Energy-Efficient Route Navigation (Eco-Routing) for Electric Vehicles in SUMO

IF 2.1 Q3 COMPUTER SCIENCE, HARDWARE & ARCHITECTURE IEEE Canadian Journal of Electrical and Computer Engineering Pub Date : 2024-10-03 DOI:10.1109/ICJECE.2024.3425515
Insaf Sagaama;Amine Kchiche;Wassim Trojet;Farouk Kamoun
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Abstract

The diffusion of electric vehicles (EVs) is recently gaining great attention in the road transport and automotive sectors as an attempt to bring in an emission-free world. EVs are considered a key to future clean transportation systems. However, these vehicles still suffer from limited battery capacity and range anxiety. Therefore, EVs manufacturers are focusing on reducing energy consumption and CO2 emissions. In addition, research in the context of intelligent transportation systems embedding information and communication technologies are focusing on the optimization of the energy consumption as a valuable solution to foster the wide diffusion of EVs. In this article, we propose a simulation platform for eco-routing services based on estimating EV energy consumption to provide the most energy-efficient routes for the EV while traveling. We provide an energy map that can be used for eco-routing through a real-time data collection of the EV energy consumption. The energy map was established in the traffic simulator Simulation of Urban MObility (SUMO) to show the efficiency of the proposed eco-routing strategy compared to the other strategies based on establishing the fastest routes. This map will be exploited as good support, in the future, for advanced research on the EV concept.
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相扑比赛中电动汽车的节能路线导航(Eco-Routing
最近,电动汽车(ev)的普及在道路运输和汽车行业引起了极大的关注,因为它试图实现零排放世界。电动汽车被认为是未来清洁交通系统的关键。然而,这些车辆仍然受到电池容量有限和里程焦虑的困扰。因此,电动汽车制造商将重点放在降低能耗和二氧化碳排放上。此外,在嵌入信息和通信技术的智能交通系统背景下,研究的重点是能源消耗的优化,作为促进电动汽车广泛扩散的有价值的解决方案。本文提出了一种基于电动汽车能耗估算的生态路径服务仿真平台,为电动汽车在行驶过程中提供最节能的路径。我们提供了一个能源地图,可用于生态路线通过实时数据收集的电动汽车的能源消耗。在交通模拟器仿真城市交通(SUMO)中建立能量图,以显示基于建立最快路线的生态路径策略与其他策略相比的效率。这张地图将在未来为电动车概念的高级研究提供良好的支持。
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