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.

Optimization of urban bus operation frequency under common route condition with rail transit

The overlap of bus and rail transit routes is common in China. This overlap provides passengers multiple choices for one trip. However, the availability of multiple options would cause uncertainty in the travel distribution of passengers. Given that buses and rail transits are becoming increasingly common, this paper aims to present the overlapped operation condition of bus and rail transit using a bi-level model from the perspective of bus operators. Frequency optimization model is established in the upper-level model. A heuristic algorithm called shuffled complex evolution(SCE-UA) method is used to solve the established frequency optimization model, and three other heuristic methods are compared with SCE-UA. A lower-level Logit model based on Agent simulation is set for traffic mode split. Data on the transit system in Dalian city are chosen as an example to test the feasibility of the model and the algorithm. Results show that as the overlapped optimization of bus route and rail transit routes changed primary bus frequency, the use of SCE-UA to solve such problems has evident advantages and feasibility; furthermore, changed bus frequency would improve bus operations.