Information Management and Vehicle Scheduling for Intelligent Transportation Systems
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Physical Sensors".
Deadline for manuscript submissions: closed (30 July 2025) | Viewed by 3223
Special Issue Editors
Interests: collaborative perception vehicle networking for autonomous driving; machine learning and its application in wireless networks
Interests: construction and application of intelligent transportation knowledge graph under big data; traffic route planning; intelligent connected vehicle platoon control
Interests: operational research in transportation; data-driven decision-making; intelligent transport system; intelligent algorithms; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are delighted to announce a Special Issue on "Information Management and Vehicle Scheduling for Intelligent Transportation Systems", which aims to explore cutting-edge advancements in intelligent transportation systems (ITSs).
The ever-developing information management technology in vehicular networks, including V2X communication, edge computing, and cloud cache, has great potential to enhance road safety, traffic efficiency, energy savings, and the driving experience of intelligent transportation systems. On the other hand, vehicle scheduling serves as another physical way to optimize road efficiency, which inevitably rearranges the information regarding traffic distribution. Therefore, ITSs can benefit from the optimization of information management and vehicle scheduling; more gain can be expected if the two aspects are considered jointly.
To this end, this Special Issue is dedicated to showcasing innovative research that addresses the challenges and opportunities of ITSs, particularly through the optimization of information management and vehicle scheduling. The particular topics of interest for this Special Issue include, but are not limited to, the following:
- Service offloading methods in transportation.
- Differentiated service scheduling in transportation.
- Cooperative communication among vehicles.
- Resource allocation and scheduling in UAV-assisted V2X networks.
- Distribution analysis of computing and communication resources in the Internet of Vehicles.
- Data-driven vehicle scheduling approaches.
- Vehicle route planning and scheduling in autonomous transportation systems.
- Advanced analytics and predictive modeling for vehicle scheduling.
- Dynamic vehicle scheduling algorithms.
- Green/sustainable transportation network optimization.
- Collaborative perception techniques assisted by V2X.
- High-accuracy PNT for autonomous driving.
- Low-earth-orbit satellite-assisted ITSs.
- Joint wireless resource allocation and vehicle scheduling.
- Joint optimization of V2X and vehicle control.
Dr. Chongtao Guo
Dr. Yun Meng
Dr. Hongguang Ma
Guest Editors
Manuscript Submission Information
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Keywords
- service offloading methods in transportation
- differentiated service scheduling in transportation
- cooperative communication among vehicles
- resource allocation and scheduling in UAV-assisted V2X networks
- distribution analysis of computing and communication resources in the Internet of Vehicles
- data-driven vehicle scheduling approaches
- vehicle route planning and scheduling in autonomous transportation systems
- advanced analytics and predictive modeling for vehicle scheduling
- dynamic vehicle scheduling algorithms
- green/sustainable transportation network optimization
- collaborative perception techniques assisted by V2X
- high-accuracy PNT for autonomous driving
- low-earth-orbit satellite-assisted ITSs
- joint wireless resource allocation and vehicle scheduling
- joint optimization of V2X and vehicle control
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