1 code implementation • NeurIPS 2023 • Nico Montali, John Lambert, Paul Mougin, Alex Kuefler, Nick Rhinehart, Michelle Li, Cole Gulino, Tristan Emrich, Zoey Yang, Shimon Whiteson, Brandyn White, Dragomir Anguelov
Simulation with realistic, interactive agents represents a key task for autonomous vehicle software development.
no code implementations • 31 Jul 2020 • Shubhankar Agarwal, Harshit Sikchi, Cole Gulino, Eric Wilkinson, Shivam Gautam
A popular way to plan trajectories in dynamic urban scenarios for Autonomous Vehicles is to rely on explicitly specified and hand crafted cost functions, coupled with random sampling in the trajectory space to find the minimum cost trajectory.
no code implementations • ECCV 2020 • Sergio Casas, Cole Gulino, Simon Suo, Katie Luo, Renjie Liao, Raquel Urtasun
In order to plan a safe maneuver an autonomous vehicle must accurately perceive its environment, and understand the interactions among traffic participants.
no code implementations • 4 Jun 2020 • Sergio Casas, Cole Gulino, Simon Suo, Raquel Urtasun
Towards this goal, we design a framework that leverages REINFORCE to incorporate non-differentiable priors over sample trajectories from a probabilistic model, thus optimizing the whole distribution.
no code implementations • 18 Oct 2019 • Sergio Casas, Cole Gulino, Renjie Liao, Raquel Urtasun
A graph neural network then iteratively updates the actor states via a message passing process.