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 time delay.
“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]
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.
“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]
The internal stability of a Cooperative Adaptive Cruise Control system does not automatically guarantee string stability, and if error signals are amplified upstream despite internal stability, it can lead to collisions among consecutive vehicles.
“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]
The assumption of homogeneity among vehicles is not realistic due to the wide range of models, types, and powertrain component variations.
“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]
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Self-citationDistributed Consensus-Based Cooperative Highway On-Ramp Merging Using V2X Communications
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Self-citationCooperative Ramp Merging System: Agent-Based Modeling and Simulation Using Game Engine
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Self-citationOperational Concepts for Truck Maneuvers with Cooperative Adaptive Cruise Control
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Self-citationReducing Time Headway for Platoons of Connected Vehicles via Multiple-Predecessor Following
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Self-citationAUTOPIA architecture for automatic driving and maneuvering
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Mobility Digital Twin: Concept, Architecture, Case Study, and Future Challenges
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Self-citationReceive, Reason, and React: Drive as You Say, With Large Language Models in Autonomous Vehicles
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Self-citationScalable and Resilient Platooning Control of Cooperative Automated Vehicles
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Self-citationDriver Digital Twin for Online Prediction of Personalized Lane-Change Behavior
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Disturbance Observer-Based Cooperative Control of Vehicle Platoons Subject to Mismatched Disturbance
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Self-citationImpact of CAV platoon management on traffic flow considering degradation of control mode
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Self-citationA Survey on Integration of Network Communication into Vehicle Real-Time Motion Control
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Self-citationA survey on clustering methods for distributed and networked control systems
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Impacts of Information Flow Topology on Traffic Dynamics of CAV-MV Heterogeneous Flow
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A Review of Vehicle Group Intelligence in a Connected Environment
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Anomaly diagnosis of connected autonomous vehicles: A survey
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Self-citationGaussian Process-Based Personalized Adaptive Cruise Control
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Simulation of mixed traffic with cooperative lane changes
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Platoon Tracking Control With Road-Friction Based Spacing Policy for Nonlinear Vehicles
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Impact of Mixed Traffic on the Energy Savings of a Truck Platoon
McAuliffe, B., Raeesi, A., Lammert, M. P., Smith, P. D., Hoffman, M., & Bevly, D. M. (2020) · SAE International Journal of Advances and Current Practices in Mobility · doi:10.4271/2020-01-0679 · Cited by 40 · see citing works
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Exploring Shared Perception and Control in Cooperative Vehicle-Intersection Systems: A Review
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Self-citationReview of Decision-Making and Planning Approaches in Automated Driving
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Damping behavior analysis for connected automated vehicles with linear car following control
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Adaptive Control with Moving Actuators at Motorway Bottlenecks with Connected and Automated Vehicles
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Vehicle Platoon Control Based on Third-Order Heterogeneous Model and Predictive Spacing Strategy
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Behavioral Harmonization of a Cyclic Vehicular Platoon in a Closed Road Network
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Self-citationA Coevolutionary Algorithm for Cooperative Platoon Formation of Connected and Automated Vehicles
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A Learning Control Method of Automated Vehicle Platoon at Straight Path with DDPG-Based PID
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Augmented Reality-Based Advanced Driver-Assistance System for Connected Vehicles
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Self-citationAutomatic Lane-Changing Trajectory Planning: From Self-Optimum to Local-Optimum
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Collaborative Control of Vehicle Platoon Based on Deep Reinforcement Learning
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Centralized Model Predictive Control With Human-Driver Interaction for Platooning
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Nonlinear spacing policies for vehicle platoons: A geometric approach to decentralized control
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DMPC-based string stable platoon control with robustness against communication delays
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Self-citationSecure Cooperative Localization for Connected Automated Vehicles Based on Consensus
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Self-citationCan Connected Autonomous Vehicles really improve mixed traffic efficiency in realistic scenarios?
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Online Prediction of Lane Change with a Hierarchical Learning-Based Approach
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Self-citationResilient Virtual Coupling Control of Automatic Train Convoys With Intermittent Communications
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Secure virtual coupling control of connected train platoons under cyber attacks
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Cooperative Adaptive Cruise Control With Unconnected Vehicle in the Loop
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Self-citationA Robust Mpc Approach for Platooning Control of Automated Vehicles with Constraints on Acceleration
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- 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 › Computer Science › Computer Networks and Communications › 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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