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Summary & Details

Utilizing Human Social Norms for Multimodal Trajectory Forecasting via Group-based Forecasting Module

Group-based Forecasting Moduleによる歩行者の社会的相互作用を考慮したマルチモーダルな軌跡予測

Delivery: Available on this site

Format: PDF

Price: Non-members (tax incl.)：￥1,100 Members (tax incl.)：￥880

Publication code: 20225007

Paper/Info type: Proceedings (Spring)

No.2-22

Pages: 1-6(Total 6 p)

Date of publication: May 2022

Publisher: JSAE

Language: Japanese

Event: 2022 JSAE Annual Congress (Spring)

Detailed Information

Author(J)	1) 箕浦大晃, 2) 平川翼, 3) 山下隆義, 4) 藤吉弘亘
Author(E)	1) Hiroaki Minoura, 2) Tsubasa Hirakawa, 3) Takayoshi Yamashita, 4) Hironobu Fujiyoshi
Affiliation(J)	1) 中部大学, 2) 中部大学, 3) 中部大学, 4) 中部大学
Affiliation(E)	1) Chubu University, 2) Chubu University, 3) Chubu University, 4) Chubu University
Abstract(J)	歩行者を対象とした既存の経路予測手法は，過去数フレームの観測値から将来の経路を予測する．自動運転車技術に経路予測を応用する場合，周囲環境を瞬時に判断する能力が求められるため，既存手法を適用した場合事故につながる可能性がある．そこで本研究では，現時点の歩行者情報などの属性情報を用いて課題に対処する． Translation
Abstract(E)	The existing trajectory forecasting method for pedestrians predicts the future trajectory from the observed trajectory of the past few frames. However, if the existing method is used for autonomous vehicles, it may cause an accident. It is because autonomous vehicles are required to have the ability to instantly judge the surrounding environment. In this study, we work on the issues using attribute information such as the appearance of pedestrians at the current time.

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