Document Type
Conference Paper
Subject Area
CPS Auto, CPS Formal Methods
Date of this Version
4-14-2016
Publication Source
SAE World Congress 2016
Start Page
1
Last Page
13
DOI
doi:10.4271/2016-01-0019
Abstract
Autonomous vehicles (AVs) have already driven millions of miles on public roads, but even the simplest scenarios have not been certified for safety. Current methodologies for the verification of AV's decision and control systems attempt to divorce the lower level, short-term trajectory planning and trajectory tracking functions from the behavioral rules-based framework that governs mid-term actions. Such analysis is typically predicated on the discretization of the state space and has several limitations. First, it requires that a conservative buffer be added around obstacles such that many feasible plans are classified as unsafe. Second, the discretized controllers modeled in this analysis require several refinement steps before being implementable on an actual AV, and typically do not allow the specification of comfort-related properties on the trajectories. In contrast, consumer-ready AVs use motion planning algorithms that generate smooth trajectories. While viable algorithms exist for the generation of smooth trajectories originating from a single state, analysis should consider that the AV faces state estimation errors and disturbances. Third, verification is restricted to a discretized state space with fixed-size cells; this assumption can artificially limit the set of available trajectories if the discretization is too coarse. Conversely, too fine of a discretization renders the problem intractable for automated analysis. This work presents a new verification tool, APEX, which investigates the combined action of a behavioral planner and state lattice-based motion planner to guarantee a safe vehicle trajectory is chosen. In APEX, decisions made at the behavioral layer can be traced through to the spatio-temporal evolution of the AV and verified. Thus, there is no need to create abstractions of the AV's controllers, and aggressive trajectories required for evasive maneuvers can be accurately investigated.
Keywords
autonomous vehicles, formal verification, reachability
Recommended Citation
Matthew O'Kelly, Houssam Abbas, Sicun Gao, Shin'ichi Shiraishi , Shinpei Kato, and Rahul Mangharam, "APEX: Autonomous Vehicle Plan Verification and Execution" SAE World Congress, April 2016.
Bib Tex
@ARTICLE {apex_SAE16, author = "Matthew O'Kelly and Houssam Abbas and Sicun Gao and Shin'ichi Shiraishi and Shinpei Kato, and Rahul Mangharam", title = "APEX: Autonomous Vehicle Plan Verification and Execution", journal = "SAE World Congress", year = "2016", volume = "1", month = "Apr" }
Included in
Computer Engineering Commons, Systems and Communications Commons, Theory and Algorithms Commons
Date Posted: 15 January 2016
This document has been peer reviewed.