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

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.

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Publication Details

Journal
IEEE Transactions on Intelligent Transportation Systems
Published
2024-12-25
DOI
https://doi.org/10.1109/tits.2024.3517162
Citations
5
Primary Topic
Autonomous Vehicle Technology and Safety
Type
article
Field-Weighted Citation Impact
1.02
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article

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

Pak Kin Wong, Hailong Huang, Edward Chung, Yan Wang et al.
5 citations
IEEE Transactions on Intelligent Transportation Systems
Autonomous Vehicle Technology and Safety
1.02
article

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

Pak Kin Wong, Hailong Huang, Edward Chung, Yan Wang, Chao Huang, Abbas Jamalipour, Anh‐Tu Nguyen, Kai Li, Wei Ni, Tian Cheng
article en
5 citations

Abstract

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.

IEEE Transactions on Intelligent Transportation SystemsVol. 26(3)
Centre National de la Recherche Scientifique (FR), The University of Sydney (AU), Hong Kong Polytechnic University (HK), University of Macau (MO), University of Cambridge (GB), Laboratoire d'Automatique, de Mécanique et d'Informatique Industrielles et Humaines (FR), Health Sciences and Nutrition (AU), Data61 (AU), INSA Hauts-de-France (FR), Université Polytechnique Hauts-de-France (FR)
Sustainable cities and communities
Openalex Percentile: Top 24%
Autonomous Vehicle Technology and Safety
1.02
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