基于演化细胞自动机的自适应交通控制研究  

Self-adaptive Traffic Signal Control Based on Evolvable Cellular Automata

作　　者：刘鹏[1] 阚亚斌[1] 聂鑫 LIU Peng;KAN Yabin;NIE Xin(Dalian Navy Academy,Dalian 116018)

机构地区：[1]海军大连舰艇学院,大连116018

出　　处：《计算机与数字工程》2018年第12期2458-2462,共5页Computer & Digital Engineering

摘　　要：提出了一种改进的二维细胞自动机交通流模型,此种细胞自动机边界固定为0,寻找满足细胞自动机全局状态变为全0的最小迭代次数的规则执行顺序。通过实验得出:通过演化提高了交通控制效率,而且优化效率与车辆密度和横纵车辆比相关,即横纵车辆比越小,优化效率越高,而在车辆密度为50%左右,优化效率最好。进而得出一个一般的结论:较小和较大的车辆密度下交通调节效果不明显,只有在某种车辆密度下进行正确的调节才能发挥交通调节的最大作用。A new model of tow dimension cellular automata for traffic flow is proposed.The edge of this model is all zero.The problem is to find out the order of the implementation of the rule which makes the cellular automata’s states to all 0s.Several experi?ments are taken and confirmed that the traffic control rate is improved by evolution,and the optimization efficiency is related to the vehicle density and the simulated vehicle ratio,that is,the smaller the horizontal and vertical vehicle ratio,the higher the optimiza?tion efficiency,and it will get the most efficiency at the density of the vehicle is fifty percent.And we can get a more general conclu?sion that only at the special density of vehicle and take right traffic regulation will play a significant role.

关 键 词：演化算法 细胞自动机 BML模型 智能交通系统 

分 类 号：TP301[自动化与计算机技术—计算机系统结构]