Safety and progress proofs for a reactive planner and controller for autonomous driving

07/13/2021
by   Abolfazl Karimi, et al.
0

In this paper, we perform safety and performance analysis of an autonomous vehicle that implements reactive planner and controller for navigating a race lap. Unlike traditional planning algorithms that have access to a map of the environment, reactive planner generates the plan purely based on the current input from sensors. Our reactive planner selects a waypoint on the local Voronoi diagram and we use a pure-pursuit controller to navigate towards the waypoint. Our safety and performance analysis has two parts. The first part demonstrates that the reactive planner computes a plan that is locally consistent with the Voronoi plan computed with full map. The second part involves modeling of the evolution of vehicle navigating along the Voronoi diagram as a hybrid automata. For proving the safety and performance specification, we compute the reachable set of this hybrid automata and employ some enhancements that make this computation easier. We demonstrate that an autonomous vehicle implementing our reactive planner and controller is safe and successfully completes a lap for five different circuits. In addition, we have implemented our planner and controller in a simulation environment as well as a scaled down autonomous vehicle and demonstrate that our planner works well for a wide variety of circuits.

READ FULL TEXT
research
04/21/2022

Autonomous Vehicle Parking in Dynamic Environments: An Integrated System with Prediction and Motion Planning

This paper presents an integrated motion planning system for autonomous ...
research
07/01/2022

Comprehensive Reactive Safety: No Need For A Trajectory If You Have A Strategy

Safety guarantees in motion planning for autonomous driving typically in...
research
04/19/2022

Learning Forward Dynamics Model and Informed Trajectory Sampler for Safe Quadruped Navigation

For autonomous quadruped robot navigation in various complex environment...
research
11/17/2021

Adaptive Lookahead Pure-Pursuit for Autonomous Racing

This paper presents an adaptive lookahead pure-pursuit lateral controlle...
research
07/31/2020

Infusing Reachability-Based Safety into Planning and Control for Multi-agent Interactions

Within a robot autonomy stack, the planner and controller are typically ...
research
04/17/2023

PaaS: Planning as a Service for reactive driving in CARLA Leaderboard

End-to-end deep learning approaches has been proven to be efficient in a...
research
09/15/2021

Delay-aware Robust Control for Safe Autonomous Driving

With the advancement of affordable self-driving vehicles using complicat...

Please sign up or login with your details

Forgot password? Click here to reset