Speed-guided intelligent transportation system helps achieve low-carbon and green traffic: Evidence from real-world measurements

摘要

Intelligent transportation systems (ITS) have emerged as essential measures to manage traffic congestion and to reduce vehicular emission and energy consumption, while their effectiveness has not been directly quantified under real-world driving conditions. By conducting real-world driving and emission measurements with a portable emission measurement system, we found that the usage of the speed guided-ITS (SG-ITS) significantly reduces fuel consumption and pollutant emissions (i.e., carbon monoxide, nitrogen monoxide, nitrogen dioxide, and particle number) of both tested vehicles (a light-duty gasoline car and a heavy-duty diesel truck) through decreasing the frequency of starts and stops, the strength of acceleration, and the time proportions of acceleration and idle. These reductions obtained from real-world measurements are higher than those predicted by vehicle emission models such as Motor Vehicle Emission Simulator (MOVES) and Computer Programme to calculate Emissions from Road Transport (COPERT). Reductions in fuel consumption and pollutant emissions due to the usage of the SG ITS are most efficient on urban roads (low traffic) among all the three road types, while the most time saving can be obtained on urban roads (high traffic). By combining a high-resolution vehicle emission inventory, we estimate that the implementation of the SG-ITS may significantly reduce the total vehicular exhaust emissions of nitrogen oxides, carbon monoxide, total hydrocarbons, and particulate matter in Beijing by 15.9%, 20.5%, 23.9%, and 22.5%, respectively. Our study directly evaluates the benefits of using SG-ITS based on real-world measurements, highlighting that implementation of the SG-ITS can be a practical policy option in terms of efficiently reducing energy consumption, mitigating urban air pollution, and alleviating urban traffic congestion. (C) 2020 Elsevier Ltd. All rights reserved.