FREIGHT-SIGNIFICANT SITE MONITORING USING
This Thesis presents a simulation-based evaluation study for link speed estimation using Bluetooth and RFID combined detection system. Freight-significant sites refer to roadway sections with high freight flow. Previous studies on freight traffic performance monitoring are generally based on data collected using GPS devices installed on freight vehicles. The exclusive freight traffic data do not have sufficient information for analyzing the condition of the general traffic system. The issue which should be considered is that vehicles of different classes should not be independent from complete traffic system. The isolated data source may neglect the factors that activate traffic problems. The insufficient freight data collection and freight performance measures efforts make researches on freight-specific studies necessary. In this study, we investigate the feasibility of using Automatic Vehicle Identification (AVI) technologies (i.e. Bluetooth and Radio-Frequency Identification (RFID) technology) to automatically collect data from freight vehicles and the general traffic. The innovation points and contribution are 1) new detection system architecture is developed for collecting all-vehicle traffic data and freight-specific data simultaneously; 2) the concept of speed estimation unit and methodology are defined; 3) an evaluation analysis under simulation situation close to the real field condition is provided; 4) some future works are foreseen that can make the propose system work better in real-time traffic monitoring at freight-significant freeway sections. A VISSIM-based simulation model is developed as a test bed to evaluate the Bluetooth-RFID combined system in collecting data to measure segment average speed in a short range. The traffic flow data used to calibrate the VISSIM model comes from the 5-min loop detector data collected on I-94 freeway in the urban area of Milwaukee, WI, USA. Heavy vehicle percentages are determined using 3-min CCTV traffic snapshots. The simulation results indicate that the innovative AVI-based system can be promising in freight performance monitoring.