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Data-Driven Spatial Modeling For Quantifying Networkwide Resilience In The Aftermath Of Hurricanes Irene And Sandy, Yuan Zhu, Kun Xie, Kaan Ozbay, Fan Zuo, Hong Yang
Data-Driven Spatial Modeling For Quantifying Networkwide Resilience In The Aftermath Of Hurricanes Irene And Sandy, Yuan Zhu, Kun Xie, Kaan Ozbay, Fan Zuo, Hong Yang
Computational Modeling & Simulation Engineering Faculty Publications
In recent years, the New York City metropolitan area was hit by two major hurricanes, Irene and Sandy. These extreme weather events disrupted and devastated the transportation infrastructure, including road and subway networks. As an extension of the authors' recent research on this topic, this study explored the spatial patterns of infrastructure resilience in New York City with the use of taxi and subway ridership data. Neighborhood tabulation areas were used as the units of analysis. The recovery curve of each neighborhood tabulation area was modeled with the logistic function to quantify the resilience of road and subway systems. Moran's …
Impact Of Connected Vehicles On Mitigating Secondary Crash Risk, Hong Yang, Zhenyu Wang, Kun Xie
Impact Of Connected Vehicles On Mitigating Secondary Crash Risk, Hong Yang, Zhenyu Wang, Kun Xie
Computational Modeling & Simulation Engineering Faculty Publications
Reducing the risk of secondary crashes is a key goal for effective traffic incident management. However, only few countermeasures have been established in practices to achieve the goal. This is mainly due to the stochastic nature of both primary and secondary crashes. Given the emerging connected vehicle (CV) technologies, it is highly likely that CVs will soon be able to communicate with each other through the ad-hoc wireless vehicular network. Information sharing among vehicles is deemed to change traffic operations and allow motorists for more proactive actions. Motorists who receive safety messages can be motivated to approach queues and incident …