Incident management in intelligent transportation systems

Effective incident detection, response, clearance and recovery from vehicle disablements and accidents can save commuter hours, fuel and money. This book describes an integrated traffic incident management system and related software designed to facilitate inter-agency communication and help transportation officials co-ordinate response activities so that traffic flow is restored to normal as soon as possible.

Author Notes

Kaan Ozbay earned his Ph.D. and M.S. in civil engineering at Virginia Tech University.

Dr. Ozbay is an assistant professor at Rutgers University. He is a recipient of the Eno Fellowship Award, the author of 25 research proposals, and the principal and co-principal investigator, and project manager of more than 10 ITS projects including the "Wide Area Incident Management " project sponsored by FHWA , and VDOT.

050

Preface	p. xiii
1 Introduction	p. 1
1.1 Highway Congestion	p. 1
1.2 Impact of Incidents on Highway Congestion	p. 4
1.3 Incident Types and Impacts	p. 6
1.4 Incident Management	p. 9
1.5 Agencies Involved in Incident Management	p. 12
1.6 Incident Management Process	p. 14
1.7 Problems in Incident Management	p. 15
2 Review of Incident Management Systems	p. 21
2.1 Introduction	p. 21
2.2 Proposed Implementation Frameworks for Incident Management Support Systems	p. 22
2.2.1 System Requirements and Characteristics	p. 23
2.2.2 Blackboard Architecture	p. 28
2.3 Incident Management Frameworks Based on Expert Systems	p. 31
2.4 Incident Management Systems Based on Geographical Information Systems	p. 33
2.5 Summary	p. 36
Review Questions	p. 37
3 Wide-Area Incident Management Support System Software	p. 41
3.1 Design Considerations	p. 41
3.1.1 Overall Concept	p. 42
3.1.2 Framework for Integration	p. 43
3.2 Application Design	p. 45
3.2.1 Decision Support Modules	p. 46
3.2.2 Duration Estimation Module	p. 47
3.2.3 Delay Calculation Module	p. 48
3.2.4 Response Module	p. 49
3.3 Software Implementation	p. 50
3.3.1 Software Implementation Architecture	p. 52
3.3.2 Application Development	p. 54
3.3.3 Data-level Integration	p. 56
3.3.4 Command-level Integration	p. 56
3.4 Summary	p. 57
Review Questions	p. 58
4 Incident Detection	p. 61
4.1 Introduction	p. 61
4.2 What Is Incident Detection?	p. 62
4.2.1 Traffic Surveillance and Data	p. 62
4.2.2 Analysis of Traffic Data	p. 62
4.2.3 Importance of Incident Detection Time	p. 63
4.3 Effect of Incident Detection Time on Overall Incident Duration	p. 64
4.4 Incident Detection Issues	p. 66
4.4.1 Surveillance Issues	p. 66
4.4.2 Algorithmic Issues	p. 69
4.5 Verification Issues: Evaluation of Incident Detection Systems	p. 74
4.6 Operational Field Tests	p. 76
4.6.1 Transcom Transmit Project	p. 76
4.6.2 I-880 Field Experiment: Incident Detection Using Cellular Phones	p. 77
4.7 Summary	p. 78
Review Questions	p. 79
5 Incident Duration and Delay Prediction	p. 83
5.1 Incident Duration Estimation Models	p. 84
5.2 Northern Virginia Case Study: Methodological Structure	p. 91
5.2.1 Structure and Design of Survey Forms and Data Collection	p. 92
5.2.2 Analysis of New Incident Data	p. 98
5.2.3 Detailed Analysis	p. 107
5.2.4 Summary of Detailed Data Analysis	p. 112
5.2.5 Development of Incident Clearance Time Prediction/Decision Trees	p. 112
5.2.6 Validation of Prediction/Decision Trees	p. 117
5.2.7 Distribution Properties of Incident Duration Data Collected for Case Study	p. 121
5.2.8 Comparison of Our Results With Previous Work	p. 123
5.3 Incident Delay Prediction	p. 125
5.3.1 Deterministic Queuing Diagram	p. 125
