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Potential Enhancement for Wrong-way Driver Detection using Precise Attribute Information

Published online by Cambridge University Press:  14 August 2019

Jinyue Wang Open the ORCID record for Jinyue Wang [Opens in a new window] ,
Martin Metzner  and
Volker Schwieger
Jinyue Wang*
Affiliation:
(University of Stuttgart, Institute of Engineering Geodesy, Germany)
Martin Metzner
Affiliation:
(University of Stuttgart, Institute of Engineering Geodesy, Germany)
Volker Schwieger
Affiliation:
(University of Stuttgart, Institute of Engineering Geodesy, Germany)
*
(E-mail: jinyue.wang@iigs.uni-stuttgart.de)
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Abstract

Map-matching is widely used in automotive navigation systems to locate vehicle positions on a given digital road map. Various map-matching algorithms have been developed focusing on different application needs. Within the Ghosthunter project, a weighting-function-based map-matching algorithm has been developed for detecting wrong-way driving in order to improve road safety, particularly in Autobahn entrance and exit areas. This paper aims at exploring the potential use of lane-level attributes and height data in improving the success rate of the previously presented algorithm. This algorithm performs well in entrance and exit areas to the Autobahn, with a high success rate of 99.5% in identifying the road on which the vehicle is actually travelling. In the enhanced algorithm presented in this paper the weight coefficients used for computing the total weighting score of candidate roads are adjusted with the aid of one or both kinds of these precise data. The results confirmed that the usage of these precise data can effectively help to detect and correct mismatches at junctions and overpasses.

Keywords

Map-matchingGNSSLane-level attributeHeight data
Type
Research Article
Information
The Journal of Navigation , Volume 73 , Issue 2 , March 2020 , pp. 384 - 397
Copyright
Copyright © The Royal Institute of Navigation 2019

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References

REFERENCES

Babic, S. and Valic, M.I. (2010). Proposal for a new method for wrong way detection. http://www.sipronika.si/reference/Clanki/Babic%20et%20al%20ICTS%202010%20clanek.pdf. Accessed 2 December 2015.Google Scholar
Baillemont, G. and Dumas, S. (2017). Wrong-way drivers: detect and warn. Proceedings of 12th ITS European Congress, 19–22 June, Strasbourg, France.Google Scholar
Beckmann, H., Frankl, K., Wang, J., Metzner, M., Schwieger, V., Pany, T. and Eissfeller, B. (2017). Performance comparison of different GNSS-based multi-sensor systems for detecting wrong-way driving on highways. Proceedings of ION GNSS+ Meeting 2017, 25–29 September, Oregon, USA.Google Scholar
Bernstein, D. and Kornhauser, A. (1996): An Introduction to Map Matching for Personal Navigation Assistants. New Jersey TIDE Center, Princeton University.Google Scholar
Blazquez, C., Ries, J., Leon, R. and Miranda, P. (2017). Towards a Parameter Tuning Approach for a Map-Matching Algorithm. Proceedings of 2017 IEEE International Conference on Vehicular Electronics and Safety (ICVES), 27–28 June 2017, Vienna, Austria.CrossRefGoogle Scholar
Blazquez, C., Ries, J., Leon, R. and Miranda, P. (2018). An Instance-Specific Parameter Tuning Approach Using Fuzzy Logic for a Post-Processing Topological Map-Matching Algorithm. Proceedings of IEEE Intelligent Transportation Systems Magazine, 1(1), 87–97.CrossRefGoogle Scholar
Czommer, R. (2000). Efficiency of vehicle-autonomous locating methods based on map matching techniques. Dissertation, the Institute for Applications of Geodesy to Civil Engineering (IAGB), University of Stuttgart, Germany (originally in German).Google Scholar
General German Automobile Club. (2015). Wrong-way driver-tips for cases of emergency. http://www.adac.de/infotestrat/adac-im-einsatz/motorwelt/geisterfahrer.aspx. Accessed April 2015 (originally in German).Google Scholar
Hashemi, M. and Karimi, H.A. (2016). A weight-based map-matching algorithm for vehicle navigation in complex urbahn networks. Journal of Intelligent Transportation Systems, 20(6), 573–590.CrossRefGoogle Scholar
Hassan, W., Birch, P., Young, R. and Chatwin, C. (2013). An improved background segmentation method for ghost removals. Proceedings of SPIE – The International Society for Optical Engineering, March 2013, Burlingame, California, United States.CrossRefGoogle Scholar
HERE. (2015). File GeoDatabase Referencce Manual, v2.6, Proprietary and Confidential, HERE, Chicago, USA.Google Scholar
Krausz, N. (2013). Applying RFID in traffic junction monitoring. Proceedings of Second Conference of Junior Researchers of Civil Engineering, 17–18 June, Budapest, Hungary.Google Scholar
Oran, A. and Jaillet, P. (2013). A Precise Proximity-Weight Formulation for Map Matching Algorithms. Proceedings of 10th IEEE Workshop on Positioning, Navigation and Communication (WPNC), 20–21 March, Dresden, Germany.CrossRefGoogle Scholar
Quddus, M., Ochieng, W.Y. and Noland, R.B. (2007). Current map-matching algorithms for transport applications: State-of-the art and future research directions. Transportation Research, Part C 15, 312–328.Google Scholar
Quddus, M. and Washington, S. (2015). Shortest path and vehicle trajectory aided map-matching for low frequency GPS data. Transportation Research, Part C 55, 328–339.Google Scholar
Velaga, N., Quddus, M. and Bristow, A. (2009). Developing an enhanced weight-based topological map-matching algorithm for intelligent transport systems. Transportation Research Part C: Emerging Technologies, 17(6), 672–683.CrossRefGoogle Scholar
Velaga, N., Quddus, M. and Bristow, A. (2010). Detecting and Correcting Map-Matching Errors in Location-Based Intelligent Transport Systems. Proceedings of 12th WCTR Conference, Lisbon, Portugal.Google Scholar
Vicedo, P. (2006). Prevention and Management of Ghost drivers Incidents on Motorways - the French experience - the contribution of ITS to immediate detection and optimum management of ghost driver incidents. Proceedings of the 13th ITS Word Congress, 8–12 October, London, UK.Google Scholar
Wang, J., Metzner, M. and Schwieger, V. (2017). Weighting-function based map-matching algorithm for a reliable wrong-way driving detection. Proceedings of 12th ITS European Congress, 19–22 June, Strasbourg, France.Google Scholar
Wang, J., Wachsmuth, M., Metzner, M. and Schwieger, V. (2018). Digital Road Maps as Sensor. 176. DVW-Seminar Multisensor Technology: Low-Cost Sensor combination, 13–14 September, Hamburg, Germany (originally in German).Google Scholar