En-route headway-based bus reliability with real-time data at network scale

Bus reliability has long attracted attention and been extensively studied to enhance service quality.However,existing research generally evaluates bus reliability of specific routes or stops.To this end,this study explores en-route bus reliability with real-time data at network scale.Drawing on data of bus automatic vehicle location and smart card usage in Ningbo,China,this study calculates headway-based reliability with the difference between actual and scheduled headway at each stop.To demonstrate the trend of stop-level reliability along a bus route,reliability is graded and visualized on a map with ridership at each stop,which is then weighted with passenger-boarding volume.Route-level reliability is then quantified and mapped,where unreliable service basically concentrates in or extends through the centre area.With respect to network-level reliability,temporal changes are demonstrated with ridership on weekdays and at the weekend.It is observed that on weekdays,the reliability trend is similar to that of ridership,implying a causal relationship between bus travel-time variation and bus waiting-time at stops.Furthermore,a reliability comparison between weekdays in December and October shows the necessity of evaluating periodically and around important events to avoid negative riding experiences that discourage public transport usage.This research provides insights for bus agencies to systematically evaluate service reliability both spatially and temporarily,in order to identify and prioritize the routes and stops where the scope for reliability improvement and the expected benefit are greatest.

Optimization of transit total bus stop time models

Several factors influence bus transit reliability which includes bus stop conditions along the route, traffic conditions, route of travel and time of day. The overall transit bus reli- ability is generally affected by dwell time （DT）, the fare payment method, the bus stop location, and the number of passengers alighting or boarding. A new variable is defined in this study, total bus stop time （TBST）, which is the summation of DT and the time it takes a bus to effectively park at a bus stop and the re-entering the traffic stream. It is suggested that the overall bus transit reliability along routes could be improved if the TBST is mini- mized at bus stops. In this study, TBST models for bus stops located at mid-blocks and near intersections were developed based on multivariate regression analysis using ordinary least squares method. Data collection was conducted at 60 bus stops, 30 of which were near intersections and 30 at mid-blocks, in Washington DC during morning, mid-day and evening peak hours. The variables observed at each bus stop are as follows： number of passengers alighting or boarding, DT, TBST, bus stop type, bus pad, length number of lanes on approach to the bus stop, and permitted parking. Statistical inferences were based on 5% level of significance. From the results, it was inferred that the new variable, TBST, could potentially be used to improve scheduling and transit bus systems planning in a dense urban area.