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Traffic incidents, including disabled vehicles, fire, road debris, constructions, police activities, and vehicle crashes, have long been recognized as the main contributor of congestion in highway networks and the related adverse environmental impacts. Unlike recurrent congestion, non-recurrent congestion is random in occurrence and duration owing to the nature of incidents so that it is highly unlikely to follow predetermined temporal and spatial patterns. These findings indicate the need to have an efficient and effective incident management system, including detection, response, clearance, and network-wise traffic management to contend with non-recurrent congestion.

In such a system, reliably estimated incident duration, the time difference between the onset of an incident and its complete removal, plays a key role to accomplish its goal - mitigating incident-related congestions and delays. However, due to the complex interactions between factors contributing to the resulting incident duration and the difficulty in recording data at the desirable level of quality, development of such a system for incident traffic management remains at its infancy. Thus, this research has developed a methodology for estimating incident duration and has identified critical variables and their interrelationships related to incident duration using the MDSHA (the Maryland State Highway) incident database. The proposed system is composed of the sequential

classifier with association rules (SCAR) and two supplemental models. This study has confirmed its reliability and robustness through a comparative study with several state-of-the-art approaches.

To minimize the incident impact, this study further pursued two additional objectives: (1) development of a deployment strategy for incident response units, and (2) design of a detour decision support model for control center staff to determine the necessity of detouring traffic. To achieve the second objective, an integer programming model has been developed from a new perspective of minimizing incident-induced delay, rather than minimizing total response time in the literature. Extensive tests of the developed model's performance and a comparative analysis with other existing models have confirmed the reliability and robustness of the proposed model. To achieve the third objective, this research has first explored key factors critical to the decision for implementing detour/diversion operations. Those factors have been integrated with an Analytical Hierarchy Process (AHP) to constitute the hybrid multi-criteria decision support system. A case study with the developed system has confirmed its reliability and flexibility.

The proposed incident estimation model integrated with a response unit allocation model and a detour decision model can enhance the current traffic incident management system for highway agencies to contend with freeway non-recurrent congestion and to assist traffic operators in answering some critical issues such as: "what would be the estimated duration to clear the detected incident?", "How far will the maximum queue reach?", "Can the projected delay and congestion during incident management warrant the detour operations?", and "What would be the resulting operational costs and total socio-economic benefits due to the effective detour operations?". Furthermore, such a system will be able to substantially improve the quality and efficiency of motorists' travel over congested highways.