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Title: | The Impact of Three Specific Collaborative Merging Strategies on Traffic Flow | Authors: | SHANG, Xuecheng LIU, Feng Li, Xin-Gang JANSSENS, Davy WETS, Geert |
Editors: | Naranjo, Jose E. | Issue Date: | 2023 | Publisher: | WILEY-HINDAWI | Source: | JOURNAL OF ADVANCED TRANSPORTATION, 2023 (Art N° 1375867) | Abstract: | On-ramps are considered to be one of the common traffic bottlenecks. In order to improve the operation efficiency of on-ramps, scholars worldwide have proposed various vehicle merging strategies. In this study, we designed different rules to express three collaborative strategies and studied their impact on on-ramp systems. Cellular automata models were used to simulate the systems under different situations, and the average speed and traffic flow rate of both the main roads and ramps were analyzed. The results show that (1) all the three merging strategies give excessive "priority" to the merging vehicle, leading to a severe reduction in the traffic performance of the main road; (2) nevertheless, these strategies have different effects on the entire system with a one-lane or two-lane main road. Due to the lane-changing behavior, the system with a two-lane main road has more advantages than that featured with a one-lane road, making the former system performing better than the latter under the same strategies; (3) the vehicles on the ramp and main road affect each other, and as the vehicle entering probabilities become large, the traffic flow rate on the main road decreases whereas that on the ramp increases. However, the effect is not unlimited, the flow rate on both roads finally reaches a stable level (forming a "platform"); and (4) large values of the merging safety distance parameter decrease the flow rate of the entire system. All the previous results provide a deep understanding of the impact of the three merging strategies on traffic flow, contributing to the design of on-ramp systems that have better operation efficiency and low levels of congestion. | Notes: | Li, XG (corresponding author), Beijing Jiaotong Univ, Key Lab Transport Ind Big Data Applicat Technol Co, Beijing 100044, Peoples R China.; Liu, F (corresponding author), Hasselt Univ, Transportat Res Inst IMOB, Wetenschapspark 5,Bus 6, B-3590 Diepenbeek, Belgium. shangxc@bjtu.edu.cn; feng.liu@uhasselt.be; lixingang@bjtu.edu.cn; davy.janssens@uhasselt.be; geert.wets@uhasselt.be |
Document URI: | http://hdl.handle.net/1942/39526 | ISSN: | 0197-6729 | e-ISSN: | 2042-3195 | DOI: | 10.1155/2023/1375867 | ISI #: | 000919212000001 | Rights: | 2023 Xue-Cheng Shang et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. | Category: | A1 | Type: | Journal Contribution |
Appears in Collections: | Research publications |
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1375867.pdf | Published version | 7.59 MB | Adobe PDF | View/Open |
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