Pedestrian crossing intention prediction in the wild:A survey  

作　　者：Yancheng Ling Zhenliang Ma 

机构地区：[1]KTH Royal Institute of Technology Ringgold Standard Institution,Brinellvägen 23,Stockholm,Stockholm 11428,Sweden

出　　处：《Chain》2024年第4期263-279,共17页链(英文)

摘　　要：In real-world driving scenarios,understanding the intentions of pedestrians in real-time is critical for the built environment safety when operating intelligent vehicles on the roads.Pedestrians crossing the street is a common behavior that can easily lead to accidents.This paper presents a comprehensive review of the prediction of pedestrian crossing intentions,focusing on data,model structure,data representation,information extraction,prediction function,and associated models and challenges.The review highlights that data types,model generalization ability,and prediction uncertainty are key challenges on pedestrian crossing intention prediction.It identifies open challenges and opportunities for future research in pedestrian crossing intention prediction.

关 键 词：pedestrian crossing intention prediction data representation information extraction prediction uncertainty 

分 类 号：U49[交通运输工程—交通运输规划与管理]