基于模糊感知阻抗的交通分配研究
|
摘要
针对城市道路交通拥堵现状和驾驶员对于路段认知偏差的现象,从驾驶员对于路段阻抗认知的问题着手.考虑道路交通阻抗的主要影响因素,包括交通流特性和附加的模糊感知阻抗,通过模糊聚类分析,同时考虑了感知行程时间、路段重要度和路段流量等因素,将路段的感知阻抗划分成不同等级,建立新的路阻函数模型.通过路网算例,将使用原始阻抗函数分配和改进后的阻抗函数分配结果进行对比.实验结果显示,改进后的分配结果能够反映出驾驶员对路段阻抗的模糊感知,较好地反映城市道路网中的拥挤路段,并为交通规划与管理工作提供更加合理的路网交通分配评价结果.
In view of the current situation of urban road traffic congestion and the phenomenon of drivers' cognitive bias towards road sections,starting from the problem of drivers' cognition towards road section impedance,the main influencing factors of road traffic impedance were considered,including traffic flow characteristics and additional fuzzy perceived impedance.Through fuzzy clustering analysis,considering factors such as perceived travel time,road segment importance and road segment flow,the perceived impedance of road segments was divided into different grades,and a new road resistance function model was established.Finally,through the road network example,the distribution results of the original impedance function and the improved impedance function were compared.The experimental results show that the improved distribution results can reflect drivers' fuzzy perception of road section impedance,better reflect the crowded road sections in the urban road network,which provides more reasonable road network traffic distribution evaluation results for traffic planning and management.
In view of the current situation of urban road traffic congestion and the phenomenon of drivers' cognitive bias towards road sections,starting from the problem of drivers' cognition towards road section impedance,the main influencing factors of road traffic impedance were considered,including traffic flow characteristics and additional fuzzy perceived impedance.Through fuzzy clustering analysis,considering factors such as perceived travel time,road segment importance and road segment flow,the perceived impedance of road segments was divided into different grades,and a new road resistance function model was established.Finally,through the road network example,the distribution results of the original impedance function and the improved impedance function were compared.The experimental results show that the improved distribution results can reflect drivers' fuzzy perception of road section impedance,better reflect the crowded road sections in the urban road network,which provides more reasonable road network traffic distribution evaluation results for traffic planning and management.
引文
[1]刘治彦,岳晓燕,赵睿.我国城市交通拥堵成因与治理对策[J].城市研究发展,2011,18(11):90-96.
[2]PORTA S,CRUCITTI P,LATORA V.The network analysis of urban streets:a dual approach[J].Physica A,2006,369(2):853-866.
[3]邓亚娟,杨云峰,马荣国.基于复杂网络理论的公路网结构特征[J].中国公路学报,2010,23(1):98-104.
[4]LUO Y L,WANG N,XIANG H K,et al.Road impedence model study under the control of intersection signal[C]. Mathematical Problems Engineering,2015(1):1-6.
[5]王文静,敬明,刘冬梅,等.基于LOGIT模型和BPR阻抗函数的容量限制-多路径交通分配研究[J].公路交通科技,2012,29(增刊1):81-85.
[6]刘宁,赵胜川,何南.基于BPR函数的路阻函数研究[J].武汉理工大学学报(交通科学与工程版),2013,37(3):546-548.
[7]LI X,QIN Z F,YANG L X,et al.Entropy maximization model for the trip distribution problem with fuzzy and random parameters[J].Journal of Computational and Applied Mathematics,2011,235:1906-1913.
[8]吴祥标.基于模糊随机理论的交通平衡分析理论研究[D].重庆:西南大学,2013.
[9]LUJAK M,GIORDANI S.Centrality measures for evacuation:finding agile evacuation routes[J].Future Generation Computer Systems,2018,83:401-412.
[2]PORTA S,CRUCITTI P,LATORA V.The network analysis of urban streets:a dual approach[J].Physica A,2006,369(2):853-866.
[3]邓亚娟,杨云峰,马荣国.基于复杂网络理论的公路网结构特征[J].中国公路学报,2010,23(1):98-104.
[4]LUO Y L,WANG N,XIANG H K,et al.Road impedence model study under the control of intersection signal[C]. Mathematical Problems Engineering,2015(1):1-6.
[5]王文静,敬明,刘冬梅,等.基于LOGIT模型和BPR阻抗函数的容量限制-多路径交通分配研究[J].公路交通科技,2012,29(增刊1):81-85.
[6]刘宁,赵胜川,何南.基于BPR函数的路阻函数研究[J].武汉理工大学学报(交通科学与工程版),2013,37(3):546-548.
[7]LI X,QIN Z F,YANG L X,et al.Entropy maximization model for the trip distribution problem with fuzzy and random parameters[J].Journal of Computational and Applied Mathematics,2011,235:1906-1913.
[8]吴祥标.基于模糊随机理论的交通平衡分析理论研究[D].重庆:西南大学,2013.
[9]LUJAK M,GIORDANI S.Centrality measures for evacuation:finding agile evacuation routes[J].Future Generation Computer Systems,2018,83:401-412.