Distributed Edge Intelligence for Vehicle–Road Collaborative Systems: Sensing, Communication and Computation Synergy
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Vehicular Sensing".
Deadline for manuscript submissions: 30 October 2026 | Viewed by 213
Special Issue Editors
Interests: intelligent transportation systems; Internet of Vehicles; distributed computing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
In recent years, autonomous driving technologies have entered a stage of rapid development. In autonomous driving scenarios, vehicles rely on onboard sensors to perceive environments and make decisions. However, the inherent limitations of single-vehicle perception significantly constrain the safety and reliability of autonomous driving systems. To address these challenges, Vehicle–Road Collaboration (VRC) has emerged as a promising paradigm. By leveraging cooperative perception technologies that integrate heterogeneous sensors deployed on intelligent vehicles and roadside infrastructures, VRC extends sensing coverage and enhances system robustness. However, it also generates massive volumes of data, thereby imposing stringent requirements on communication bandwidth and computational resources. Meanwhile, vehicular applications are typically computation-intensive and delay-sensitive, with strict demands on accuracy, real-time responsiveness, and fault tolerance, which further intensify the need for efficient communication and computing resource support. Distributed Edge Intelligence (DEI) offers a compelling solution to address these challenges by enabling low-latency data processing and intelligent service provisioning at the network edge. By migrating data processing from centralized cloud servers to distributed edge nodes, DEI significantly reduces transmission latency, improves Quality of Service (QoS), and enhances resource utilization efficiency. Furthermore, this paradigm supports privacy preservation and enables distributed, low-latency intelligent service deployment. Nevertheless, the highly dynamic and mobile vehicular environment poses significant challenges to service continuity. In addition, the scalability and heterogeneity of vehicular networks further highlight the urgency of intelligent resource management and system optimization. This Special Issue aims to explore recent advances in vehicle–road collaborative systems empowered by distributed edge intelligence. Topics of interest include, but are not limited to, the following:
- Novel sensing, computing and communication theories for vehicle–road collaboration
- Innovative architectures and communication protocols for vehicle–road collaboration
- Cloud–edge collaborative intelligence for vehicle–road collaboration
- Distributed learning and inference methods for vehicle–road collaboration
- Privacy-preserving techniques in vehicle–road collaboration systems
- Real-time decision-making and fault-tolerant mechanisms for vehicle–road collaboration
- Performance evaluation methodologies and experimental testbeds for vehicle–road collaboration
Dr. Lei Liu
Dr. Kan Wang
Guest Editors
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Keywords
- vehicle–road collaborative systems
- internet of vehicles
- distributed computing
- edge intelligence
- resource management
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