5.3.2 Other Methods to Determine Incident Delays	p. 127
5.4 Summary	p. 128
Review Questions	p. 129
6 Incident Response	p. 133
6.1 The Incident Response Problem	p. 133
6.1.1 Tools	p. 135
6.1.2 Research Needs for the Development of Incident Response Support Tools	p. 136
6.2 Existing Incident Response Systems	p. 137
6.2.1 Orange County, California: Caltrans	p. 137
6.2.2 I-95 Corridor Coalition	p. 140
6.2.3 Northern Virginia	p. 144
6.2.4 Research on Incident Response	p. 145
6.3 Formulation of a Response Plan	p. 146
6.3.1 Incident Characterization	p. 147
6.3.2 Service Identification	p. 149
6.3.3 Agency Notification	p. 150
6.3.4 Clearance Process	p. 151
6.3.5 Computer Implementation of the Conceptual Computer-Based Response Plan	p. 153
6.4 Case Study	p. 154
6.4.1 Study Area and Response Statistics	p. 154
6.4.2 Statistical Analysis of Resources	p. 154
6.4.3 Resource Allocation	p. 155
6.4.4 Implementation of Response Rule Base as Part of WAIMSS	p. 160
6.5 Summary	p. 162
Review Questions	p. 163
7 Traffic Diversion for Real-Time Traffic Management During Incidents	p. 165
7.1 A Scenario	p. 165
7.2 The Solution Approach	p. 165
7.3 Traffic Diversion	p. 168
7.4 Diversion System Architecture of WAIMSS	p. 172
7.4.1 System Components	p. 173
7.4.2 Diversion Initiation Module	p. 174
7.4.3 Diversion Strategy Planning Module (Heuristic Network Generator)	p. 175
7.4.4 Diversion Control/Routing Module	p. 177
7.5 Functions and Theory of the Network Generator	p. 177
7.6 Network Aggregation Models	p. 178
7.7 Theoretical Modeling of the Network Generator	p. 182
7.7.1 Elements and Types of Diversion Strategies	p. 182
7.8 Estimation of Incident Impact Area	p. 183
7.8.1 Representation of Incident Impact Area Knowledge	p. 184
7.8.2 Estimation of Diversion Volume	p. 186
7.8.3 Dynamic Link Elimination Concept	p. 188
7.8.4 Proposed Approach for Link Elimination	p. 189
7.8.5 Factors Influencing Link Elimination	p. 190
7.8.6 Rule Base for Dynamic Link Elimination	p. 194
7.8.7 Link Elimination Decision Making	p. 195
7.8.8 Link Elimination Rule Structure	p. 196
7.8.9 Link Elimination Decision Process	p. 197
7.8.10 Cumulative Weight Function for Conflict Resolution	p. 200
7.8.11 Rule Antecedents	p. 201
7.8.12 Link Elimination Rules	p. 201
7.9 Route Generation	p. 201
7.10 Summary and Need for Further Research	p. 205
7.10.1 Route Prioritization	p. 205
7.10.2 Testing and Validation of Diversion Strategies	p. 206
7.10.3 Multiple-Point Diversion	p. 207
7.10.4 Network Connectivity and Existence of Multiple Diversion Routes	p. 207
Review Questions	p. 207
8 Online Traffic Control	p. 211
8.1 Introduction	p. 211
8.2 Traffic Control Problems in ITS: Dynamic Traffic Routing/Assignment	p. 212
8.2.1 Traditional Techniques	p. 213
8.2.2 Ramp Metering Control	p. 216
8.2.3 Signalized Intersection Control	p. 218
8.2.4 Traffic Speed Control	p. 218
8.3 Feedback Control Designs for Macroscopic Control Problems	p. 218
8.4 Example Problem	p. 222
8.5 Summary	p. 226
Review Questions	p. 226
9 Conclusions and Future Research	p. 231
9.1 Conclusions	p. 231
9.1.1 Incident Input	p. 232
9.1.2 Duration Estimation and Delay Prediction	p. 232
9.1.3 Response Plan Development	p. 232
9.1.4 Traffic Diversion and Control	p. 233
9.2 Future Research	p. 233
9.2.1 Incident Detection	p. 233
9.2.2 Validation and Elaboration of Duration Prediction	p. 234
9.2.3 Real-World Implementation of Duration and Delay Models	p. 234
9.2.4 Advanced Traffic Control Algorithms	p. 235
9.2.5 Evaluation of Existing Incident Management Programs	p. 235
About the Authors	p. 237
Index	p. 239

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