Author(s)

M. Mesbah, M. Luy, G. Currie

Abstract

Travel time reliability is affected by a range of factors including traffic demand, road infrastructure, accidents, and weather. Although the effect of weather conditions on travel time reliability has been extensively studied, the majority of studies focus on the weather parameters during a trip. However, passengers may decide on their trip attribute (e.g. trip start time and travel mode) based on the weather conditions before the trip. Alternatively, passengers may decide based on weather predictions for the entire day and not just the weather during the morning travel. This paper aims to explore the effect of weather parameters with a lead (before starting a trip) or a lag (after an urban trip is completed). For this purpose Automatic Vehicle Location (AVL) data in Melbourne, Australia was used. This large dataset included all tram movements for more than ten routes in a period of five years during the morning peak. The results indicate that precipitation (rainfall) is the most important weather parameter to affect travel time reliability and precipitation during the trip is the most significant period followed by the rain during the last hour of the morning peak. This suggests that considering a lag in weather parameters may increase the accuracy of travel time reliability estimations.

Keywords

transit reliability, rain, big data