Revisiting Left-Turn Waiting Areas: Optimizing Left-Turn Signal Timing to Eliminate Twice Startup, Reduce Emissions, and Improve Traffic Efficiency

被引:0
作者
Shao, Yang [1 ]
Hou, Tianyue [1 ]
Sun, Ruifen [1 ]
Cheng, Yuzhu [1 ]
Fan, Yuehua [1 ]
Hu, Xinni [1 ]
Pan, Binghong [2 ]
机构
[1] Xian Univ Posts & Telecommun, Sch Modern Post, Xian 710061, Peoples R China
[2] Changan Univ, Sch Highway, Xian 710061, Peoples R China
来源
IEEE ACCESS | 2024年 / 12卷
关键词
Automobiles; Entropy; Fuels; Optimization methods; Air pollution; Exhaust gases; Urban areas; Public transportation; Carbon emissions; Environmental measurement; Road traffic control; Traffic control; Exhaust emission; air pollution; traffic efficiency; city transportation; entropy weight method; CARBON EMISSIONS; FUEL CONSUMPTION; INTERSECTIONS; CHINA; MODEL; OPTIMIZATION; PERFORMANCE; CAPACITY; DESIGN; IMPACT;
D O I
10.1109/ACCESS.2024.3453375
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Reducing urban transportation carbon emissions is a fashionable task around the globe. Electric cars, fuel cell cars, hydrogen cars, restriction policies, etc. are all aimed at this goal. But they are all expensive to make them into reality. Transportation management can also provide some contribution to this, like optimizing operation rules such as Left-turn Waiting Area Twice Startup. From the stop line to the Left-turn Waiting Area (LWA), one vehicle will start twice with more emissions due to the engine's inefficient operating range. We proposed an Accurate Left-turn One-time Startup Model (ALOSM) based on the LWA rule, which includes the intersection geometry parameters, traffic light timing schemes, vehicle start speeds, vehicle operation speeds, and fuel vehicle ratios. Make the Left-turn Vehicle (LV) waiting behind the stop line during the through vehicle light green. Calculate the left-turn green light adjustment duration and make the LV and the last through vehicle across at one moment. With real collected data in a symbolic intersection in Xi'an, China, the simulation result shows vehicle emission would be reduced by 13% and traffic efficiency would increase by 5% in this single intersection. The whole city of 5 million vehicles would reduce 2,087.88 kg CO emission in one day due to estimation.
引用
收藏
页码:127086 / 127099
页数:14
相关论文
共 55 条
[51]   Traffic Efficiency Applications over Downtown Roads: A New Challenge for Intelligent Connected Vehicles [J].
Younes, Maram Bani ;
Boukerche, Azzedine .
ACM COMPUTING SURVEYS, 2020, 53 (05)
[52]   Historic and future trends of vehicle emissions in Beijing, 1998-2020: A policy assessment for the most stringent vehicle emission control program in China [J].
Zhang, Shaojun ;
Wu, Ye ;
Wu, Xiaomeng ;
Li, Mengliang ;
Ge, Yunshan ;
Liang, Bin ;
Xu, Yueyun ;
Zhou, Yu ;
Liu, Huan ;
Fu, Lixin ;
Hao, Jiming .
ATMOSPHERIC ENVIRONMENT, 2014, 89 :216-229
[53]   Is it time to tackle PM2.5 air pollutions in China from biomass-burning emissions? [J].
Zhang, Yan-Lin ;
Cao, Fang .
ENVIRONMENTAL POLLUTION, 2015, 202 :217-219
[54]   Signal control for overflow prevention at intersections using partial connected vehicle data [J].
Zhao, Jing ;
Yao, Tianyu ;
Zhang, Cheng ;
Shafique, Muhammad Awais .
TRANSPORTMETRICA A-TRANSPORT SCIENCE, 2024,
[55]   Evaluating traffic emission control policies based on large-scale and real-time data: A case study in central China [J].
Zou, Chao ;
Wu, Lin ;
Wang, Yanan ;
Sun, Shida ;
Wei, Ning ;
Sun, Bin ;
Ni, Jingwei ;
He, Jing ;
Zhang, Qijun ;
Peng, Jianfei ;
Mao, Hongjun .
SCIENCE OF THE TOTAL ENVIRONMENT, 2023, 860