dou, wanqing lili, lu
Accurate pedestrian trajectory prediction is crucial in many fields. This requires the full use and learning of pedestrians’ social interactions, movements, and environmental information. In view of the current research on pedestrian trajectory prediction, wherein most of the pedestrian interaction information is explored from the level of overall ...
netušil, petr
V této práci se zabývám problémem predikce budoucí trajektorie chodců pro autonomní auta. Popisuji datové sady PIE a JAAD a jejich parametry. Dále zde představuji současný stav vývoje této problematiky a popisuji fungování jednotlivých řešení. Provedl jsem analýzu chybovosti metody BiTraP, na základě čehož jsem navrhl vlastní řešení predikce trajek...
ruan, kangrui xuan, di
Predicting the future trajectories of multiple interacting pedestrians within a scene has increasingly gained importance in various fields, e.g., autonomous driving, human–robot interaction, and so on. The complexity of this problem is heightened due to the social dynamics among different pedestrians and their heterogeneous implicit preferences. In...
meng, dexu zhao, guangzhe yan, feihu
As autonomous driving technology advances, the imperative of ensuring pedestrian traffic safety becomes increasingly prominent within the design framework of autonomous driving systems. Pedestrian trajectory prediction stands out as a pivotal technology aiming to address this challenge by striving to precisely forecast pedestrians’ future trajector...
deng, yingjian zhang, li chen, jie deng, yu liu, jing
Pedestrian trajectory prediction is a key technical prerequisite for autonomous vehicle trajectory planning. However, a pedestrian is a changeable individual, and their intentions exhibit certain degrees of randomness and uncertainty, which leads to the issue that modeling only past trajectories does not enable the effective description of the rand...
korbmacher, raphael tordeux, antoine
Predicting human trajectories poses a significant challenge due to the complex interplay of pedestrian behavior, which is influenced by environmental layout and interpersonal dynamics. This complexity is further compounded by variations in scene density. To address this, we introduce a novel dataset from the Festival of Lights in Lyon 2022, charact...
deng, yingjian zhang, li chen, jie deng, yu huang, zhixiang yingsong, li cao, yice zhongcheng, wu zhang, jun
Pedestrian trajectory prediction is extremely challenging due to the complex social attributes of pedestrians. Introducing latent vectors to model trajectory multimodality has become the latest mainstream solution idea. However, previous approaches have overlooked the effects of redundancy that arise from the introduction of latent vectors. Additio...
zhongli, ma ruojin, an liu, jiajia cui, yuyong jun, qi teng, yunlong sun, zhijun juguang, li zhang, guoliang
Pedestrian trajectory prediction is one of the most important topics to be researched for unmanned driving and intelligent mobile robots to perform perceptual interaction with the environment. To solve the problem of the SGAN (social generative adversarial networks) model lacking an understanding of pedestrian interaction and scene constraints, thi...
Wang, Jinyu Sang, Haifeng Chen, Wangxing Zhao, Zishan
Published in
Physica Scripta
The accurate and reliable prediction of pedestrian future trajectories is of crucial significance for ensuring the safe navigation of autonomous driving systems. This paper introduces a novel approach called the Variational One-Shot Transformer Network (VOSTN) for the prediction of future trajectories within the 2D on-board domain. VOSTN presents a...
Korbmacher, Raphael Dang, Huu-Tu Tordeux, Antoine
Predicting human trajectories is a challenging task due to the complexity of pedestrian behavior, which is influenced by external factors such as the scene’s topology and interactions with other pedestrians. A special challenge arises from the dependence of the behavior on the density of the scene. In the literature, deep learning algorithms show t...
