Road course estimation in unknown, structured environments

Georg Tanzmeister, Martin Friedl, Andreas Lawitzky, Dirk Wollherr, Martin Buss

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

14 Scopus citations


The road course is an essential feature for many driver assistance systems and for autonomously-maneuvering vehicles. It is commonly stored in a map and hence assumed to be known a-priori. There are however situations in which the map data can become invalid, such as in road construction sites. In other situations, localization in the map might not be accurate enough, which can happen, for example, in dense urban areas. In this work, a novel approach to road course estimation is presented that is based on path planning through grid maps under non-holonomic and velocity constraints. With this approach, it is possible to estimate the road boundaries on a wide range of roads, including roads with continuous as well as discontinuous borders, roads exhibiting strong curvatures or S-shapes and road junctions. Furthermore, a plausibility measure is given to validate the road course and it is shown how the road center can be smoothed.

Original languageEnglish
Title of host publication2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
Number of pages6
StatePublished - 2013
Event2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013 - Gold Coast, QLD, Australia
Duration: 23 Jun 201326 Jun 2013

Publication series

NameIEEE Intelligent Vehicles Symposium, Proceedings


Conference2013 IEEE Intelligent Vehicles Symposium, IEEE IV 2013
CityGold Coast, QLD


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