CPL - Chalmers Publication Library
| Utbildning | Forskning | Styrkeområden | Om Chalmers | In English In English Ej inloggad.

A Probabilistic Framework for Decision-Making in Collision Avoidance Systems

Mattias Brännström ; Fredrik Sandblom (Institutionen för signaler och system, Signalbehandling) ; Lars Hammarstrand (Institutionen för signaler och system, Signalbehandling)
IEEE transactions on intelligent transportation systems (1524-9050). Vol. 14 (2013), 2, p. 637-648.
[Artikel, refereegranskad vetenskaplig]

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.

Nyckelord: Automotive safety; collision avoidance (CA); decision-making; driver modeling; threat assessment



Den här publikationen ingår i följande styrkeområden:

Läs mer om Chalmers styrkeområden  

Denna post skapades 2013-06-28. Senast ändrad 2014-11-27.
CPL Pubid: 179445

 

Läs direkt!


Länk till annan sajt (kan kräva inloggning)