Assessment of urban traffic vehicle emissions reduction after integration of ‘traffic light countdown’ module in navigation
Assessment of urban traffic vehicle emissions reduction after integration of ‘traffic light countdown’ module in navigation
Blog Article
As China experiences a dramatic surge in carbon emissions from the transportation sector, reducing these emissions has become crucial in mitigating climate change.Since 2020, Navigation Service Providers has collaborated with traffic police departments to integrate the ‘Traffic Light Countdown’ module (TLCM) in the navigation applications in multiple cities across China.This initiative aims to improve vehicle traffic efficiency, reduce transportation carbon emissions, and enhance public driving safety simultaneously.To quantify the effectiveness of this module, we selected a section of Qilu Avenue in Jinan City as a case study.
Localization of Motor My Mom Dad Is Well Trained Funny Cartoon Dog Gift For Dog Lover Personalized Shirt Vehicle Emission Simulator (MOVES) model parameters to accurately reflect the specific conditions of the study area was achieved by incorporating local traffic, climate, vehicle, and fuel information.Utilizing this localized model, we evaluated the changes in traffic conditions, drivers’ driving behavior and running exhaust emissions in the study.The results indicate that, following the integration of the TLCM, the average vehicle speed on the selected road section increased from 29.5 to 31.
8 km h ^−1.Moreover, the ratio of rapid acceleration per vehicle decreased from 0.08 to 0.05, while the rapid deceleration dropped from 0.
04 to 0.01.In terms of carbon emissions, the daily average carbon emissions for this road section decreased by 4.4%, with a particularly significant reduction during the evening rush hours and post-evening rush hours (16:00–22:00 Local Standard Time).
This is the first quantitative assess the potential effect of edgewater shoes the TLCM on improving road traffic conditions and reducing carbon emissions.These findings demonstrate that the integration of TLCM in navigation applications has not only improved traffic efficiency, reduced the occurrence of risky driving behaviors (rapid acceleration and deceleration) and thus enhanced road safety, but also positively contributed to the reduction of carbon emissions from transportation and the mitigation of climate change.