公共交通AVL数据在延误变异性评价中的应用

IF 0.7 Q4 TRANSPORTATION
M. M. Harsha
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引用次数: 0

摘要

出行时间是评价公共交通系统效率和性能的重要因素。公交车站延误占旅行时间的较大比例,这取决于乘客数量、公交车站特征、交通状况、公交性能等。许多印度的公交公司都是按阶段而不是站来存储乘客的详细信息,这使得很难评估公交站层面的延误变化。在这方面,印度迈索尔实施的智能交通系统(ITS)的自动车辆定位(AVL)数据被考虑用于评估公交车站延误变化。利用收集到的数据,采用基于轨迹的公式估计五站的延误。利用概率分布来模拟时延的可变性。采用柯尔莫戈洛夫-斯米尔诺夫(KS)检验对其性能进行分析。利用变异系数(COV)对公交车站延误的日变异进行了评价。延迟分布的性能评价结果表明,广义极值(GEV)分布在精度、鲁棒性和生存能力方面是延迟变异性的最佳描述符。在没有乘客数据收集系统的情况下,本研究提出的使用AVL数据评估延误的方法是有帮助的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Public Transit AVL Data for Evaluation of Delay Variability
The travel time is the significant factor in evaluating efficiency and performance of public transit system. A greater percentage of travel time is accounted by bus stop delays which depends on passenger count, bus stop characteristics, traffic condition, bus performance, etc. Many of the Indian transit agencies store the passenger details stage wise not stop wise, which makes it difficult to evaluate delay variability at bus stop level. In this connection, Automatic Vehicle Location (AVL) data from Intelligent Transport System (ITS) implemented at Mysore, India is considered for evaluating bus stop delay variability. The collected data is used for estimating delay at five stops by adopting trajectory-based formulation. The probability distributions have been utilized to model the variability in delay. The performance has been analysed using Kolmogorov-Smirnov (KS) test. The daily variability of delay at bus stops has been evaluated using Coefficient of Variation (COV). The results of the performance evaluation of delay distributions show that the Generalized Extreme Value (GEV) distribution is the best descriptor of the delay variability in terms of accuracy, robustness, and survival capacity. In the absence of passenger data collection systems, method of evaluation of delay using AVL data presented in this study is helpful.
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来源期刊
CiteScore
2.30
自引率
0.00%
发文量
19
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