Article
Engineering, Civil
Parth Kothari, Sven Kreiss, Alexandre Alahi
Summary: This study explores the development of human trajectory forecasting, comparing handcrafted representations with deep learning methods, and proposing two data-driven approaches to effectively capture social interactions. By establishing the TrajNet++ benchmark and introducing new performance metrics, the superiority of the proposed method on real-world and synthetic datasets is validated.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Engineering, Civil
Can Li, Wei Liu
Summary: This study proposes a model for multimodal transport demand forecasting using federated learning, which improves accuracy without direct data sharing. By introducing a processing center to handle parameters from private datasets, privacy concerns and ownership constraints are addressed. Evaluations show that this model outperforms baselines and state-of-the-art models.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Review
Psychology
Russell Spears
Summary: This chapter reviews research on the group identity explanation of social influence and contrasts it with other group-based explanations. It also discusses moderating factors related to individual variation, intragroup and intergroup context, and contextual variables relevant to online influence in the new media. The self-categorization explanation grounded in group norms is compared to other normative explanations of influence.
ANNUAL REVIEW OF PSYCHOLOGY, VOL 72
(2021)
Article
Robotics
Lei Zhou, Dingye Yang, Xiaolin Zhai, Shichao Wu, Zhengxi Hu, Jingtai Liu
Summary: This paper proposes a novel trajectory prediction framework, GA-STT, which effectively models socially aware spatial interaction and complex temporal dependencies among groups through a group aware spatial-temporal transformer network. Experimental results demonstrate that our model outperforms the state-of-the-art method in predicting complex spatial-temporal interactions.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Engineering, Civil
Parth Kothari, Alexandre Alahi
Summary: Human trajectory forecasting in crowds faces the challenge of modeling social interactions and outputting collision-free multimodal distribution. SGANv2, an improved safety-compliant SGAN architecture equipped with spatio-temporal interaction modeling and a transformer-based discriminator, is introduced to address the limitation of current networks in outputting socially acceptable trajectories. Through extensive experimentation, the efficacy of SGANv2 to provide socially-compliant multimodal trajectories is demonstrated.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Xiaoyu Mo, Haochen Liu, Zhiyu Huang, Xiuxian Li, Chen Lv
Summary: This work proposes a novel map-adaptive multimodal trajectory predictor that predicts future traffic behavior in complex driving environments. The predictor is derived by training an intention-aware unimodal trajectory predictor and linking driving modalities, driver's intentions, and a vehicle's candidate centerlines. The proposed predictor offers a faster and more cost-effective alternative compared to traditional multimodal predictors and has demonstrated comparable or superior performance in specific applications.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Engineering, Civil
Jianwu Fang, Chen Zhu, Pu Zhang, Jianru Xue, Hongkai Yu
Summary: This study proposes a risk and scene graph learning method for heterogeneous road agents, which effectively predicts trajectories in driving situations. The method includes a Heterogeneous Risk Graph (HRG) and a Hierarchical Scene Graph (HSG) that capture the complex interaction relations among road agents and their agent-environment constraint. Experimental results on multiple datasets demonstrate its superior performance compared to state-of-the-art approaches.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Celso M. de Melo, Kazunori Terada, Francisco C. Santos
Summary: The experimental analysis reveals how emotion expressions interact with direct and indirect reciprocity mechanisms to shape individual choices and foster cooperation, highlighting the significance of emotions in promoting societal cooperation.
Article
Environmental Studies
Samantha N. Mertens, P. Wesley Schultz
Summary: Research has shown that normative feedback can increase waste diversion rates, especially among households with baseline diversion rates below the norm. However, there were no significant differences between the different types of feedback conditions.
JOURNAL OF ENVIRONMENTAL PSYCHOLOGY
(2021)
Article
Psychology, Social
Selma C. Rudert, J. N. Rasmus Moering, Christoph Kenntemich, Christiane M. Buttner
Summary: Research on ostracism has usually focused on how individuals who are excluded and ignored react to being ostracized. However, the perspective and reasons for why individuals decide to ostracize others are still largely unexplored. In this study, two fundamental motives were proposed that drive motivated ostracism decisions: perceiving a norm violation or perceiving the target as expendable for achieving group goals. The results of survey studies and experiments supported these predictions and also showed that strategic considerations about the situational context influence ostracism decisions.
JOURNAL OF PERSONALITY AND SOCIAL PSYCHOLOGY
(2023)
Article
Chemistry, Analytical
Weiping Zhu, Lin Xu, Yijie Tang, Rong Xie
Summary: This study introduces an approach to synchronize trajectory data for group recognition, aligning all people's trajectories using data interpolating and eliminating time deviations through message passing. Experimental results demonstrate a 97.7% accuracy in group recognition. The proposed method outperforms existing approaches in dealing with time deviations.
Article
Psychology, Multidisciplinary
Iina Savolainen, Atte Oksanen, Markus Kaakinen, Anu Sirola, Izabela Zych, Hye-Jin Paek
Summary: This study examined the association between following gambling norms in online interaction and youth problem gambling. The results showed that conforming to online gambling norms is related to youth problem gambling, but cultural differences exist. Therefore, intervention strategies should provide accurate gambling information to young problem gamblers.
COMPUTERS IN HUMAN BEHAVIOR
(2021)
Article
Computer Science, Artificial Intelligence
Edmure Windsor, Wei Cao
Summary: This study develops an innovative multimodal fusion-based model to forecast exchange rates by incorporating market indicators and investor sentiments into consideration. The experimental results demonstrate the superiority of the proposed approach over baseline algorithms.
APPLIED INTELLIGENCE
(2022)
Article
Robotics
Jianing Qiu, Lipeng Chen, Xiao Gu, Frank P-W Lo, Ya-Yen Tsai, Jiankai Sun, Jiaqi Liu, Benny Lo
Summary: In this study, the problem of forecasting the trajectory of an egocentric camera wearer in crowded spaces is addressed. A novel egocentric human trajectory forecasting dataset is constructed, and a Transformer-based neural network model integrated with a cascaded cross-attention mechanism is designed. The results show that the proposed model outperforms the state-of-the-art methods in egocentric human trajectory forecasting.
IEEE ROBOTICS AND AUTOMATION LETTERS
(2022)
Article
Computer Science, Information Systems
Jing Jing, Hongchen Wu, Jie Sun, Xiaochang Fang, Huaxiang Zhang
Summary: This study proposes a progressive fusion network (MPFN) for multimodal fake news detection, which captures the representational information of each modality at different levels and establishes connections between modalities through feature fusion. The method achieves significant improvement in identifying fake news.
INFORMATION PROCESSING & MANAGEMENT
(2023)
