Road infrastructure indicators for trajectory prediction

Geetank Raipuria, Floris Gaisser, Pieter P. Jonker

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review

3 Citations (Scopus)

Abstract

Safe and comfortable path planning in a dynamic urban environment is essential to an autonomous vehicle. This requires the future trajectories of all other road users in the environment of the vehicle. These trajectories are predicted through modeling the motion and behaviour of these road users. In this work we state that for efficient trajectory prediction only motion indicators are not sufficient. Therefore, we propose using a curvilinear coordinate system with curvature as road infrastructure indicators to improve motion modeling and trajectory prediction. With experiments, we show that the curvilinear coordinate system with curvature sufficiently incorporates the road structure. Furthermore, we show that a sequence-tosequence RNN model is suitable to incorporate road curvature indicators directly into the modeling and prediction.

Original languageEnglish
Title of host publication2018 IEEE Intelligent Vehicles Symposium (IV 2018)
Place of PublicationPiscataway, NJ, USA
PublisherIEEE
Pages537-543
ISBN (Electronic)9781538644522
DOIs
Publication statusPublished - 2018
Event2018 IEEE Intelligent Vehicles Symposium, IV 2018 - Changshu, Suzhou, China
Duration: 26 Sep 201830 Sep 2018

Conference

Conference2018 IEEE Intelligent Vehicles Symposium, IV 2018
Country/TerritoryChina
CityChangshu, Suzhou
Period26/09/1830/09/18

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