Sökning: L773:2379 8858 > Lane-Level Map Matc...
Fältnamn | Indikatorer | Metadata |
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000 | 03298naa a2200493 4500 | |
001 | oai:research.chalmers.se:94554e0a-a4b2-4bdc-833e-2053929bb3f8 | |
003 | SwePub | |
008 | 201024s2021 | |||||||||||000 ||eng| | |
024 | 7 | a https://research.chalmers.se/publication/5200852 URI |
024 | 7 | a https://doi.org/10.1109/TIV.2020.30353292 DOI |
024 | 7 | a https://research.chalmers.se/publication/5252772 URI |
040 | a (SwePub)cth | |
041 | a engb eng | |
042 | 9 SwePub | |
072 | 7 | a art2 swepub-publicationtype |
072 | 7 | a ref2 swepub-contenttype |
100 | 1 | a Hansson, Andersu Zenuity AB4 aut |
245 | 1 0 | a Lane-Level Map Matching based on HMM |
264 | 1 | c 2021 |
338 | a electronic2 rdacarrier | |
520 | a Lane-level map matching is essential for autonomous driving. In this paper, we propose a Hidden Markov Model (HMM) for matching a trajectory of noisy GPS measurements to the road lanes in which the vehicle records its positions. To our knowledge, this is the first time that HMM is used for lanelevel map matching. Apart from GPS values, the model is further assisted by yaw rate data (converted to a lane change indicator signal) and visual cues in the form of the left and right lane marking types (dashed, solid, etc.). Having defined expressions for the HMM emission and transition probabilities, we evaluate our model to demonstrate that it achieves 95.1% recall and 3.3% median path length error for motorway trajectories. | |
650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Annan data- och informationsvetenskap0 (SwePub)102992 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Other Computer and Information Science0 (SwePub)102992 hsv//eng |
650 | 7 | a TEKNIK OCH TEKNOLOGIERx Annan teknik0 (SwePub)2112 hsv//swe |
650 | 7 | a ENGINEERING AND TECHNOLOGYx Other Engineering and Technologies0 (SwePub)2112 hsv//eng |
650 | 7 | a NATURVETENSKAPx Matematikx Sannolikhetsteori och statistik0 (SwePub)101062 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Mathematicsx Probability Theory and Statistics0 (SwePub)101062 hsv//eng |
650 | 7 | a NATURVETENSKAPx Data- och informationsvetenskapx Datavetenskap0 (SwePub)102012 hsv//swe |
650 | 7 | a NATURAL SCIENCESx Computer and Information Sciencesx Computer Sciences0 (SwePub)102012 hsv//eng |
653 | a map matching | |
653 | a Viterbi algorithm | |
653 | a road networks | |
653 | a lane-level map matching | |
653 | a hidden Markov model | |
700 | 1 | a Korsberg, Ellenu Chalmers tekniska högskola,Chalmers University of Technology4 aut |
700 | 1 | a Maghsood, Rozau Zenuity AB4 aut |
700 | 1 | a Nordén, Elizau Chalmers tekniska högskola,Chalmers University of Technology4 aut |
700 | 1 | a Selpi, Selpi,d 1977u Chalmers tekniska högskola,Chalmers University of Technology4 aut0 (Swepub:cth)selpi |
710 | 2 | a Zenuity ABb Chalmers tekniska högskola4 org |
773 | 0 | t IEEE Transactions on Intelligent Vehiclesg 6:3, s. 430-439q 6:3<430-439x 2379-8858 |
856 | 4 | u https://research.chalmers.se/publication/525277/file/525277_Fulltext.pdfx primaryx freey FULLTEXT |
856 | 4 8 | u https://research.chalmers.se/publication/520085 |
856 | 4 8 | u https://doi.org/10.1109/TIV.2020.3035329 |
856 | 4 8 | u https://research.chalmers.se/publication/525277 |
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