GPT-4V Takes the Wheel: Promises and Challenges for Pedestrian Behavior Prediction

no code implementations • 24 Nov 2023 • Jia Huang, Peng Jiang, Alvika Gautam, Srikanth Saripalli

To our knowledge, this research is the first to conduct both quantitative and qualitative evaluations of VLMs in the context of pedestrian behavior prediction for autonomous driving.

Autonomous Driving Common Sense Reasoning +3

Learning Pedestrian Actions to Ensure Safe Autonomous Driving

no code implementations • 22 May 2023 • Jia Huang, Alvika Gautam, Srikanth Saripalli

Evaluation results illustrate that the proposed method reaches an accuracy of 81% on action prediction task on JAAD testing data and outperforms the LSTM-ed by 7. 4%, while LSTM counterpart performs much better on trajectory prediction task for a prediction sequence length of 25 frames.

Autonomous Driving Trajectory Prediction