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Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs
12 references·0 citing·43 second hop
Forecasting Trajectory and Behavior of Road-Agents Using Spectral Clustering in Graph-LSTMs (2020)Forecasting Trajectory and Behavior of Ro…Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting (2019)Traffic Graph Convolutional R…Group LSTM: Group Trajectory Prediction in Crowded Scenarios (2019)Group LSTM: Group Trajectory …Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting (2019)Dynamic Spatial-Temporal Grap…Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (2019)Attention Based Spatial-Tempo…Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting (2018)Spatio-Temporal Graph Convolu…Encoding Crowd Interaction with Deep Neural Network for Pedestrian Trajectory Prediction (2018)Encoding Crowd Interaction wi…The Trouble with Autopilots (2017)The Trouble with AutopilotsImpact of mobile phone use on car-following behaviour of young drivers (2015)Impact of mobile phone use on…Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions (2013)Behavioural changes in driver…THE BIG FIVE PERSONALITY DIMENSIONS AND JOB PERFORMANCE: A META‐ANALYSIS (1991)THE BIG FIVE PERSONALITY DIME…Time Series Analysis: Forecasting and Control. (1978)Time Series Analysis: Forecas…Time Series Analysis Forecasting and Control. (1973)Time Series Analysis Forecast…Toward a Theory of Situation Awareness in Dynamic Systems (1995)Humans and Automation: Use, Misuse, Disuse, Abuse (1997)A model for types and levels of human interaction with automation (2000)Responsibility for Crashes of Autonomous Vehicles: An Ethical Analysis (2014)The influence of age on the take-over of vehicle control in highly automated driving (2016)Toward Computational Simulations of Behavior During Automated Driving Takeovers: A Review of the Empirical and Modeling Literatures (2019)Handbook of Industrial and Organizational Psychology. (1977)Validation of the five-factor model of personality across instruments and observers. (1987)Personality Structure: Emergence Of The 5-Factor Model (1990)An Introduction to the Five‐Factor Model and Its Applications (1992)The Big Five Trait taxonomy: History, measurement, and theoretical perspectives. (1999)Grit: Perseverance and passion for long-term goals. (2007)Plans and Situated Actions: The Problem of Human-Machine Communication (1990)Sequence Organization in Interaction (2007)Machine learning, social learning and the governance of self-driving cars (2017)Driving Style: How Should an Automated Vehicle Behave? (2019)Autonowashing: The Greenwashing of Vehicle Automation (2020)Modeling and Forecasting Vehicular Traffic Flow as a Seasonal ARIMA Process: Theoretical Basis and Empirical Results (2003)Traffic Flow Prediction With Big Data: A Deep Learning Approach (2014)Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting (2017)Graph WaveNet for Deep Spatial-Temporal Graph Modeling (2019)Social force model for pedestrian dynamics (1995)Agent-based modeling: Methods and techniques for simulating human systems (2002)Crowds by Example (2007)SR-LSTM: State Refinement for LSTM Towards Pedestrian Trajectory Prediction (2019)STGAT: Modeling Spatial-Temporal Interactions for Human Trajectory Prediction (2019)Spatio-Temporal Graph Transformer Networks for Pedestrian Trajectory Prediction (2020)Deep Multi-View Spatial-Temporal Network for Taxi Demand Prediction (2018)Adaptive Graph Convolutional Recurrent Network for Traffic Forecasting (2020)Spatial-Temporal Synchronous Graph Convolutional Networks: A New Framework for Spatial-Temporal Network Data Forecasting (2020)Graph neural network for traffic forecasting: A survey (2022)Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction (2017)How to Build a Graph-Based Deep Learning Architecture in Traffic Domain: A Survey (2020)Traffic Flow Forecasting with Spatial-Temporal Graph Diffusion Network (2021)Spatio-Temporal Meta-Graph Learning for Traffic Forecasting (2023)Principles of Forecasting (2001)25 years of time series forecasting (2006)DeepAR: Probabilistic forecasting with autoregressive recurrent networks (2019)Deep Learning on Traffic Prediction: Methods, Analysis, and Future Directions (2022)Dynamic Graph Convolutional Recurrent Network for Traffic Prediction: Benchmark and Solution (2022)Revealing the dynamic network structure of the Beck Depression Inventory-II (2014)The life course cube: A tool for studying lives (2018)Assessing the environmental impacts of renewable energy sources: A case study on air pollution and carbon emissions in China (2023)
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References

  • 1991THE BIG FIVE PERSONALITY DIMENSIONS AND JOB PERFORMANCE: A META‐ANALYSIS9,122 cited
  • 2018Spatio-Temporal Graph Convolutional Networks: A Deep Learning Framework for Traffic Forecasting6,048 cited
  • 1978Time Series Analysis: Forecasting and Control.5,395 cited
  • 2019Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting3,248 cited
  • 2019Traffic Graph Convolutional Recurrent Neural Network: A Deep Learning Framework for Network-Scale Traffic Learning and Forecasting1,020 cited
  • 1973Time Series Analysis Forecasting and Control.995 cited
  • 2019Dynamic Spatial-Temporal Graph Convolutional Neural Networks for Traffic Forecasting351 cited
  • 2013Behavioural changes in drivers experiencing highly-automated vehicle control in varying traffic conditions345 cited
  • 2018Encoding Crowd Interaction with Deep Neural Network for Pedestrian Trajectory Prediction292 cited
  • 2017The Trouble with Autopilots186 cited
  • 2015Impact of mobile phone use on car-following behaviour of young drivers147 cited
  • 2019Group LSTM: Group Trajectory Prediction in Crowded Scenarios131 cited

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