A Centralized Route-Management Solution for Autonomous Vehicles in Urban Areas

Electronics

Juan-Carlos Cano¹  JorgeLuis Zambrano-Martinez¹  CarlosT. Calafate¹  Pietro Manzoni¹  Lenin-Guillermo Lemus-Zúñiga²  David Soler³  Thierry Gayraud⁴ 

[1] Department of Computer Engineering (DISCA), Universitat Politècnica de València, 46022 Valencia, Spain;ITACA Institute. Universitat Politècnica de València, Camino de Vera S/N, 46022 Valencia, Spain;Institute of Multidisciplinary Mathematics (IMM), Universitat Politècnica de València, 46022 Valencia, Spain;LAAS/CNRS—Groupe OLC, Université Paul Sabatier-Toulouse III, 31031 Toulouse, France;

关键词: autonomous vehicle;    traffic prediction;    SUMO;    route server;    DFROUTER;    intelligent transportation system;   

DOI  :  10.3390/electronics8070722

来源: DOAJ

【 摘 要 】

Currently, one of the main challenges that large metropolitan areas must face is traffic congestion. To address this problem, it becomes necessary to implement an efficient solution to control traffic that generates benefits for citizens, such as reducing vehicle journey times and, consequently, environmental pollution. By properly analyzing traffic demand, it is possible to predict future traffic conditions, using this information for the optimization of the routes taken by vehicles. Such an approach becomes especially effective if applied in the context of autonomous vehicles, which have a more predictable behavior, thus enabling city management entities to mitigate the effects of traffic congestion and pollution, thereby improving the traffic flow in a city in a fully centralized manner. This paper represents a step forward towards this novel traffic management paradigm by proposing a route server capable of handling all the traffic in a city, and balancing traffic flows by accounting for present and future traffic congestion conditions. We perform a simulation study using real data of traffic congestion in the city of Valencia, Spain, to demonstrate how the traffic flow in a typical day can be improved using our proposed solution. Experimental results show that our proposed traffic prediction equation, combined with frequent updating of traffic conditions on the route server, can achieve substantial improvements in terms of average travel speeds and travel times, both indicators of lower degrees of congestion and improved traffic fluidity.

【 授权许可】

Unknown