首页|Recent Estimation Techniques of Vehicle-Road-Pedestrian States for Traffic Safety: Comprehensive Review and Future Perspectives

Recent Estimation Techniques of Vehicle-Road-Pedestrian States for Traffic Safety: Comprehensive Review and Future Perspectives

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  • NETL
  • NSTL
  • IEEE
Accurate and real-time acquisition of vehicular system dynamic states, road surface conditions, and motion states of surrounding participants is crucial for the safety, passenger comfort, and operational efficiency of autonomous vehicles (AVs) and connected automated vehicles (CAVs). In recent years, a significant amount of research has contributed to the field of state estimation for vehicles, roads, and pedestrians. From the systemwide perspective of intelligent transportation systems to a focused view on “vehicle-road-pedestrian”, this survey aims to provide a comprehensive review and summary of recent state estimation techniques for vehicle motion, road surface, and pedestrian motion. A thorough analysis of the reviewed literature, relevant datasets, evaluation metrics, and experimental platforms in this field is also conducted. Finally, existing challenges and future research directions about methods and performance evaluation are further discussed. This survey is expected to contribute to the advancement of research in dynamic state estimation of vehicle-road-pedestrian, thereby facilitating the development of efficient and safe intelligent transportation systems.

RoadsVehicle dynamicsSurveysPedestriansTiresIntelligent transportation systemsDynamicsState estimationElectronic mailSafety

Cheng Tian、Chao Huang、Yan Wang、Edward Chung、Anh-Tu Nguyen、Pak Kin Wong、Wei Ni、Abbas Jamalipour、Kai Li、Hailong Huang

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Department of Aeronautical and Aviation Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China

Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China

Department of Electrical and Electronic Engineering, The Hong Kong Polytechnic University, Hong Kong, SAR, China

LAMIH Laboratory, UMR CNRS 8201, and INSA Hauts-de-France, Université Polytechnique Hauts-de-France, Valenciennes, France

Department of Electromechanical Engineering, University of Macau, Macau, China

Data61, Commonwealth Scientific and Industrial Research Organization, Sydney, Australia

School of Electrical and Computer Engineering, The University of Sydney, Sydney, Australia

Department of Engineering, University of Cambridge, Cambridge, U.K.|Real-Time and Embedded Computing Systems Research Centre (CISTER), Porto, Portugal

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2025

10.1109/TITS.2024.3517162

IEEE transactions on intelligent transportation systems

IEEE transactions on intelligent transportation systems

ISSN：
年,卷(期)：2025.26(3)
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