Enhancing Freeway Traffic Capacity: The Impact of Autonomous Vehicle Platooning Intensity

被引:0
作者
Chang, Qing [1 ]
Chen, Hong [1 ]
机构
[1] Changan Univ, Sch Transportat Engn, Xian 710064, Peoples R China
来源
APPLIED SCIENCES-BASEL | 2024年 / 14卷 / 04期
关键词
platooning intensity; heterogeneous traffic; automated vehicles; microscopic traffic flow modeling; market penetration rate; ADAPTIVE CRUISE CONTROL; AUTOMATED VEHICLES; SIMULATION FRAMEWORK; FUNDAMENTAL DIAGRAM; CONNECTED VEHICLES; LANE MANAGEMENT; FLOW; MODEL; THROUGHPUT; STABILITY;
D O I
10.3390/app14041362
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
This paper proposes a theoretical model to discuss the capacity of heterogeneous saturated flow. A crucial indicator, platooning intensity, which represents the willingness of connected and autonomous vehicles to form platoons, is taken into consideration. The relationship between platooning intensity and the penetration rate of connected and autonomous vehicles is also evaluated. Numerical analysis is conducted based on relevant parameters, which further improves the proposed theoretical model. Finally, a microscopic simulation is used to verify the accuracy of the proposed model. The results indicate that both the speed and the market penetration rate have a significant impact on capacity; however, the impact is not linear. The slope of the speed-affected curve gradually decreases, whereas the slope of the market penetration rate-affected curve gradually increases. The impact of market penetration rate on theoretical capacity intensifies with the increase in speed. As the number of vehicles within a fleet increase, the weighted average of platooning intensity gradually tends towards the market penetration rate. The formulation offers important insights into traffic performance with heterogeneous flow.
引用
收藏
页数:17
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共 48 条
[1]   Network Fundamental Diagram (NFD) and traffic signal control: first empirical evidences from the city of Santander [J].
Alonso, Borja ;
Ibeas Portilla, Angel ;
Musolino, Giuseppe ;
Rindone, Corrado ;
Vitetta, Antonino .
20TH EURO WORKING GROUP ON TRANSPORTATION MEETING, EWGT 2017, 2017, 27 :27-34
[2]  
Altay I, 2013, Int. J. Veh. Technol, V2013, P749896, DOI [10.1155/2013/749896, DOI 10.1155/2013/749896]
[3]   Traffic automation and lane management for communicant, autonomous, and human-driven vehicles [J].
Amirgholy, Mahyar ;
Shahabi, Mehrdad ;
Gao, H. Oliver .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2020, 111 (111) :477-495
[4]  
[Anonymous], 2022, Highway Capacity Manual 7th Edition: A Guide for Multimodal Mobility Analysis, DOI DOI 10.17226/26432
[5]   Exploring the effects of cooperative adaptive cruise control on highway traffic flow using microscopic traffic simulation [J].
Arnaout, Georges M. ;
Arnaout, Jean-Paul .
TRANSPORTATION PLANNING AND TECHNOLOGY, 2014, 37 (02) :186-199
[6]   Development and testing of a fully Adaptive Cruise Control system [J].
Bifulco, Gennaro Nicola ;
Pariota, Luigi ;
Simonelli, Fulvio ;
Di Pace, Roberta .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2013, 29 :156-170
[7]  
Calvert SC, 2012, 2012 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV), P861, DOI 10.1109/IVS.2012.6232138
[8]   Towards vehicle automation: Roadway capacity formulation for traffic mixed with regular and automated vehicles [J].
Chen, Danjue ;
Ahn, Soyoung ;
Chitturi, Madhav ;
Noyce, David A. .
TRANSPORTATION RESEARCH PART B-METHODOLOGICAL, 2017, 100 :196-221
[9]   Highway traffic state estimation with mixed connected and conventional vehicles: Microscopic simulation-based testing [J].
Fountoulakis, Markos ;
Bekiaris-Liberis, Nikolaos ;
Roncoli, Claudio ;
Papamichail, Ioannis ;
Papageorgiou, Markos .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2017, 78 :13-33
[10]   A mixed traffic speed harmonization model with connected autonomous vehicles [J].
Ghiasi, Amir ;
Li, Xiaopeng ;
Ma, Jiaqi .
TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2019, 104 :210-233