DocumentCode :
1492966
Title :
Model-Based Threat Assessment for Avoiding Arbitrary Vehicle Collisions
Author :
Brännström, Mattias ; Coelingh, Erik ; Sjöberg, Jonas
Author_Institution :
Dept. of Vehicle Dynamics & Active Safety, Volvo Car Corp., Gothenburg, Sweden
Volume :
11
Issue :
3
fYear :
2010
Firstpage :
658
Lastpage :
669
Abstract :
This paper presents a model-based algorithm that estimates how the driver of a vehicle can either steer, brake, or accelerate to avoid colliding with an arbitrary object. In this algorithm, the motion of the vehicle is described by a linear bicycle model, and the perimeter of the vehicle is represented by a rectangle. The estimated perimeter of the object is described by a polygon that is allowed to change size, shape, position, and orientation at sampled time instances. Potential evasive maneuvers are modeled, parameterized, and approximated such that an analytical expression can be derived to estimate the set of maneuvers that the driver can use to avoid a collision. This set of maneuvers is then assessed to determine if the driver needs immediate assistance to avoid or mitigate an accident. The proposed threat-assessment algorithm is evaluated using authentic data from both real traffic conditions and collision situations on a test track and by using simulations with a detailed vehicle model. The evaluations show that the algorithm outperforms conventional threat-assessment algorithms at rear-end collisions in terms of the timing of autonomous brake activation. This is crucial for increasing the performance of collision-avoidance systems and for decreasing the risk of unnecessary braking. Moreover, the algorithm is computationally efficient and can be used to assist the driver in avoiding or mitigating collisions with all types of road users in all kinds of traffic scenarios.
Keywords :
collision avoidance; motion control; road traffic; road vehicles; arbitrary vehicle collision avoidance; autonomous brake activation; evasive maneuvers; linear bicycle model; model-based threat assessment; rear-end collisions; vehicle motion; Acceleration; Bicycles; Collision mitigation; Computational modeling; Remotely operated vehicles; Road accidents; Shape; Testing; Traffic control; Vehicle driving; Automotive safety; collision avoidance (CA); intersection collisions; rear-end collisions; threat assessment;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2010.2048314
Filename :
5466072
Link To Document :
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