摘要
公交旅行时间预测是提高公交服务可靠性、改善出行结构、缓解交通问题的关键技术之一。它涉及多种信息采集处理技术和复杂的模型与算法。公交旅行时间预测方法的研究,将是未来发展先进的公交系统重点关注的研究之一。本文基于公交IC卡、AVL(自动车辆定位)等数据,综合考虑多种交通随机影响因素,构建公交旅行时间预测模型,并将预测结果与实际结果对比分析,从而进一步优化预测模型,以期提高公共交通旅时间预测的精度和可靠性,为公交出行者提供更加可靠的信息服务。
Travel time prediction of transit is the key to improve the reliability of transit services, to improve trip structure, to alleviate traffic problems. It involves acquisition and processing technology of a variety of information and sophisticated models and algorithms, which will be one of research focus of development of advanced transit system in the future. Based on AVL and IC data, This paper consider a variety of traffic random factors, model travel time prediction of transit, and comparative analysis was carry on with the actual results, to further adjust and optimize the prediction model, to raise accuracy and reliability of the model of travel time prediction of transit, provide more reliable travel information services for traveler.
出处
《交通与运输》
2016年第A01期52-57,共6页
Traffic & Transportation
基金
交通事故影响下的城市路网拥堵传播规律及控制策略研究
浙江省自然科学基金青年科学基金项目(LQ15E080005)
关键词
单线路检测
多线路检测
旅行时间
卡尔曼滤波
预测模型
Single routesdetection
Multiple routes detection
Travel time
Kalman filter
Prediction model
