Traffic-flow characterization to quantify the real world driving profile
Abstract
Most urgent transport related problems in India are traffic congestion and concomitant air pollutant emissions. The common causes of congestion in urban centers are pedestrian interruption, unregulated traffic signals, unregulated bus stoppages and unauthorized roadside parking, which together, particularly during peak hours create erratic traffic pattern causing higher emissions. This study characterized real world traffic-flow, particularly flow patterns during peak hours by using instantaneous speed, traffic count and volume during different hours of the day. Traffic speed is important factor that is perceived by commuters. Therefore, speed variables and traffic volume are used as a base variable to examine real world traffic-flow patterns. The speed variables such as average speed (AS), velocity noise (VN, standard deviation of speed), and the coefficient of variation of speed (CV) were examined with respect to traffic volume. The polynomial fit of CV shows three distinct zones of variations with increasing traffic volume, explaining the dynamics of traffic-flow patterns, e.g. start-up phase and stop-and-go, a characteristic of urban peak traffic-flow. The variation of speed defines three different threshold levels with increasing traffic volume. The adopted method is simple and also based on simple measurable parameters. The results provide real-time information of traffic-flow patterns, which may be useful for the public and transport related agencies.
