Scholarlink

As intelligent and connected vehicles advance, evaluating their impact on urban traffic remains challenging due to the lack of real-world data. This paper presents an agent-based simulation framework using JADE and SUMO to analyze heterogeneous vehicle interactions and the effects of deploying advanced driving systems. Our framework enables researchers to explore how conventional and cooperative driving systems influence traffic flow, safety, and emissions, offering a valuable tool for developing intelligent transportation systems. Using our framework, we compare a conventional car-following model with a cooperative model that leverages vehicle-to-vehicle (V2V) communication. The results show that the cooperative model leads to smoother vehicle acceleration and improved driving comfort compared to the conventional model.

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

MATSum: Multi-agent Traffic Simulation of Urban Mobility with Consideration of Heterogeneous Vehicles

  • 会议论文

  • 发表日期：

    2025年

查看全文
  • Oussama Messaoudi,
  • Akli Abbas

摘要

As intelligent and connected vehicles advance, evaluating their impact on urban traffic remains challenging due to the lack of real-world data. This paper presents an agent-based simulation framework using JADE and SUMO to analyze heterogeneous vehicle interactions and the effects of deploying advanced driving systems. Our framework enables researchers to explore how conventional and cooperative driving systems influence traffic flow, safety, and emissions, offering a valuable tool for developing intelligent transportation systems. Using our framework, we compare a conventional car-following model with a cooperative model that leverages vehicle-to-vehicle (V2V) communication. The results show that the cooperative model leads to smoother vehicle acceleration and improved driving comfort compared to the conventional model.