Learning-based Initialization Strategy for Safety of Multi-Vehicle Systems

by   Jennifer C. Shih, et al.

Multi-vehicle collision avoidance is a highly crucial problem due to the soaring interests of introducing autonomous vehicles into the real world in recent years. The safety of these vehicles while they complete their objectives is of paramount importance. Hamilton-Jacobi (HJ) reachability is a promising tool for guaranteeing safety for low-dimensional systems. However, due to its exponential complexity in computation time, no reachability-based methods have been able to guarantee safety for more than three vehicles successfully in unstructured scenarios. For systems with four or more vehicles,we can only empirically validate their safety performance.While reachability-based safety methods enjoy a flexible least-restrictive control strategy, it is challenging to reason about long-horizon trajectories online because safety at any given state is determined by looking up its safety value in a pre-computed table that does not exhibit favorable properties that continuous functions have. This motivates the problem of improving the safety performance of unstructured multi-vehicle systems when safety cannot be guaranteed given any least-restrictive safety-aware collision avoidance algorithm while avoiding online trajectory optimization. In this paper, we propose a novel approach using supervised learning to enhance the safety of vehicles by proposing new initial states in very close neighborhood of the original initial states of vehicles. Our experiments demonstrate the effectiveness of our proposed approach and show that vehicles are able to get to their goals with better safety performance with our approach compared to a baseline approach in wide-ranging scenarios.


Reachability-based Safe Planning for Multi-Vehicle Systems withMultiple Targets

Recently there have been a lot of interests in introducing UAVs for a wi...

Reachability-Based Confidence-Aware Probabilistic Collision Detection in Highway Driving

Risk assessment is a crucial component of collision warning and avoidanc...

Analysing Ultra-Wide Band Positioning for Geofencing in a Safety Assurance Context

There is a desire to move towards more flexible and automated factories....

Goal-Aware RSS for Complex Scenarios via Program Logic

We introduce a goal-aware extension of responsibility-sensitive safety (...

Physical Backdoor Trigger Activation of Autonomous Vehicle using Reachability Analysis

Recent studies reveal that Autonomous Vehicles (AVs) can be manipulated ...

An Empirical Analysis of the Use of Real-Time Reachability for the Safety Assurance of Autonomous Vehicles

Recent advances in machine learning technologies and sensing have paved ...

Critical Zones for Comfortable Collision Avoidance with a Leading Vehicle

This paper provides a general framework for efficiently obtaining the ap...

Please sign up or login with your details

Forgot password? Click here to reset