通过路侧单元优化自动驾驶车辆过路口，显著减少急加速急刹车
A Roadside Unit for Infrastructure Assisted Intersection Control of Autonomous Vehicles
- 用路侧单元与车辆通信，动态调控红绿灯和车速
- 实测使车辆加减速次数减少75.35%，降低燃油消耗
- 适合智能交通、车联网研究者参考，代码开源
自动驾驶技术与蜂窝网络速度的进步推动了车与万物（V2X）通信的发展。增强道路安全与提升燃油效率是未来交通系统中V2X的重要目标。自适应交叉口控制系统可通过减少停车时间并预测短期交通状况，实现这些目标。将V2X融入交通管理系统，可构建更安全的道路环境，并推动智慧互联城市发展。为验证控制算法，我们搭建了包含两辆自动驾驶电动车、一个路侧单元（RSU）和交通信号灯的四向交叉口与人行横道仿真与真实场景。该架构使车辆通过路口时的加减速行为最多减少75.35%，已被证明可降低燃油车油耗。本研究提出一种低成本、可扩展的智能交叉口控制方案，作为后续研究的原型基础。项目代码已公开于 https://github.com/MMachado05/REU-2024。
原文摘要 · Abstract (English)
Recent advances in autonomous vehicle technologies and cellular network speeds motivate developments in vehicle-to-everything (V2X) communications. Enhanced road safety features and improved fuel efficiency are some of the motivations behind V2X for future transportation systems. Adaptive intersection control systems have considerable potential to achieve these goals by minimizing idle times and predicting short-term future traffic conditions. Integrating V2X into traffic management systems introduces the infrastructure necessary to make roads safer for all users and initiates the shift towards more intelligent and connected cities. To demonstrate our control algorithm, we implement both a simulated and real-world representation of a 4-way intersection and crosswalk scenario with 2 self-driving electric vehicles, a roadside unit (RSU), and a traffic light. Our architecture reduces acceleration and braking through intersections by up to 75.35%, which has been shown to minimize fuel consumption in gas vehicles. We propose a cost-effective solution to intelligent and connected intersection control to serve as a proof-of-concept model suitable as the basis for continued research and development. Code for this project is available at https://github.com/MMachado05/REU-2024.
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