Author: Nan Zou
Type: Ph. D. Dissertation
Abstract: Due to the increasing congestion in most urban networks, providing reliable trip times to commuters has emerged as one of the most critical challenges for all existing Advanced Traffic Information Systems (ATIS). However, predicting travel time is a very complex and difficult task, as the resulting accuracy varies with many variables of time-varying nature, including the day-to-day traffic demands, responses of individual drivers to daily commuting congestion, conditions of the road facility, weather, incidents, and reliability of available detectors. This study aims to develop a travel time prediction system that needs only a small number of reliable traffic detectors to perform accurate real-time travel time predictions under recurrent traffic conditions. To ensure its effectiveness, the proposed system consists of three principle modules: travel time estimation module, travel time prediction module, and the missing data estimation module.