基于贝叶斯网络的公交路径选择影响因素分析
首发时间:2018-10-15
摘要:公交路径选择影响因素决定了公交路径规划方案的优劣。本文利用贝叶斯参数估计方法和K2算法构建了公交路径选择影响因素网络拓扑图,确定了公交路径选择的影响因素。利用主成分分析法得出公交路径选择影响因素的主成分,及每个主成分对路径选择的贡献率。利用联合树引擎推理分析影响因素对公交路径选择的影响规律。结果表明:(1)公交路径选择受路径距离、出行时耗等8个因素影响;(2)公交路径影响因素包括3个主成分,按贡献率由大到小分别为公交路径、出行环境和乘客对路径的熟悉度;(3)路径距离、出行时耗、换乘次数和站点数的减少利于最优路径的选择;(4)一个月内搭乘频数可反映乘客对线路的偏好性,考虑用户的偏好性可制定更符合用户期望的公交路径。
关键词: 交通运输规划与管理 公交路径选择 影响因素 贝叶斯网络模型 K2算法
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Bayesian network-based bus path choice factor analysis
Abstract:Planning scheme of bus path is judged by influencing factors. Using K2 method and Bayesian method, a Bayesian network is built and influencing factors are confirmed. Through PCA, principal components on bus path choice are confirmed, while factors\' contribution rate to bus path choice is computed. Influencing laws on factors to bus path choice are analyzed using the junction tree engine. The results indicate that, first, bus path choice was influencing by 8 factors such as trip distance, time of riding etc. Second, there are three principal components influencing bus path choice. Travel environment and familiarity of bus path are sorted by contribution rate in descending order. Third, the decreasing of trip distance, time of riding, transfer time and station numbers is of benefit to optimal path. Last, frequency within one path reflects passenger\'s preference to bus path. Considering preference is beneficial to making bus path meeting user\'s expectations.
Keywords: transportation planning and management bus path choice influencing factors Bayesian network K2 method
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