A novel algorithm to identifying vehicle travel path in elevated road area based on GPS trajectory data

Abstract

In recent years, the increasing development of traffic information collection technology based on floating car data has been recognized, which gives rise to the establishment of real-time traffic information dissemination system in many cities. However, the recent massive construction of urban elevated roads hinders the processing of corresponding GPS data and further extraction of traffic information (e.g., identifying the real travel path), as a result of the frequent transfer of vehicles between ground and elevated road travel. Consequently, an algorithm for identifying the travel road type (i.e., elevated or ground road) of vehicles is designed based on the vehicle traveling features, geometric and topological characteristics of the elevated road network, and a trajectory model proposed in the present study. To be specific, the proposed algorithm can detect the places where a vehicle enters, leaves or crosses under elevated roads. An experiment of 10 sample taxis in Shanghai, China was conducted, and the comparison of our results and results that are obtained from visual interpretation validates the proposed algorithm.

Keywords

GPS trajectory / vehicle status identification / trajectory segmentation / road network modeling / elevated road

References

[1] Calabrese F, Colonna M, Lovisolo P (2010). Real time Rome urban monitoring using cell phones: a case study in Rome. IEEE Trans Intell Transp Syst, 12(1): 141–151

[2] Cowan K, Gates G (2002). Floating vehicle data system—a smart move. In: Proceedings of 9th World Congress on Intelligent Transport Systems. Chicago Illinois, USA, from October 14–17, 2002

[3] Najjar M E, Bonnifait P (2005). A road-matching method for precise vehicle localization using Belief theory and Kalman filtering. Autonomous Robots, 19(2): 173–191

[4] Greenfeld J S (2002). Matching GPS observations to locations on a digital map. In: Proceedings of the 81st Annual Meeting of the Transportation Research Board, January, Washington D.C

[5] Li J, Zuo L (2004). Shanghai urban elevated roads and metropolis traffic. Urban Roads Bridges & Flood Control, 21(6): 14–17 (in Chinese)

[6] Lin Z X, Wu Z, Yang C H (2010). A study on traffic flow models based on measure video of Yan’an Expressway of Shanghai.Journal of Hydrodynamics (Series A), 25(5): 683–693 (in Chinese)

[7] Obradovic D, Lenz H, Schupfner M (2006). Fusion of map and sensor data in a modern car navigation system. The Journal of VSLI Signal Processing, 45(1–2): 112–122

[8] Ochieng W Y, Quddus M A, Noland R B (2003). Map-matching in complex urban road networks.Brazilian Journal of Cartography, 55(2): 1–18

[9] Quddus M A, Noland R B, Ochieng W Y (2006). A high accuracy fuzzy logic-based map-matching algorithm for road transport. Journal of Intelligent Transportation Systems: Technology, Planning, and Operations, 10(3): 103–115

[10] Quddus M A, Ochieng W Y, Noland R B (2007). Current map-matching algorithms for transport applications: state-of-the art and future research directions. Transp Res, Part C Emerg Technol, 15(5): 312–328

[11] Wang L (2006). Study on key technologies of floating-car system. Dissertation for Doctorial Degree. Beijing: Beijing University of Aeronautics and Astronautics (in Chinese)

[12] Wang M L, Cheng L (2012). Study on map matching algorithm for floating car. Acta Geodaetica et Cartographica Sinica, 41(1): 133–138 (in Chinese)

[13] Wang W (2011). Traffic Engineering. Nanjing: South East University Press (in Chinese)

[14] White C E, Bernstein D, Kornhauser A L (2000). Some map-matching algorithms for personal navigation assistants. Transportation Research Part C, 8(1–6): 91–108

[15] Yoon J, Noble B, Liu M (2007). Surface street traffic estimation. In: MobiSys’07 Proceedings of the 5th International Conference on Mobile Systems, Applications and Services, New York: ACM, 220–232

[16] Zhang C B, Yang X G, Yan X P (2006). Traffic data collection system based on floating cars. Comput Commun, 24(5): 31–34 (in Chinese)

[17] Zhang Y M (2004). The thinking of relieving the congestion of elevated road system. Traffic and Transportation, (5): 37–38 (in Chinese)

RIGHTS & PERMISSIONS

2014 Higher Education Press and Springer-Verlag Berlin Heidelberg