Approach to Real-Time Commercial Vehicle Monitoring

Vehicle classification algorithms allocate vehicles to predefined classes based on selected vehicle characteristics. Such algorithms have many important applications in transportation systems analysis and policy development, including travel forecasting, goods movement studies, road design and maintenance, setting user fees, safety studies, traffic flow modeling, environmental impact analysis, traffic management and automated toll collection. This research will collect a large and unique dataset of commercial vehicle (CV) signatures using conventional inductive loops and a new wireless sensor with potential for cost-effective and widespread use. The data will be used to develop detailed and accurate vehicle classification algorithms for CVs, and will provide important insights into the strengths and limitations of a new wireless traffic sensor.