Exemplar Trajectory Generation for Prior Driving Experience Re-Usage in Autonomous Driving | IEEE Conference Publication | IEEE Xplore

Exemplar Trajectory Generation for Prior Driving Experience Re-Usage in Autonomous Driving


Abstract:

It is evident that High-Definition Maps (HD Maps) are key enablers of autonomous driving systems, since they enable them to understand the nearby road structure in order ...Show More

Abstract:

It is evident that High-Definition Maps (HD Maps) are key enablers of autonomous driving systems, since they enable them to understand the nearby road structure in order to generate a localized corridor. However, the huge cost incurred in creating and maintaining HD Maps is being recognized as a big challenge. To deal with this problem, some researchers have been studying HD Map independent approaches such as online corridor estimation. They tend to require optimistic observations such as tracklets of surrounding vehicles. In this paper, we consider the use of self-driven trajectories, because they represent strong evidence that ego-vehicle could travel along. Based on this consideration, a concept of exemplary trajectory (or exemplar) generation by recombining parts of different trajectories is introduced. The recombination is achieved using genetic algorithm followed by a final selection. The crossover and selection operators are designed to preserve characteristics of parents; with the possibility to simultaneously maintain multiple exemplars covering different lanes. The final selection eliminates redundancy and provides the minimum set of exemplars. Our implementation demonstrated the effectiveness and usefulness of the proposed method.
Date of Conference: 11-17 July 2021
Date Added to IEEE Xplore: 01 November 2021
ISBN Information:
Conference Location: Nagoya, Japan

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