个人快速交通系统智能协同控制与优化

提出了一种新型智能协同控制运行方案，基于个人快速交通(PRT)车辆的运行规则与车辆间的自组织关系，以自底向上的方式建立动态知识图谱，用以辅助车辆运行决策；通过领航者-跟随者策略在车辆行驶过程中形成虚拟车队运行，在此基础上，将滚动优化策略与粒子群算法(PSO)相结合，对车辆的加速度和减速度进行滚动优化调整，缩短了PRT车辆形成虚拟编队的运行时间，进一步提高了PRT系统的运输能力．结果表明:智能协同控制运行方案使得PRT车辆形成虚拟编队所耗时间平均减少了约38%，每小时运输客流量平均提高了约1.5倍；该运行方案保证了PRT系统运行的高效性和安全性，符合低碳出行、绿色发展的需要． 

Cooperative intelligent control and optimization of personal rapid transportation

Traditional personal rapid transportation(PRT) vehicles have limited number of single vehicle seats, and have the challenge of complex and changeable driving environment, therefore are difficult to meet actual traffic demand of large volume of urban transportation．A new intelligent cooperative control operation scheme is proposed to solve this problem．Operation rules of PRT vehicles and self-organization relationship among vehicles are used to establish dynamic knowledge maps in a bottom-up manner to assist decision-making of vehicle operation．The leader-follower strategy is used to form virtual fleet operation during actual vehicle driving．Rolling optimization strategy and particle swarm optimization (PSO) algorithm are combined to adjust rolling acceleration of vehicles, resulting in shortened running time of PRT vehicles forming a virtual formation, and further improved transport capacity of PRT system．Intelligent cooperative control operation scheme is found to reduce the time spent by PRT vehicles to form a virtual formation by 38%, passenger flow per hour is increased 1.5 times．This operation scheme ensures high efficiency and safety of PRT system operation, and meets the needs of low-carbon travel and green development．