Estimation of Influence Distance of Bus Stops Using Bus GPS Data and Bus Stop Properties

In congested cities where commuting time doubles during peak hours, it is crucial to identify every network problem. Here, it is aimed to analyze the traffic behavior of the buses around the bus stops and to show the effects of the surrounding network to speedup the pattern of buses using the trajectory data of Global Positioning System (GPS)-equipped bus fleet. As an indicator of speed differences near bus stops, influence distance is suggested, wherein the speed of buses significantly changes while approaching and leaving the bus stops. Speed patterns of buses operating on 12 bus routes in Istanbul are analyzed. The data include more than 5000 daily trajectory log files and 25 million rows of location and time information during April 2016. The influence distance, measured using the fused lasso method, for the 438 bus stops varies from 36 to 174m, with an average value of 98m. In the second part of this paper, correlation of the influence distances of the bus stops with the surrounding interruptions is investigated. A distance matrix of surrounding interruptions to the nearest bus stop is generated. This matrix is used as parameters of M5 Prime, random forest, and extremely randomized trees models in order to predict the influence distances. The models show that the passenger demand plays a key role in the influence distances of the bus stops. It is also found that the changes in the number of lanes and the location of the traffic lights are quite effective on the influence distances.