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原文传递 Integrating safety and mobility for pathfinding using big data generated by connected vehicles

题名：	Integrating safety and mobility for pathfinding using big data generated by connected vehicles
正文语种：	英文
作者：	Nima Hoseinzadeh;Ramin Arvin;Asad J. Khattak;Lee D. Han
作者单位：	University of Tennessee
关键词：	Big data; connected vehicle; multi-objective pathfinding; route planning; safety; travel time; volatility
摘要：	With the emergence of the in ternet of things, pathfi nding problems have recently received a significant amount of attention. Various commercial applications provide automated routing by considering travel time, travel distanee, fuel consumption, complexity of the road, etc. However, many of these prospective applications do not consider route safety. Emerge nee of high-resolution big data gen erated by conn ected vehicles (CV) helps us to integrate safety into routing problem. The goal of this study is to address safety aspects in pathfinding problems by developing a methodological framework that simultaneously considers safety and mobility. To reach this goal, the concept of volatility is utilized as a surrogate safety performanee measure to quantify route safety and driver behavior. The proposed framework uses CV big data and real-time traffic data to calculate safety indices and travel times. Measured safety indices in elude 5-year crash history, route speed and acceleration volatility, and driver volatility. Travel time and safety shape a cost function called "route impedanee." The algorithm has the flexibility for the user to predefine the weight for safety con sideration. It also uses driver volatility to automatically increase safety weight for volatile drivers. To illustrate the algorithm, a numerical example is provided using an origin-destination pair in Ann Arbor, Ml, and more than 42 million CV observations from around 2,500 CVs from the Safety Pilot Model Deployment (SPMD) were analyzed. The sensitivity analysis is performed to discuss the impact of penetration rate of CVs and time of the trip on the results. Finally, this paper shows suggested routes for multiple seenarios to demonstrate the outcome of the study. The results revealed that the algorithm might suggest different routes when con sidering safety in dices and not just travel time.
出版日期：	2020
出版年：	2020
期刊名称：	Journal of Intelligent Transportation Systems Technology Planning and Operations
卷：	Vol24
期：	No01-06
页码：	404-420