A Review of Sensing and Communication, Human Factors, and Controller Aspects for Information-Aware Connected and Automated Vehicles
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Abstract (arXiv)
Information-aware connected and automated vehicles (CAVs) have drawn great attention in recent years due to its potentially significant positive impacts on roadway safety and operational efficiency. In this paper, we conduct an in-depth review of three basic and key interrelated aspects of a CAV: sensing and communication technologies, human factors, and information-aware controller design. First, different vehicular sensing and communication technologies and their protocol stacks, to provide reliable information to the information-aware CAV controller, are thoroughly discussed. Diverse human factor issues, such as user comfort, preferences, and reliability, to design the CAV systems for mass adaptation are also discussed. Then, different layers of a CAV controller (route planning, driving mode execution, and driving model selection) considering human factors and information through connectivity are reviewed. In addition, critical challenges for the sensing and communication technologies, human factors, and information-aware controller are identified to support the design of a safe and efficient CAV system while considering user acceptance and comfort. Finally, promising future research directions of these three aspects are discussed to overcome existing challenges to realize a safe and operationally efficient CAV.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). First posted on arXiv 20 Mar 2019.
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Citing papers per year: 2024: 2; 2025: 2; 2026: 1.
5 papers.
- 2024CAV-AHDV-CAV: Mitigating Traffic Oscillations for CAVs through a Novel Car-Following Structure and Reinforcement Learningcited by 1
- 2024CAV-AD: A Robust Framework for Detection of Anomalous Data and Malicious Sensors in CAV Networkscited by 1
- 2025Platoon-Centric Green Light Optimal Speed Advisory Using Safe Reinforcement Learningcited by 0
- 2025Designing The Drive: Enhancing User Experience through Adaptive Interfaces in Autonomous Vehiclescited by 0
- 2026UGAF-ITS: A Standards Harmonization Framework and Validation Tool for Multi-Framework AI Governance in Distributed Intelligent Transportation Systemscited by 0
- 2026UGAF-ITS: A Standards Harmonization Framework and Validation Tool for Multi-Framework AI Governance in Distributed Intelligent Transportation Systems7 Apr 2026
- 2025Designing The Drive: Enhancing User Experience through Adaptive Interfaces in Autonomous Vehicles14 Dec 2025
- 2025Platoon-Centric Green Light Optimal Speed Advisory Using Safe Reinforcement Learning15 Sep 2025
- 2024CAV-AD: A Robust Framework for Detection of Anomalous Data and Malicious Sensors in CAV Networks7 Jul 2024
- 2024CAV-AHDV-CAV: Mitigating Traffic Oscillations for CAVs through a Novel Car-Following Structure and Reinforcement Learning23 Jun 2024