Multi-Source Data Integration-Based Urban Road GPS Environment Friendliness Estimation

In urban areas, multipath errors may occur due to blockage and reflection of GPS signals by buildings, and significantly reduce the accuracy of GPS positioning. The degree to which the environment causes multipath errors and negatively impacts GPS accuracy is referred to as GPS Environment Friendliness (GEF) in this paper. The estimation of GEF helps location-based-service remind users to reduce the psychological expectation of GPS accuracy when they enter a poor GEF area. While existing studies estimate the GEF only based on the vehicle trajectory data, we propose a more efficient matrix completion-based approach that uses the historical bus trajectory data with the integration of the building layout information and road tag information. Based on one month GPS trajectory data of 4835 buses within the second ring road in Chengdu, China, we estimate the GEF of 8831 different road segments and verify the rationality of the results by satellite maps, street views, and field tests.

[1]  Arkadiusz Stopczynski,et al.  Tracking Human Mobility Using WiFi Signals , 2015, PloS one.

[2]  Muhammad Tayyab Asif,et al.  Online map-matching based on Hidden Markov model for real-time traffic sensing applications , 2012, 2012 15th International IEEE Conference on Intelligent Transportation Systems.

[3]  Minglu Li,et al.  A Compressive Sensing Approach to Urban Traffic Estimation with Probe Vehicles , 2013, IEEE Transactions on Mobile Computing.

[4]  Jean-Yves Tourneret,et al.  A Particle Filtering Approach for Joint Detection/Estimation of Multipath Effects on GPS Measurements , 2007, IEEE Transactions on Signal Processing.

[5]  Suman Nath,et al.  Gnome: A Practical Approach to NLOS Mitigation for GPS Positioning in Smartphones , 2018, MobiSys.

[6]  Raymond H. Putra,et al.  Map matching with Hidden Markov Model on sampled road network , 2012, Proceedings of the 21st International Conference on Pattern Recognition (ICPR2012).

[7]  John Krumm,et al.  Hidden Markov map matching through noise and sparseness , 2009, GIS.

[8]  Cezary Specht,et al.  Accuracy Of The GPS Positioning System In The Context Of Increasing The Number Of Satellites In The Constellation , 2015 .

[9]  Achiya Dax,et al.  Imputing Missing Entries of a Data Matrix: A review , 2014 .

[10]  Martin Pielot,et al.  GNSS quality in pedestrian applications - a developer perspective , 2008, 2008 5th Workshop on Positioning, Navigation and Communication.

[11]  Shunsuke Kamijo,et al.  GPS multipath detection and rectification using 3D maps , 2013, 16th International IEEE Conference on Intelligent Transportation Systems (ITSC 2013).

[12]  Wang Yasha,et al.  Evaluation of GPS-Environment Friendliness of Roads Based on Bus Trajectory Data , 2016 .

[13]  Chengyang Zhang,et al.  Map-matching for low-sampling-rate GPS trajectories , 2009, GIS.

[14]  Jay A. Farrell,et al.  Real-Time Computer Vision/DGPS-Aided Inertial Navigation System for Lane-Level Vehicle Navigation , 2012, IEEE Transactions on Intelligent Transportation Systems.

[15]  Robert B. Noland,et al.  Current map-matching algorithms for transport applications: State-of-the art and future research directions , 2007 .

[16]  Weiwei Sun,et al.  Is only one gps position sufficient to locate you to the road network accurately? , 2016, UbiComp.

[17]  Weiwei Sun,et al.  CLSTERS: A General System for Reducing Errors of Trajectories Under Challenging Localization Situations , 2017, Proc. ACM Interact. Mob. Wearable Ubiquitous Technol..

[18]  Nobuaki Kubo,et al.  Multipath mitigation and NLOS detection using vector tracking in urban environments , 2015, GPS Solutions.

[19]  Otman A. Basir,et al.  GPS Localization Accuracy Classification: A Context-Based Approach , 2013, IEEE Transactions on Intelligent Transportation Systems.

[20]  George P. Gerdan,et al.  The Influence of the Number of Satellites on the Accuracy of RTK GPS Positions , 1999 .

[21]  Marko Modsching,et al.  Field trial on GPS Accuracy in a medium size city: The influence of built- up 1 , 2006 .

[22]  Agus Budiyono,et al.  Principles of GNSS, Inertial, and Multi-sensor Integrated Navigation Systems , 2012 .

[23]  Raja Sengupta,et al.  Kalman Filter-Based Integration of DGPS and Vehicle Sensors for Localization , 2005, IEEE Transactions on Control Systems Technology.

[24]  Scott Duncan,et al.  Dynamic Accuracy of GPS Receivers for Use in Health Research: A Novel Method to Assess GPS Accuracy in Real-World Settings , 2014, Front. Public Health.

[25]  Weiwei Sun,et al.  PRESS: A Novel Framework of Trajectory Compression in Road Networks , 2014, Proc. VLDB Endow..