RP and SP Data-Based Travel Time Reliabiality Analysis

Travel time is considered to be the key criterion when making travel related decisions.As the travel decisions are made in a dynamic environment, the travel time also changes according to the real-time operations of the transport system.More and more evidence proves that travellers are not only interested in the expected travel time but also in travel time reliability.Especially for trips that are made regularly, reliability is valued more than travel time itself.This dissertation focuses on travel time reliability measures and their effects on travel related decisions as well as network performance.Travel time is studied both at the aggregate level and the disaggregate level.At the aggregate level, personal preferences of travellers towards travel time are explored; while on the disaggregate level, the network performance is evaluated based on travel time reliability.Instead of defining a new travel time reliability index, the travel time distribution is used to address the variation of the travel time and its influences on both travellers at the micro level and the network at the macro level.Both revealed preference (RP) data and stated preference (SP) data are used for the analysis of the travel time reliability.The SP data provided two scenarios based on mode choice and route choice respectively and the data was collected in Switzerland.Proceeding on the SP data, parts of the RP data is also collected in Switzerland, which is later used to reconstruct the actual route choices of the respondents for a route choice model.Tomtom Stats data is obtained to assist the travel time reliability analysis during the procedure.Another part of the RP data, the floating car data (FCD), was collected from Wuhan, China and it is applied to employ network travel time reliability.Route choice models are built with travel time measures using both SP data and RP data.In the SP data based route choice model, as the travel time distribution was applied to generate the route alternatives, it allows us to explore the early and late indifference buffers around the preferred arrival time.An exhaustive algorithm searches for the optimum early and late buffer combinations and during the procedure, the changes of value of