A Probabilistic Framework for Decision-Making in Collision Avoidance Systems
Artikel i vetenskaplig tidskrift, 2013

This paper is concerned with the problem of decision-making in systems that assist drivers in avoiding collisions. An important aspect of these systems is not only assisting the driver when needed but also not disturbing the driver with unnecessary interventions. Aimed at improving both of these properties, a probabilistic framework is presented for jointly evaluating the driver acceptance of an intervention and the necessity thereof to automatically avoid a collision. The intervention acceptance is modeled as high if it estimated that the driver judges the situation as critical, based on the driver's observations and predictions of the traffic situation. One advantage with the proposed framework is that interventions can be initiated at an earlier stage when the estimated driver acceptance is high. Using a simplified driver model, the framework is applied to a few different types of collision scenarios. The results show that the framework has appealing properties, both with respect to increasing the system benefit and to decreasing the risk of unnecessary interventions.

driver modeling

threat assessment

collision avoidance (CA)

decision-making

Automotive safety

Författare

Mattias Brännström

Volvo

Fredrik Sandblom

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

Lars Hammarstrand

Signaler och system, Signalbehandling och medicinsk teknik, Signalbehandling

IEEE Transactions on Intelligent Transportation Systems

1524-9050 (ISSN)

Vol. 14 637-648

Styrkeområden

Informations- och kommunikationsteknik

Ämneskategorier

Elektroteknik och elektronik

DOI

10.1109/TITS.2012.2227474