Improving bus travel time reliability can attract more commuters to use bus transit, and therefore reduces the share of car and alleviates traffic congestion. This paper formulates a new bus travel time reliability metric that jointly considers two stochastic processes: the in-stop waiting process and in-vehicle travel time process, and the bus travel time reliability function is calculated by the convolution of independent events’ probabilities. The new reliability metric is defined as the probability when bus travel time is less than a certain threshold and can be used in both conditions with and without bus transfer. Next, Automatic Vehicle Location (AVL) data of the city of Harbin is used to demonstrate the applicability of the proposed method. Results show that factors such as weather, day of week, departure time, travel distance, and the distance from the boarding stop to the bus departure station can significantly affect the travel time reliability. Then, a case with low bus frequency is analyzed to show the impact of travellers’ arrival distribution on their bus travel time reliability. Further, it is demonstrated that the travel time reliabilities of two bus transfer schemes of the same Origin-Destination (O-D) pair can have significantly different patterns. Understanding the bus travel time reliability pattern of the alternative bus routes can help travellers to choose a more reliable bus route under different condition. The proposed bus travel time reliability metric is tested to be sensitive to the effect of different factors and can be applied in bus route recommendation, bus service evaluation and optimization.
哈尔滨工业大学交通科学与工程学院副教授。2014年入选哈工青年拔尖人才选聘计划，主持国家自然科学基金面上和青年项目、中国博士后科学基金面上和国际交流计划派出项目、CCF-滴滴大数据联合实验室盖亚青年学者项目等。研究领域包括网络交通流理论、交通系统可靠性、公交优先策略和交通大数据分析，研究成果发表在：Transportation Research Part B/C、Transport Policy、Transportmetrica A、Journal of Transportation Engineering等国际权威期刊。目前，担任世界交通运输大会（WTC）交通工程学部“交通网络设计”技术委员会主席。
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