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1.发明授权公开(公告)号：US10748421B2
公开(公告)日：2020-08-18
申请号：US15778064
申请日：2017-09-21
发明人： Shaopeng Zhong , Haimin Jun , Kai Liu , Quanzhi Wang , Kun Wang , Yanquan Zou , Lu Zhang , Tianli Tang
摘要： The present invention relates to a method for estimating distribution of urban road travel time in considering operation state of taxi, and belongs to the technical field of urban transportation planning and management. The distributions of path travel time are respectively estimated according to different operation states of the taxi. When the distribution of the path travel time is estimated, adjacent road sections in the road network are not independent. In the present invention, the Markov model is added to describe the correlation of the travel time distribution between the adjacent road sections, so as to increase science and accuracy of the estimation result. In the present invention, the weight is set according to the proportion of the number of the vehicles under two different operation states to obtain the final distribution of the path travel time. Driving behaviors of taxi drivers under two operation states of no passenger and passenger service may be different, so a difference between the travel time estimated from direct use of taxi data and a true value inevitably exists. The proposed model is calculated through Shenzhen data, which shows that the calculated travel time distribution function is more accurate after considering the operation states.
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公开(公告)号：US10783774B2
公开(公告)日：2020-09-22
申请号：US16076109
申请日：2017-10-11
发明人： Shaopeng Zhong , Haimin Jun , Yanquan Zou , Kun Wang , Kangli Zhu
IPC分类号： G08G1/01
摘要： A method for estimating road travel time based on the built environment and low-frequency floating car data belongs to the technical field of urban traffic management and traffic system evaluation. The method takes built environment as an explanatory variable of the road travel time. The interpretability of this variable is proved by a numerical example. In addition, the method determines distribution parameters of road travel time using the number distribution of vehicles instead of distance. The benefits of the method are that: (1) it explains the positive effect of built environment on road travel time; and (2) it reflects the speed difference among different road sections, which can improve the precision of estimating road travel time.
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