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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 443

Special Issue Editors


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Guest Editor
College of Electronics and Information Engineering, Shenzhen University, Shenzhen, China
Interests: collaborative perception vehicle networking for autonomous driving; machine learning and its application in wireless networks

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Guest Editor
School of Electronic and Control Engineering, Chang'an University, Xi'an, China
Interests: construction and application of intelligent transportation knowledge graph under big data; traffic route planning; intelligent connected vehicle platoon control

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Guest Editor
School of Economics and Management, Beijing University of Chemical Technology, Beijing, China
Interests: optimization; big data analysis; urban traffic management; logistics management
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

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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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Published Papers (1 paper)

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Research

37 pages, 4052 KB  
Article
PD Control with Feedforward Compensation for String Stable Cooperative Adaptive Cruise Control in Vehicle Platoons
by Kangjun Lee and Chanhwa Lee
Sensors 2025, 25(17), 5434; https://doi.org/10.3390/s25175434 - 2 Sep 2025
Abstract
In this paper, we propose systematic controller design guidelines to ensure both individual vehicle stability and string stability in cooperative adaptive cruise control (CACC)-based platoon systems, assuming a homogeneous platoon where all vehicles share identical dynamic models. We rigorously demonstrate that the limitation [...] Read more.
In this paper, we propose systematic controller design guidelines to ensure both individual vehicle stability and string stability in cooperative adaptive cruise control (CACC)-based platoon systems, assuming a homogeneous platoon where all vehicles share identical dynamic models. We rigorously demonstrate that the limitation of conventional adaptive cruise control (ACC) in maintaining the target inter-vehicle distance can be effectively overcome by incorporating the desired acceleration of the preceding vehicle as a static feedforward input. Furthermore, by formulating transfer functions in the frequency domain, we analytically derive the conditions required to ensure both individual vehicle stability and string stability of the CACC system. Building on this insight, we propose a practical and theoretically well-founded design guideline for determining the proportional, derivative, and feedforward gains of control input under a constant time gap spacing policy. The proposed guidelines are validated through simulations conducted in a realistic platooning scenario involving multiple vehicles. Full article
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