School of Transportation Science and Engineering, Harbin Institute of Technology, Harbin 150090, China.
Department of Civil and Environmental Engineering, University of Macau, Macau 999078, China.
Sensors (Basel). 2021 Jul 5;21(13):4619. doi: 10.3390/s21134619.
In order to explore the changes that autonomous vehicles on the road would bring to the current traffic and make full use of the intelligent features of autonomous vehicles, the article defines a self-balancing system of autonomous vehicles. Based on queuing theory and stochastic process, the self-balancing system model with self-balancing characteristics is established to balance the utilization rate of autonomous vehicles under the conditions of ensuring demand and avoiding an uneven distribution of vehicle resources in the road network. The performance indicators of the system are calculated by the MVA (Mean Value Analysis) method. The analysis results show that the self-balancing process could reduce the average waiting time of customers significantly in the system, alleviate the service pressure while ensuring travel demand, fundamentally solve the phenomenon of concentrated idleness after the use of vehicles in the current traffic, maximize the use of the mobile vehicles in the system, and realize the self-balancing of the traffic network while reducing environmental pollution and saving energy.
为探索道路上自动驾驶汽车带来的变化，充分利用自动驾驶汽车的智能特性，本文定义了自动驾驶汽车的自平衡系统。基于排队论和随机过程，建立了具有自平衡特性的自平衡系统模型，以在保证需求和避免路网车辆资源分配不均的情况下平衡自动驾驶汽车的利用率。通过 MVA（均值分析）方法计算系统的性能指标。分析结果表明，自平衡过程可以显著减少系统中客户的平均等待时间，在保证出行需求的同时缓解服务压力，从根本上解决当前交通中车辆使用后集中闲置的现象，最大限度地利用系统中的移动车辆，实现交通网络的自平衡，同时减少环境污染和节约能源。
