Real world driving dynamics characterization and identification of emission rate magnifying factors for auto-rickshaw

Abstract

Most urgent transport related problems in India are traffic congestion and concomitant air pollutant emissions. During traffic flow, the common causes of congestion in urban centres 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. In this study, we characterized auto-rickshaw driving dynamics by instantaneous measurements of speed and emission at different times of the day. Traffic speed is an important factor that is perceived by commuters. The speed variables and traffic volume are used as a base variable to examine the 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, the ratio of VN and AS) 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. Further, time, speed and mileage variable were investigated for the emission rate analysis in different traffic flow pattern. The analysis depicted that the combined factor of lower speed (speed ≤12 km/h) and higher time of travel in correspondence cause higher emission rate. Similarly, vehicle mileage of ≥52, 000 km has significant impact on emission for pollutants CO, HC and NOx. The results provide real-time information on traffic flow characteristics and impacts of dynamic and age variables on emission rate in on-road driving condition, which may be useful for the public and transport related agencies. © 2020 Technoscience Publications. All rights reserved.