Bus travel time reliability incorporating stop waiting time and in‑vehicle travel time with AVL data

Improving bus travel time reliability can attract more commuters to use bus transit,and therefore reduces the share of cars and alleviates trafc 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 defned 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 the week,departure time,travel distance,and the distance from the boarding stop to the bus departure station can signifcantly afect the travel time reliability.Then,a case with low bus departure frequency is analyzed to show the impact of travelers’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 signifcantly diferent patterns.Understanding the bus travel time reliability pattern of the alternative bus routes can help passengers to choose a more reliable bus route under diferent conditions.The proposed bus travel time reliability metric is tested to be sensitive to the efect of diferent factors and can be applied in bus route recommendation,bus service evaluation,and optimization.

Bus transit travel time reliability evaluation based on automatic vehicle location data

In order to provide important parameters for schedule designing, decision-making bases for transit operation management and references for passengers traveling by bus, bus transit travel time reliability is analyzed and evaluated based on automatic vehicle location （AVL） data. Based on the statistical analysis of the bus transit travel time, six indices including the coefficient of variance, the width of travel time distribution, the mean commercial speed, the congestion frequency, the planning time index and the buffer time index are proposed. Moreover, a framework for evaluating bus transit travel time reliability is constructed. Finally, a case study on a certain bus route in Suzhou is conducted. Results show that the proposed evaluation index system is simple and intuitive, and it can effectively reflect the efficiency and stability of bus operations. And a distinguishing feature of bus transit travel time reliability is the temporal pattern. It varies across different time periods.