An ontology-based approach to relax traffic regulation for autonomous vehicle assistance

12/04/2012
by   Philippe Morignot, et al.
0

Traffic regulation must be respected by all vehicles, either human- or computer- driven. However, extreme traffic situations might exhibit practical cases in which a vehicle should safely and reasonably relax traffic regulation, e.g., in order not to be indefinitely blocked and to keep circulating. In this paper, we propose a high-level representation of an automated vehicle, other vehicles and their environment, which can assist drivers in taking such "illegal" but practical relaxation decisions. This high-level representation (an ontology) includes topological knowledge and inference rules, in order to compute the next high-level motion an automated vehicle should take, as assistance to a driver. Results on practical cases are presented.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 1

page 2

page 3

page 4

02/13/2019

Integrating Neurophysiological Sensors and Driver Models for Safe and Performant Automated Vehicle Control in Mixed Traffic

In future mixed traffic Highly Automated Vehicles (HAV) will have to res...
05/05/2022

A Driver-Vehicle Model for ADS Scenario-based Testing

Scenario-based testing for automated driving systems (ADS) must be able ...
01/11/2021

Kinetic derivation of Aw-Rascle-Zhang-type traffic models with driver-assist vehicles

In this paper, we derive second order hydrodynamic traffic models from k...
04/02/2017

The Stixel world: A medium-level representation of traffic scenes

Recent progress in advanced driver assistance systems and the race towar...
04/07/2018

Drive Video Analysis for the Detection of Traffic Near-Miss Incidents

Because of their recent introduction, self-driving cars and advanced dri...
12/23/2020

A Survey of Recent Developments in Collision Avoidance, Collision Warning and Inter-Vehicle Communication Systems

This paper presents the state-of-the-art on Collision Avoidance and Coll...
10/31/2018

A speech-based driver assisting module for Intelligent Transport System

Aim of this research is to transform images of roadside traffic panels t...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.