EconPapers    
Economics at your fingertips  
 

A Cooperative Merging Control Method for Freeway Ramps in Connected and Autonomous Driving

Jiaxin Wu, Yibing Wang, Zhao Zhang, Yiqing Wen, Liangxia Zhong and Pengjun Zheng ()
Additional contact information
Jiaxin Wu: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
Yibing Wang: Institute of Intelligent Transportation Systems, Zhejiang University, Hangzhou 310058, China
Zhao Zhang: School of Transportation Science and Engineering, Beihang University, Beijing 100191, China
Yiqing Wen: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
Liangxia Zhong: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China
Pengjun Zheng: Faculty of Maritime and Transportation, Ningbo University, Ningbo 315832, China

Sustainability, 2022, vol. 14, issue 18, 1-20

Abstract: The highway on-ramp merging area is one of the major sections that form traffic bottlenecks. In a connected vehicle environment, V2V and V2I technologies enable real-time exchange of information, including position, speed, and acceleration. To improve the efficiency of vehicle merging at the on-ramp, this study proposes a cooperative merging control strategy for network-connected autonomous vehicles. First, the central controller designs the merging sequence and safety space for vehicles passing through the confluence point. Then, a trajectory optimization model was constructed based on vehicle longitudinal dynamics, and the PMP algorithm was used to determine the optimal control input. Finally, all vehicles follow the optimal trajectory so that the ramp vehicles merge smoothly into the mainline. Simulations verify that the proposed algorithm performs better than FIFO, with 13.2% energy savings, 41.4% increase in average speed, and 50.4% reduction in travel time over the uncontrolled merging scenario. The method is further applied to different traffic flow conditions and the results show that it can significantly improve traffic safety and mobility, while effectively reducing vehicle energy consumption. However, the traffic operation improvement is not satisfactory under low traffic demand.

Keywords: connected and automated vehicles; ramp merging control; optimal control; NGSIM (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2071-1050/14/18/11120/pdf (application/pdf)
https://www.mdpi.com/2071-1050/14/18/11120/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:14:y:2022:i:18:p:11120-:d:907624

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jsusta:v:14:y:2022:i:18:p:11120-:d:907624