巡航控制
协同自适应巡航控制
车头时距
微模拟
流量(计算机网络)
排
燃料效率
航程(航空)
专用短程通信
计算机科学
理论(学习稳定性)
车载通信系统
汽车工程
模拟
工程类
运输工程
控制(管理)
车载自组网
电信
无线自组网
计算机网络
无线
航空航天工程
机器学习
人工智能
作者
Riccardo Donà,Konstantinos Mattas,Yinglong He,Giovanni Albano,Biagio Ciuffo
标识
DOI:10.1016/j.trc.2022.103687
摘要
Adaptive Cruise Control (ACC) systems have been expected to solve many problems of motorway traffic. Now that they are widespread, it is observed that the majority of existing systems are string unstable. Therefore, small perturbations in the speed profile of a vehicle are amplified for the vehicles following upstream, with negative impacts on traffic flow, fuel consumption, and safety. Increased headway settings provide more stable flow but at the same time it deteriorates the capacity. Substantial research has been carried out in the past decade on utilizing connectivity to overcome this trade-off. However, such connectivity solutions have to overcome several obstacles before deployment and there is the concrete risk that motorway traffic flow will considerably deteriorate in the meanwhile. As an alternative solution, the paper explores multianticipation without inter-vehicle communication, taking advantage of the recent advancements in the field of RADAR sensing. An analytical study is carried out, based on the most widely used model and parameter settings used to simulate currently available commercial ACC systems, comparing the transfer functions and step responses for the nominal and the multianticipative formulations. Then, a microsimulation framework is employed to validate our claim on different speed profiles. Analytical results demonstrate that multianticipation enhances stability without impacting traffic flow. On the contrary, the simulation study indicates that the multianticipative-ACC can produce higher road capacity even in the presence of external disturbances and for a wide range of calibrated parameters. Finally, optimality conditions for the tuning of the headway policy are derived from a Pareto optimization.
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