| Preface |
| Introduction / 1： |
| Highway Congestion / 1.1： |
| Impact of Incidents on Highway Congestion / 1.2： |
| Incident Types and Impacts / 1.3： |
| Incident Management / 1.4： |
| Agencies Involved in Incident Management / 1.5： |
| Incident Management Process / 1.6： |
| Problems in Incident Management / 1.7： |
| Review of Incident Management Systems / 2： |
| Proposed Implementation Frameworks for Incident Management Support Systems / 2.1： |
| System Requirements and Characteristics / 2.2.1： |
| Blackboard Architecture / 2.2.2： |
| Incident Management Frameworks Based on Expert Systems / 2.3： |
| Incident Management Systems Based on Geographical Information Systems / 2.4： |
| Summary / 2.5： |
| Review Questions |
| Wide-Area Incident Management Support System Software / 3： |
| Design Considerations / 3.1： |
| Overall Concept / 3.1.1： |
| Framework for Integration / 3.1.2： |
| Application Design / 3.2： |
| Decision Support Modules / 3.2.1： |
| Duration Estimation Module / 3.2.2： |
| Delay Calculation Module / 3.2.3： |
| Response Module / 3.2.4： |
| Software Implementation / 3.3： |
| Software Implementation Architecture / 3.3.1： |
| Application Development / 3.3.2： |
| Data-level Integration / 3.3.3： |
| Command-level Integration / 3.3.4： |
| Incident Detection / 3.4： |
| What Is Incident Detection? / 4.1： |
| Traffic Surveillance and Data / 4.2.1： |
| Analysis of Traffic Data / 4.2.2： |
| Importance of Incident Detection Time / 4.2.3： |
| Effect of Incident Detection Time on Overall Incident Duration / 4.3： |
| Incident Detection Issues / 4.4： |
| Surveillance Issues / 4.4.1： |
| Algorithmic Issues / 4.4.2： |
| Verification Issues: Evaluation of Incident Detection Systems / 4.5： |
| Operational Field Tests / 4.6： |
| Transcom Transmit Project / 4.6.1： |
| I-880 Field Experiment: Incident Detection Using Cellular Phones / 4.6.2： |
| Incident Duration and Delay Prediction / 4.7： |
| Incident Duration Estimation Models / 5.1： |
| Northern Virginia Case Study: Methodological Structure / 5.2： |
| Structure and Design of Survey Forms and Data Collection / 5.2.1： |
| Analysis of New Incident Data / 5.2.2： |
| Detailed Analysis / 5.2.3： |
| Summary of Detailed Data Analysis / 5.2.4： |
| Development of Incident Clearance Time Prediction/Decision Trees / 5.2.5： |
| Validation of Prediction/Decision Trees / 5.2.6： |
| Distribution Properties of Incident Duration Data Collected for Case Study / 5.2.7： |
| Comparison of Our Results With Previous Work / 5.2.8： |
| Incident Delay Prediction / 5.3： |
| Deterministic Queuing Diagram / 5.3.1： |
| Other Methods to Determine Incident Delays / 5.3.2： |
| Incident Response / 5.4： |
| The Incident Response Problem / 6.1： |
| Tools / 6.1.1： |
| Research Needs for the Development of Incident Response Support Tools / 6.1.2： |
| Existing Incident Response Systems / 6.2： |
| Orange County, California: Caltrans / 6.2.1： |
| I-95 Corridor Coalition / 6.2.2： |
| Northern Virginia / 6.2.3： |
| Research on Incident Response / 6.2.4： |
| Formulation of a Response Plan / 6.3： |
| Incident Characterization / 6.3.1： |
| Service Identification / 6.3.2： |
| Agency Notification / 6.3.3： |
| Clearance Process / 6.3.4： |
| Computer Implementation of the Conceptual Computer-Based Response Plan / 6.3.5： |
| Case Study / 6.4： |
| Study Area and Response Statistics / 6.4.1： |
| Statistical Analysis of Resources / 6.4.2： |
| Resource Allocation / 6.4.3： |
| Implementation of Response Rule Base as Part of WAIMSS / 6.4.4： |
| Traffic Diversion for Real-Time Traffic Management During Incidents / 6.5： |
| A Scenario / 7.1： |
| The Solution Approach / 7.2： |
| Traffic Diversion / 7.3： |
| Diversion System Architecture of WAIMSS / 7.4： |
| System Components / 7.4.1： |
| Diversion Initiation Module / 7.4.2： |
| Diversion Strategy Planning Module (Heuristic Network Generator) / 7.4.3： |
| Diversion Control/Routing Module / 7.4.4： |
| Functions and Theory of the Network Generator / 7.5： |
| Network Aggregation Models / 7.6： |
| Theoretical Modeling of the Network Generator / 7.7： |
| Elements and Types of Diversion Strategies / 7.7.1： |
| Estimation of Incident Impact Area / 7.8： |
| Representation of Incident Impact Area Knowledge / 7.8.1： |
| Estimation of Diversion Volume / 7.8.2： |
| Dynamic Link Elimination Concept / 7.8.3： |
| Proposed Approach for Link Elimination / 7.8.4： |
| Factors Influencing Link Elimination / 7.8.5： |
| Rule Base for Dynamic Link Elimination / 7.8.6： |
| Link Elimination Decision Making / 7.8.7： |
| Link Elimination Rule Structure / 7.8.8： |
| Link Elimination Decision Process / 7.8.9： |
| Cumulative Weight Function for Conflict Resolution / 7.8.10： |
| Rule Antecedents / 7.8.11： |
| Link Elimination Rules / 7.8.12： |
| Route Generation / 7.9： |
| Summary and Need for Further Research / 7.10： |
| Route Prioritization / 7.10.1： |
| Testing and Validation of Diversion Strategies / 7.10.2： |
| Multiple-Point Diversion / 7.10.3： |
| Network Connectivity and Existence of Multiple Diversion Routes / 7.10.4： |
| Online Traffic Control / 8： |
| Traffic Control Problems in ITS: Dynamic Traffic Routing/Assignment / 8.1： |
| Traditional Techniques / 8.2.1： |
| Ramp Metering Control / 8.2.2： |
| Signalized Intersection Control / 8.2.3： |
| Traffic Speed Control / 8.2.4： |
| Feedback Control Designs for Macroscopic Control Problems / 8.3： |
| Example Problem / 8.4： |
| Conclusions and Future Research / 8.5： |
| Conclusions / 9.1： |
| Incident Input / 9.1.1： |
| Duration Estimation and Delay Prediction / 9.1.2： |
| Response Plan Development / 9.1.3： |
| Traffic Diversion and Control / 9.1.4： |
| Future Research / 9.2： |
| Validation and Elaboration of Duration Prediction / 9.2.1： |
| Real-World Implementation of Duration and Delay Models / 9.2.3： |
| Advanced Traffic Control Algorithms / 9.2.4： |
| Evaluation of Existing Incident Management Programs / 9.2.5： |
| About the Authors |
| Index |
| Preface |
| Introduction / 1： |
| Highway Congestion / 1.1： |
図書
