Impacts of Different Types of Automated Vehicles on Traffic Flow Characteristics and Emissions: A Microscopic Traffic Simulation of Different Freeway Segments

被引:17
作者
Beza, Abebe Dress [1 ,2 ]
Zefreh, Mohammad Maghrour [3 ]
Torok, Adam [4 ,5 ]
机构
[1] Bahir Dar Univ, Fac Civil & Water Resources Engn, Bahir Dar Inst Technol, POB 26, Bahir Dar, Ethiopia
[2] Univ Mons, Fac Engn, B-7000 Mons, Belgium
[3] KTH Royal Inst Technol, Div Transport Planning, Brinellvagen 23, SE-10044 Stockholm, Sweden
[4] Budapest Univ Technol & Econ, Dept Transport Technol & Econ, H-1111 Budapest, Hungary
[5] KTI Inst Transport Sci, Dept Transport Policy & Econ, H-1111 Budapest, Hungary
关键词
cooperative automated vehicles; autonomous automated vehicles; microscopic simulation; experimental analysis; traffic flow; traffic emissions; freeway segments; AUTONOMOUS VEHICLES; BEHAVIOR; UNCERTAINTY; STABILITY;
D O I
10.3390/en15186669
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Different types of automated vehicles (AVs) have emerged promptly in recent years, each of which might have different potential impacts on traffic flow and emissions. In this paper, the impacts of autonomous automated vehicles (AAVs) and cooperative automated vehicles (CAVs) on capacity, average traffic speed, average travel time per vehicle, and average delay per vehicle, as well as traffic emissions such as carbon dioxide (CO2), nitrogen oxides (NOx), and particulate matter (PM10) have been investigated through a microsimulation study in VISSIM. Moreover, the moderating effects of different AV market penetration, and different freeway segments on AV's impacts have been studied. The simulation results show that CAVs have a higher impact on capacity improvement regardless of the type of freeway segment. Compared to other scenarios, CAVs at 100% market penetration in basic freeway segments have a greater capacity improvement than AAVs. Furthermore, merging, diverging, and weaving segments showed a moderating effect on capacity improvements, particularly on CAVs' impact, with merging and weaving having the highest moderating effect on CAVs' capacity improvement potential. Taking average delay per vehicle, average traffic speed, and average travel time per vehicle into account, simulation results were diverse across the investigated scenarios. The emission estimation results show that 100% AAV scenarios had the best performance in emission reductions in basic freeway and merging sections, while other scenarios increased emissions in diverging and weaving sections.
引用
收藏
页数:19
相关论文
共 48 条
[1]   Local Climate Action Planning as a Tool to Harness Greenhouse Gas Emissions Mitigation and the Equity Potential of Autonomous Vehicles and On-Demand Mobility [J].
Alexander, Serena ;
Weinstein Agrawal, Asha ;
Clark, Benjamin .
TRANSPORTATION RESEARCH RECORD, 2022, 2676 (03) :521-534
[2]   Investigation of Automated Vehicle Effects on Driver's Behavior and Traffic Performance [J].
Aria, Erfan ;
Olstam, Johan ;
Schwietering, Christoph .
INTERNATIONAL SYMPOSIUM ON ENHANCING HIGHWAY PERFORMANCE (ISEHP), (7TH INTERNATIONAL SYMPOSIUM ON HIGHWAY CAPACITY AND QUALITY OF SERVICE, 3RD INTERNATIONAL SYMPOSIUM ON FREEWAY AND TOLLWAY OPERATIONS), 2016, 15 :761-770
[3]  
Atkins WS., 2016, Stage 2: Traffic Modelling and Analysis Technical Report
[4]   Analysis and Initial Observations on Varying Penetration Rates of Automated Vehicles in Mixed Traffic Flow utilizing SUMO [J].
Berrazouane, Mohamed ;
Tong, Kailin ;
Solmaz, Selim ;
Kiers, Martijn ;
Erhart, Jacqueline .
2019 8TH IEEE INTERNATIONAL CONFERENCE ON CONNECTED VEHICLES AND EXPO (IIEEE CCVE), 2019,
[5]   POTENTIAL EFFECTS OF AUTOMATED VEHICLES ON ROAD TRANSPORTATION: A LITERATURE REVIEW [J].
Beza, Abebe Dress ;
Zefreh, Mohammad Maghrour .
TRANSPORT AND TELECOMMUNICATION JOURNAL, 2019, 20 (03) :269-278
[6]  
Bohm F, 2015, THESIS UPPSALA U UPP
[7]  
Cao WJ, 2013, ASIA CONTROL CONF AS
[8]  
Crisalli U, 2020, TRANSP RES PROCEDIA, V47, P481, DOI [10.1016/j.trpro.2020.03.153, DOI 10.1016/J.TRPRO.2020.03.153]
[9]  
Eijk I.A, 2014, ENVIVER 4 0 PRO ENTE
[10]  
Friedrich B., 2016, AUTONOMOUS DRIVING, P317, DOI [10.1007/978-3-662-48847-816, DOI 10.1007/978-3-662-48847-816]