A margin-based approach to vehicle threat assessment
by Alexandre Constantin; Junghee Park; Karl Iagnemma
International Journal of Vehicle Autonomous Systems (IJVAS), Vol. 12, No. 4, 2014

Abstract: In this paper we propose a novel approach to the threat assessment problem for Advanced Driver Assistance System (ADAS) and autonomous navigation decision making support. This threat assessment is based on estimation of the control margin afforded to a vehicle and is performed in a multi-threat framework. Given sensor information available about the surrounding environment, an algorithm first identifies corridors of travel through which the vehicle can safely navigate. The second stage then assesses the threat posed to the vehicle in each identified corridor via a metric associated with available control margin. For this purpose, the corridors are approximated by sets of trajectories generated from a lattice sampled in the vehicle's input space. The level of threat can then serve to influence autonomous navigation as an input to a decision-making layer. It also potentially allows a semi-autonomous control system to honour driver intent while ensuring safe and robust navigation in hazardous events. The benefit of such an approach is compared to common threat metrics in canonical scenarios. The method is also applied to the multi-lane road environment of highway navigation by post processing human driving data gathered from a simulator.

Online publication date: Sat, 07-Mar-2015

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.

Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Vehicle Autonomous Systems (IJVAS):
Login with your Inderscience username and password:

Username:        Password:          Forgotten your password?

Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.

If you still need assistance, please email subs@inderscience.com