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Recent Estimation Techniques of Vehicle-Road-Pedestrian States for Traffic Safety: Comprehensive Review and Future Perspectives
Ref: CISTER-TR-241001       Publication Date: 2024

Abstract:
Accurate and real-time acquisition of vehicle system dynamic states and pedestrian motion state information is crucial for the safety 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 the recent state estimation techniques for vehicle and pedestrian motion states, as well as tire-road friction. 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.

Cheng Tian

,

Chao Huang

,

Yan Wang

,

Edward Chung

,

Anh Tu Nguyen

,

Pak Kin Wong

,

Wei Ni

,

Abbas Jamalipour

,

Kai Li

,

Hailong Huang