Developing Operating Mode Distribution Inputs for MOVES with a Computer Vision–Based Vehicle Data Collector

Abstract

Acquisition of reliable vehicle activity inputs to the U.S. Environmental Protection Agency's MOVES (Motor Vehicle Emission Simulator) model is necessary for maximizing modeling capacity and helping federal and state officials improve the quality of transportation management. For this purpose, rapid and low-cost collection of the operating mode distribution and other traffic activity data for the MOVES model is necessary. In this study, a computer vision–based software tool, Rapid Traffic Emission and Energy Consumption Analysis (REMCAN), is developed to enable a rapid operating mode distribution profiling for the MOVES model. The video-based system provides traffic activity inputs, including vehicle speeds and acceleration and deceleration rates covering the entire vehicle fleet; these may be difficult to extract from traffic data collected by traditional methods. The REMCAN system architecture and vehicle parameter extraction methods are presented. The speed measurement, which is the most critical factor for operating mode profiling, is calibrated with a coefficient that converts screen space to real-world space. Three case studies with different traffic operation scenarios are tested to demonstrate the capability of the REMCAN system. The integration of REMCAN traffic activity data collection and MOVES operating mode distribution generation provides timely, low-cost, and accurate environmental impact assessment compared with traditional data sources for emission estimation analysis.