection Signal Control	p. 98
3.4 Interconnected Intersection Signal Control Using Online-Generated, Traffic-Adaptive Timing Plans	p. 113
3.5 Freeway Incident Detection	p. 133
3.6 Freeway Metering	p. 142
3.7 Coordinated Operation of Freeways and Surface Streets	p. 156
3.8 Enhanced Information Dissemination to Travelers	p. 157
3.9 Traffic Data Collection	p. 159
3.10 Using Sensor Data to Characterize, Detect, and Analyze Sensor Failure Modes	p. 169
3.11 Detection of Priority Vehicles	p. 181
3.12 Overheight Sensors	p. 185
3.13 Weather Sensors	p. 186
3.14 Vehicle-Mounted Sensors that Enhance Safe Operation	p. 186
3.15 Specifications for Inductive Loop Detectors	p. 193
3.16 Traffic Parameter Accuracy Requirements for Current Applications	p. 193
3.17 Summary	p. 196
Exercises	p. 197
References	p. 200
4 Data Requirements for Future Traffic Management Applications	p. 209
4.1 Sensor Data Requirements for Evolving Applications	p. 209
4.2 Detection Technology for IVHS Program	p. 217
4.3 Traffic Surveillance and Detection Technology Development Program	p. 230
4.4 Summary	p. 236
References	p. 237
5 Traffic Flow Sensor Technologies	p. 239
5.1 Video Image Processor	p. 243
5.2 Microwave Radar	p. 262
5.3 Infrared Sensors	p. 269
5.4 Ultrasonic Sensors	p. 276
5.5 Passive Acoustic Array Sensors	p. 279
5.6 Inductive Loop Detectors	p. 281
5.7 Magnetic Sensors	p. 288
5.8 Sensor Combinations	p. 295
5.9 Relative Cost of Sensors	p. 296
5.10 Traffic Flow Data from Automatic Vehicle Identification Transponders	p. 299
5.11 Traffic Flow Data from Cellular Telephones	p. 304
5.12 Sensor Technology Comparison	p. 305
5.13 Sensor Specification Summaries	p. 311
5.14 Summary	p. 311
Exercises	p. 312
References	p. 314
6 Overhead Sensor Installation Along a Highway	p. 319
6.1 Initial Sensor Evaluations	p. 320
6.2 Video Image Processors	p. 321
6.3 Microwave Radar Sensors	p. 335
6.4 Laser Radar Sensors	p. 340
6.5 Passive Infrared Sensors	p. 343
6.6 Ultrasonic Sensors	p. 344
6.7 Passive Acoustic Array Sensors	p. 346
6.8 Sensor Combinations	p. 348
6.9 Summary	p. 349
References	p. 349
7 Transponders and Standards for Dedicated Short-Range Communications	p. 351
7.1 Transponder Types	p. 352
7.2 Open Systems Interconnection Communications Model	p. 354
7.3 DSRC Standards	p. 357
7.4 Summary	p. 392
Exercises	p. 395
References	p. 395
8 Data Fusion at the Traffic Management Center	p. 399
8.1 Bayesian Inference	p. 400
8.2 Dempster-Shafer Inference	p. 411
8.3 Artificial Neural Networks	p. 424
8.4 Voting Fusion	p. 440
8.5 Fuzzy Logic	p. 465
8.6 Knowledge-Based Expert Systems	p. 485
8.7 Summary	p. 494
Exercises	p. 495
References	p. 497
9 Sensor Plan and Specification Requirements	p. 501
9.1 Planning for Sensor Use	p. 502
9.2 Sensor Specification Issues	p. 502
9.3 Summary	p. 510
List of Symbols, Abbreviations, and Acronyms	p. 511
About the Author	p. 525
Index	p. 527
Appendix A Elements of Selected United States and Canadian Traffic Management Systems	p. 1
Appendix B Freeway Incident Detection Algorithms	p. 1
B.1 Detection Rate and False Alarm Rate	p. 1
B.2 California Algorithms	p. 2
B.3 McMaster Algorithms	p. 6
B.4 Other Speed-Based Incident Detection Algorithms	p. 9
B.5 Incident Detection in Japan	p. 9
B.6 Incident Detection in Europe	p. 10
B.7 Incident Detection Algorithm Performance Comparison	p. 11
B.8 Summary	p. 15
References	p. 16
Appendix C Energy Use and Emissions by Transportation Mode	p. 1
Appendix D Inductive Loop Detector Specifications	p. 1
References	p. 6
Appendix E Deterministic and Random Components of Traffic Data	p. 1
References	p. 4
Appendix F Axel Counting and Weigh-in-Motion Sensors	p. 1
F.1 Pneumatic Road Tube	p. 1
F.2 Fiberoptic Sensors	p. 3
F.3 Piezoelectric Sensors	p. 4
F.4 Weigh-in-Motion Systems	p. 7
F.5 Weigh-in-Motion System Costs	p. 15
F.6 Summary	p. 18
References	p. 18
Appendix G Transmission Rate Requirements for Selected Traffic Management Applications	p. 1
References	p. 5
Appendix H Specifications of Representative Sensor Models	p. 1
Appendix I Sensor Manufacturers and Vendors	p. 1
Appendix J Data Fusion Algorithms and Architectures	p. 1
J.1 Definition of Data Fusion	p. 2
J.2 Level 1 Processing	p. 4
J.3 Levels 2, 3, and 4 Processing	p. 17
J.4 Definition of an Architecture	p. 19
J.5 Data Fusion Processes	p. 19
J.6 Data Fusion Architectures	p. 20
J.7 Sensor Footprint Registration and Size Considerations	p. 27
J.8 Summary	p. 28
Exercises	p. 30
References	p. 30
Appendix K Freeway and Multilane Highway Capacity for Other Than Base Conditions	p. 1
K.1 Free-Flow Speed Estimate	p. 1
K.2 Equivalent Passenger Car Flow-Rate Estimate	p. 5
K.3 Summary	p. 7
Reference	p. 9
Appendix L Answers to Chapter Exercises	p. 1

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