以出租车GPS采集的浮动车数据为依据,研究出租车驾驶员路径选择的认知及类蚂蚁的行为特征。根据城市道路功能等级与出租车的通行频率等信息素,建立出租车驾驶员路径选择信息素等级路网,并以此作为路网初始信息素,综合考虑路径通行时间、通行距离、路径信息素等级等多个因素,提出了基于蚁群优化算法的公众出行路径规划优化算法。以武汉市路网和浮动车为试验数据,将模型规划的道路与浮动车数据库中的轨迹进行了比较。结果表明:基于蚁群优化算法与出租车GPS数据的公众出行路径同出租车驾驶员选择的出行路径相似度很高,能为公众出行提供出租车驾驶员选择的行车路径。
Abstract
Taking floating car data (FCD) collected by taxi GPS as reference, taxi driver's route selection recognition and behavior characteristics of ant colony were studied. According to road function level in urban and taxi passing rate, the pheromone hierarchical road network for taxi driver's route selection was set up. Taking it as initial pheromone of road network, comprehensively considering route passing time, passing distance and route pheromone hierarchical, route planning algorithm for public traveling based on ant colony optimization algorithm was proposed. Road of model planning in the paper and track of floating car database were compared by test data of FCD and road network of Wuhan. Results show that route for public traveling based on ant colony optimization algorithm and taxi GPS data is very similar to taxi driver's traveling route. It can provide taxi driver's traveling route for public traveling.
关键词
交通工程 /
公众出行路径 /
蚁群优化算法 /
浮动车数据 /
信息素
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Key words
traffic engineering /
public travel route /
ant colony optimization algorithm /
floating car data /
pheromone
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中图分类号:
U491.254
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脚注
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基金
国家高技术研究发展计划(“八六三”计划)项目(2009AA11Z213);国家自然科学基金项目(40801155);“十一五”国家科技支撑计划项目(2008BAK49B02)
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