The DOI matches its Crossref record; 153 of the 155 references it cites were found in a registry or an index.
A Survey on Cooperative Longitudinal Motion Control of Multiple Connected and Automated Vehicles
Abstract
Connected and automated vehicles (CAVs) have the potential to address a number of safety, mobility, and sustainability issues of our current transportation systems. Cooperative longitudinal motion control is one of the key CAV technologies that allows vehicles to be driven in a cooperative manner to achieve system-wide benefits. In this paper, we provide a literature survey on the progress accomplished by researchers worldwide regarding cooperative longitudinal motion control systems of multiple CAVs. Specifically, the architecture of various cooperative CAV systems is reviewed to answerhow cooperative longitudinal motion control can workwith the help of multiple system modules. Next, different operational concepts of cooperative longitudinal motion control applications are reviewed to answerwhere they can be implemented in today’s transportation systems. Different cooperative longitudinal motion control methodologies and their major characteristics are then described to answerwhat the critical design issues are. This paper concludes by describing an overall landscape of cooperative longitudinal motion control of CAVs, as well as pointing out opportunities and challenges in the future research and experimental implementations.
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“For motion control in the ICV, communication technologies utilized to help enhance the sensing range may bring various problems due to switching information flow topologies and the time delay.”
From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [35]
In the citing paper
“The nonlinear and heterogeneous nature of vehicle dynamics and the uncertain reliability of wireless communication links require careful design of CAV controllers to mitigate the impact of feedback channels and ensure string stability in CACC strings [35].”
From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [35]
In the citing paper
“Meanwhile, the internal stability of a Cooperative Adaptive Cruise Control (CACC) system does not automatically guarantee string stability.If error signals are amplified upstream despite the closed-loop system's internal stability, it can lead to collisions among consecutive vehicles.”
From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [35]
In the citing paper
“Moreover, in terms of heterogeneous dynamics, the assumption of homogeneity among vehicles is not realistic due to the wide range of models, types, and powertrain component variations.”
From Vehicle-to-Everything Communication in Intelligent Connected Vehicles: A Survey and Taxonomy (2025) · cites this paper as [35]
Citations
Cites
A Review of Motion Planning Techniques for Automated Vehicles
Gonzalez, D., Perez, J., Milanes, V., & Nashashibi, F. (2016) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2498841 · Cited by 1,670
The Impact of Cooperative Adaptive Cruise Control on Traffic-Flow Characteristics
van Arem, B., Driel, C. J. G. V., & Visser, R. (2006) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2006.884615 · Cited by 1,548
A Multiagent Approach to Autonomous Intersection Management
Dresner, K., & Stone, P. (2008) · Journal of Artificial Intelligence Research · doi:10.1613/jair.2502 · Cited by 1,372
String stability of interconnected systems
Swaroop, D., & Hedrick, J. K. (1996) · IEEE Transactions on Automatic Control · doi:10.1109/9.486636 · Cited by 1,235
Cooperative Adaptive Cruise Control in Real Traffic Situations
Milanés, V., Shladover, S. E., Spring, J., Nowakowski, C., Kawazoe, H., & Nakamura, M. (2013) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2013.2278494 · Cited by 1,133
Self-citationMilanés, V., & Shladover, S. E. (2014) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2014.09.001 · Cited by 1,110
Self-citationString-Stable CACC Design and Experimental Validation: A Frequency-Domain Approach
Naus, G. J. L., Vugts, R. P. A., Ploeg, J., van de Molengraft, R., & Steinbuch, M. (2010) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2010.2076320 · Cited by 919
Rios-Torres, J., & Malikopoulos, A. A. (2016) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2016.2600504 · Cited by 798
Zheng, Y., Li, S. E., Wang, J., Cao, D., & Li, K. (2015) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2015.2402153 · Cited by 782
Self-citationA Survey on Platoon-Based Vehicular Cyber-Physical Systems
Jia, D., Lu, K., Wang, J., Zhang, X., & Shen, X. (2015) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2015.2410831 · Cited by 778
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Cited by
Sorted by citations
Mobility Digital Twin: Concept, Architecture, Case Study, and Future Challenges
Wang, Z.-R., Gupta, R., Han, K., Wang, H., Ganlath, A., Ammar, N., & Tiwari, P. (2022) · IEEE Internet of Things Journal · doi:10.1109/jiot.2022.3156028 · Cited by 285
Self-citationA Survey on Multimodal Large Language Models for Autonomous Driving
Cui, C., Ma, Y., Cao, X., Ye, W., Zhou, Y., Liang, K., Chen, J., Lu, J., Yang, Z., Liao, K.-D., et al. (2024) · 2024 IEEE/CVF Winter Conference on Applications of Computer Vision Workshops (WACVW) · doi:10.1109/wacvw60836.2024.00106 · Cited by 369
Self-citationChellapandi, V. P., Yuan, L., Brinton, C. G., Żak, S. H., & Wang, Z. (2023) · IEEE Transactions on Intelligent Vehicles · doi:10.1109/tiv.2023.3332675 · Cited by 271
Self-citationYu, H., Jiang, R., He, Z., Zheng, Z., Li, L., Liu, R., & Chen, X. M. (2021) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2021.103101 · Cited by 225
A Systematic Survey of Control Techniques and Applications in Connected and Automated Vehicles
Liu, W., Hua, M., Deng, Z., Meng, Z., Huang, Y., Hu, C., Song, S., Gao, L., Liu, C., Shuai, B., et al. (2023) · IEEE Internet of Things Journal · doi:10.1109/jiot.2023.3307002 · Cited by 188
Metadata
- Authors
- Wang, Z., Bian, Y., Shladover, S. E., Wu, G., Li, S. E., & Barth, M. J.
- Affiliations
- University of California, Riverside (US)
- Tsinghua University (CN)
- University of California, Berkeley (US)
- Venue
- IEEE Intelligent Transportation Systems Magazine
- Published
- 2020
- Volume
- 12
- Issue
- 1
- Pages
- 4-24
- ISSN
- 1939-1390 (ISSN-L)
- 1941-1197
- OpenAlex
- W2996811802
- Cited by
- 316
- References
- 155
- Citations by year
- 2026: 12 · 2025: 43 · 2024: 55 · 2023: 82 · 2022: 61 · 2021: 47 · 2020: 16
- FWCI
- 17.31
- Type
- journal article
- Language
- en
- Open access
- closed
- Licence
- Locations
- IEEE Intelligent Transportation Systems Magazine (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Traffic control and management
- Physical Sciences › Engineering › Automotive Engineering › Vehicle Dynamics and Control Systems
- Physical Sciences › Engineering › Control and Systems Engineering › Distributed Control Multi-Agent Systems
- Keywords
- connected and automated vehicles, cooperative driving, vehicle-to-vehicle communication, vehicle-to-infrastructure communication, vehicle platooning
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