Abstract:
An evaluation of sensor and function performance of an automated driving system as well as behavior analysis in certain situations are important steps on the road to auto...Show MoreMetadata
Abstract:
An evaluation of sensor and function performance of an automated driving system as well as behavior analysis in certain situations are important steps on the road to automated driving. The prerequisite is the filtering of relevant situations with an automated and reliable offline classification of maneuvers in large amounts of driving environment data. In this paper, a dual approach for detecting lane changes in laser scanner environment data is presented and evaluated. It uses two classifiers combined, a probabilistic and one based on fuzzy logic, leading to a higher confidence of the results with lower false positive detections. In addition, different probabilistic methods for the former classifier are compared and evaluated.
Published in: 2017 IEEE Intelligent Vehicles Symposium (IV)
Date of Conference: 11-14 June 2017
Date Added to IEEE Xplore: 31 July 2017
ISBN Information: