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.

Evaluation method on bus arrival headway reliability

To accurately capture the measurement of bus reliability and evaluate whether the transit system is properly operated an evaluation framework is established to assess the reliability of the transit system from different stratifications including stops routes and network levels.The bus operation data of the Hefei city is analyzed as a case study.Comparison is conducted to show the improvement made by using the advanced method and an example of adding exclusive bus lanes to the existing bus route is provided. The proposed advanced method can avoid the shortcomings of the traditional method.For example the value of the reliability using the traditional coefficient of variation CV is not between 0 and 1 and the value of reliability can decrease with the increase in the transit headway etc. The case study shows that the advanced method can represent the real operation condition of the transit system and can be used to evaluate the transit headway reliability more reasonably.

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.