文章基本信息

标题：Implementation of Model Predictive Control into Closed-Loop Micro-Traffic Simulation for Connected Automated Vehicle
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作者：Jongryeol Jeong ; Namdoo Kim ; Dominik Karbowski 等
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：5
页码：224-230
DOI：10.1016/j.ifacol.2019.09.036
语种：English
出版社：Elsevier
摘要：AbstractConnected automated vehicles can utilize and share driving information with other vehicles and infrastructure in real time. Applying plentiful vehicle-driving data enhances the safety, mobility and performance of connected automated vehicles. Adaptive cruise control, one of the connected automated vehicle achievements, optimizes the speed in a constrained environment to achieve the best fuel economy while maintaining the safety of the vehicle. Model predictive control is widely used to achieve both fuel savings and robustness. It is important to validate the performance, robustness and implementability of model predictive control under real-world conditions that reflect the features of connected automated vehicle driving. In this research, model predictive control using quadratic programming and dynamic programming was implemented in a newly developed micro-traffic simulation program. That program, RoadRunner, can simulate the various driving conditions such as intersection status, speed limit, and grade of the road. RoadRunner is based on a forward-looking vehicle simulation tool, Autonomie, which has various types of configurations and validated vehicle models based on vehicle dynamics that make the simulation more reliable. As a result, the controllers show 3-5 % fuel savings accompanying the applicability to the real world driving.
关键词：KeywordsConnected automated vehiclesModel predictive controlQuadratic programmingDynamic programmingMicro traffic simulationRoadRunnerForward-looking simulation