CAJ | 학술논문

在对南昌市城区主干道港湾式公交停靠站调查的基础上，通过 Vissim 仿真模拟得到大量交通流数据，从港湾式站台设置的长度、站台乘客等待数量、路段车道数、路段车辆的平均速度、站台停止车辆数、以及进出口平均延误时间6个方面建立神经网络分析模型，以路段平均延误车辆/路段实际通行能力作为通行能力的影响折减，运用 Matlab 软件编程求得变量因素与输出影响的连接强度权值 W 与偏置值 B ，为港湾式公交站对路段通行能力影响提供了定量化影响系数。
재대남창시성구주간도항만식공교정고참조사적기출상，통과 Vissim 방진모의득도대량교통류수거，종항만식참태설치적장도、참태승객등대수량、로단차도수、로단차량적평균속도、참태정지차량수、이급진출구평균연오시간6개방면건립신경망락분석모형，이로단평균연오차량/로단실제통행능력작위통행능력적영향절감，운용 Matlab 연건편정구득변량인소여수출영향적련접강도권치 W 여편치치 B ，위항만식공교참대로단통행능력영향제공료정양화영향계수。
Based on the survey of harbor-shaped bus stops in the main roadways in Nanchang City ,this paper gen-erates a large quantity of traffic flow data from Vissim simulation .A neural network is built from the six parameters of the bus stop length ,number of waiting passengers ,number of lanes ,road vehicle average speed ,number of vehicles stopped in the stop ,and the import and export of the number average delay time ,etc .The ratio of section average vehicle delay to link capacity is used as the capacity reduction .The neural network is implemented in Matlab platform to obtain variable factors and output influence weights and bias values of connection strength of W and B ,which provides the quan-titative influence coefficient for the bus stops on the road capacity .