A Simulation-Based Dynamic Traffic Assignment Model for Emergency Management on the Hangzhou Bay Bridge

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A Simulation-Based Dynamic Traffic Assignment Model for Emergency Management on the Hangzhou Bay Bridge

Han, Shu / Fang, Shouen / Wang, Xuesong / Chen, Xiaohong / Cai, Yiyi

The freeway network is the backbone of regional geographic space and the bond of business activities, the construction of which determined the extent and depth of interaction among different geospatial units. Traffic incidents and bad weather will decrease the road capacity of a freeway, and have a significant impact on traffic flows. Bridges and tunnels are important components of freeways, which is much more fragile leading to a traffic jam for a longer time in wider areas. Taking the impacts of network topology, traffic control measures and traffic demand into account, Dynamic Traffic Assignment can analyze network performance characteristics and provide support for decision-making under an emergency. Hangzhou Bay Bridge is part of Shenyang-Zhuhai Freeway as well as part of the freeway network in the Around Hangzhou Bay Area. In this paper, a simulation-based DTA model is employed to evaluate the effectiveness of dynamic assignment using a freeway network in Around Hangzhou Bay Area, and assess the impacts of designed incident scenarios, as well as compare traffic situations of different traffic control strategies and information provisions. The results show that dynamic traffic assignment presents better performance over the static traffic assignment under an emergency. It shows that the network performance is sensitive to the duration of the emergency situation, which indicates that a timely clearance of an emergency and quick response of operators benefit not only the emergency site and surroundings but also the whole network. Moreover, travel time savings and traffic delay reduction can be realized as a result of Route Guidance System, which implies that the deployment of ITS technologies can reduce the undesirable impacts of emergencies on traffic operations.