Multi-ordered short-range mover prediction models for tracking and avoidance

Overstreet, Jamahl; Khorrami, Farshad

doi:10.1109/cdc.2012.6425831

Cited by 1 publication

(1 citation statement)

References 13 publications

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“…This is not the scope of this work, since we aim at computing evasive maneuvers that are guaranteed safe. Alternatives to Monte Carlo simulation are Markov chains [22], linearizations representing different operation modes in combination with Gaussian distributions [7], [23], Bayesian occupancy filters [24], and multiordered prediction models [25].…”

Section: Introductionmentioning

confidence: 99%

Road occupancy prediction of traffic participants

Althoff

Hess

Gambert

2013

16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013)

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We predict the road occupancy of traffic participants for collision avoidance systems. The occupancy sets are computed for consecutive time intervals and contain all reachable positions of traffic participants in compliance with a proposed dynamic model. Those sets make it possible to check if planned emergency maneuvers are collision-free in all possible future scenarios. However, no algorithm exists for exactly computing the occupancy when the model forbids unrealistic behavior such as leaving road boundaries or largely exceeding speed limits. For this reason, we provide methods to tightly overapproximate occupancy sets to ensure safe emergency maneuvers. We demonstrate the applicability of the approach by numerical examples, which show that the occupancy computation is not only efficient, but also tight enough to trigger emergency maneuvers almost at the last possible point in time.

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