Ego-lane estimation by modeling lanes and sensor failures

Published in 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC), 2017

Recommended citation: ballardini2017b

Abstract. In this paper we present a probabilistic lane-localization algorithm for highway-like scenarios designed to increase the accuracy of the vehicle localization estimate. The contribution relies on a Hidden Markov Model (HMM) with a transient failure model. The idea behind the proposed approach is to exploit the availability of OpenStreetMap road properties in order to reduce the localization uncertainties that would result from relying only on a noisy line detector, by leveraging consecutive, possibly incomplete, observations. The algorithm effectiveness is proven by employing a line detection algorithm and showing we could achieve a much more usable, i.e., stable and reliable, lane-localization over more than 100Km of highway scenarios, recorded both in Italy and Spain. Moreover, as we could not find a suitable dataset for a quantitative comparison of our results with other approaches, we collected datasets and manually annotated the Ground Truth about the vehicle ego-lane. Such datasets are made publicly available for usage from the scientific community.

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Recommended citation: @INPROCEEDINGS{8317834, author={A. L. {Ballardini} and D. {Cattaneo} and R. {Izquierdo} and I. {Parra} and M. A. {Sotelo} and D. G. {Sorrenti}}, booktitle={2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC)}, title={Ego-lane estimation by modeling lanes and sensor failures}, year={2017}, volume={}, number={}, pages={1-7}, keywords={hidden Markov models;object detection;probability;road traffic;road vehicles;traffic engineering computing;vehicle localization estimate;Hidden Markov Model;transient failure model;OpenStreetMap road properties;localization uncertainties;noisy line detector;line detection algorithm;stable lane-localization;reliable lane-localization;vehicle ego-lane;ego-lane estimation;sensor failures;probabilistic lane-localization algorithm;Roads;Estimation;Hidden Markov models;Detectors;Reliability;Probabilistic logic}, doi={10.1109/ITSC.2017.8317834}, ISSN={2153-0017}, month={Oct},}