Search Results for author: Fang-Chieh Chou

Found 11 papers, 3 papers with code

Reachability Analysis for FollowerStopper: Safety Analysis and Experimental Results

no code implementations29 Dec 2021 Fang-Chieh Chou, Marsalis Gibson, Rahul Bhadani, Alexandre M. Bayen, Jonathan Sprinkle

The FollowerStopper controller has been demonstrated to dampen stop-and-go traffic waves at low speed, but previous analysis on its relative safety has been limited to upper and lower bounds of acceleration.

Integrated Framework of Vehicle Dynamics, Instabilities, Energy Models, and Sparse Flow Smoothing Controllers

no code implementations22 Apr 2021 Jonathan W. Lee, George Gunter, Rabie Ramadan, Sulaiman Almatrudi, Paige Arnold, John Aquino, William Barbour, Rahul Bhadani, Joy Carpio, Fang-Chieh Chou, Marsalis Gibson, Xiaoqian Gong, Amaury Hayat, Nour Khoudari, Abdul Rahman Kreidieh, Maya Kumar, Nathan Lichtlé, Sean McQuade, Brian Nguyen, Megan Ross, Sydney Truong, Eugene Vinitsky, Yibo Zhao, Jonathan Sprinkle, Benedetto Piccoli, Alexandre M. Bayen, Daniel B. Work, Benjamin Seibold

This work presents an integrated framework of: vehicle dynamics models, with a particular attention to instabilities and traffic waves; vehicle energy models, with particular attention to accurate energy values for strongly unsteady driving profiles; and sparse Lagrangian controls via automated vehicles, with a focus on controls that can be executed via existing technology such as adaptive cruise control systems.

Uncertainty-Aware Vehicle Orientation Estimation for Joint Detection-Prediction Models

no code implementations5 Nov 2020 Henggang Cui, Fang-Chieh Chou, Jake Charland, Carlos Vallespi-Gonzalez, Nemanja Djuric

Object detection is a critical component of a self-driving system, tasked with inferring the current states of the surrounding traffic actors.

motion prediction object-detection +1

Multi-View Fusion of Sensor Data for Improved Perception and Prediction in Autonomous Driving

no code implementations27 Aug 2020 Sudeep Fadadu, Shreyash Pandey, Darshan Hegde, Yi Shi, Fang-Chieh Chou, Nemanja Djuric, Carlos Vallespi-Gonzalez

Our model builds on a state-of-the-art Bird's-Eye View (BEV) network that fuses voxelized features from a sequence of historical LiDAR data as well as rasterized high-definition map to perform detection and prediction tasks.

Autonomous Driving object-detection +2

MultiXNet: Multiclass Multistage Multimodal Motion Prediction

no code implementations3 Jun 2020 Nemanja Djuric, Henggang Cui, Zhaoen Su, Shangxuan Wu, Huahua Wang, Fang-Chieh Chou, Luisa San Martin, Song Feng, Rui Hu, Yang Xu, Alyssa Dayan, Sidney Zhang, Brian C. Becker, Gregory P. Meyer, Carlos Vallespi-Gonzalez, Carl K. Wellington

One of the critical pieces of the self-driving puzzle is understanding the surroundings of a self-driving vehicle (SDV) and predicting how these surroundings will change in the near future.

motion prediction

Improving Movement Predictions of Traffic Actors in Bird's-Eye View Models using GANs and Differentiable Trajectory Rasterization

1 code implementation14 Apr 2020 Eason Wang, Henggang Cui, Sai Yalamanchi, Mohana Moorthy, Fang-Chieh Chou, Nemanja Djuric

One of the most critical pieces of the self-driving puzzle is the task of predicting future movement of surrounding traffic actors, which allows the autonomous vehicle to safely and effectively plan its future route in a complex world.

Autonomous Vehicles Motion Forecasting +1

Deep Kinematic Models for Kinematically Feasible Vehicle Trajectory Predictions

no code implementations1 Aug 2019 Henggang Cui, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Jeff Schneider, David Bradley, Nemanja Djuric

Self-driving vehicles (SDVs) hold great potential for improving traffic safety and are poised to positively affect the quality of life of millions of people.

motion prediction

Predicting Motion of Vulnerable Road Users using High-Definition Maps and Efficient ConvNets

1 code implementation20 Jun 2019 Fang-Chieh Chou, Tsung-Han Lin, Henggang Cui, Vladan Radosavljevic, Thi Nguyen, Tzu-Kuo Huang, Matthew Niedoba, Jeff Schneider, Nemanja Djuric

Following detection and tracking of traffic actors, prediction of their future motion is the next critical component of a self-driving vehicle (SDV) technology, allowing the SDV to operate safely and efficiently in its environment.

motion prediction

Multimodal Trajectory Predictions for Autonomous Driving using Deep Convolutional Networks

2 code implementations18 Sep 2018 Henggang Cui, Vladan Radosavljevic, Fang-Chieh Chou, Tsung-Han Lin, Thi Nguyen, Tzu-Kuo Huang, Jeff Schneider, Nemanja Djuric

Autonomous driving presents one of the largest problems that the robotics and artificial intelligence communities are facing at the moment, both in terms of difficulty and potential societal impact.

Autonomous Driving Motion Planning +1

Uncertainty-aware Short-term Motion Prediction of Traffic Actors for Autonomous Driving

no code implementations17 Aug 2018 Nemanja Djuric, Vladan Radosavljevic, Henggang Cui, Thi Nguyen, Fang-Chieh Chou, Tsung-Han Lin, Nitin Singh, Jeff Schneider

We address one of the crucial aspects necessary for safe and efficient operations of autonomous vehicles, namely predicting future state of traffic actors in the autonomous vehicle's surroundings.

Autonomous Driving motion prediction

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