Journey time estimation and incident detection using GPS equipped probe vehicle

This thesis presents a study of the use of GPS equipped probe vehicle to collect traffic data on a motorway network. The performance of the GPS information in journey time estimation has been studied by comparing the results against video camera data and the various factors affecting estimation accuracy have been discussed. By discontinuing the use of Selective Availability, one of the main error sources of GPS, current positioning accuracy without Differential GPS is sufficient for journey time estimation. Two types of GPS equipped probe vehicles, active and passive, have been studied. A passive probe vehicle was considered to provide only link journey time and a minimum number of probe vehicles is required for reliable estimation. This research has studied the distribution of individual journey times and calculated the sample size of probe vehicles required in different traffic conditions. The sample size has shown to be generally stable for the same link, but may decrease in heavier traffic. The use of real-time estimates of journey time by probe vehicles has been studied for incident detection and journey time prediction. Link journey times at current time intervals and the differences in journey times between two adjacent time intervals have been shown to be bivariate-normally distributed in incident-free traffic. Outliers of the distribution were considered to be observed in incident traffic. A bivariate model has been developed for incident detection and a satisfactory detection and false alarm rates have been achieved. Journey tunes were predicted based on current observations and historic data for incident and incident-free conditions. An active probe vehicle was found to be able to determine vehicle position and speed at 1 Hz frequency over an entire journey. By analysing the speed profile of probe vehicles, journey times can be estimated from fewer probe vehicles than normally required. In this research, a fuzzy model was developed to analysis speed profiles, and journey time could be estimated using a single probe vehicle. Satisfactory estimates were obtained in both non-incident and incident conditions. Combinations of average speed and deceleration rates were used for incident detection.