Map-Matching Algorithm for Applications in Multimodal Transportation Network Modeling

Generalized Transit Feed Specification (GTFS) files have gained wide acceptance by transit agencies, which now provide them for most major metropolitan areas. The public availability GTFSs combined with the convenience of presenting a standard data representation has promoted the development of numerous applications for their use. Whereas most of these tools are focused on the analysis and utilization of public transportation systems, GTFS data sets are also extremely relevant for the development of multimodal planning models. The use of GTFS data for integrated modeling requires creating a graph of the public transportation network that is consistent with the roadway network. The former is not trivial, given limitations of networks often used for regional planning models and the complexity of the roadway system. A proposed open-source algorithm matches GTFS geographic information to existing planning networks and is also relevant for real-time in-field applications. The methodology is based on maintaining a set of candidate paths connecting successive geographic points. Examples of implementations using traditional planning networks and a network built from crowdsourced OpenStreetMap data are presented. The versatility of the methodology is also demonstrated by using it for matching GPS points from a navigation system. Experimental results suggest that this approach is highly successful even when the underlying roadway network is not complete. The proposed methodology is a promising step toward using novel and inexpensive data sources to facilitate and eventually transform the way that transportation models are built and validated.

[1]  Mark Hickman,et al.  Trip-Based Path Algorithms Using the Transit Network Hierarchy , 2015 .

[2]  Meng Yu Improved positioning of land vehicle in its using digital map and other accessory information , 2006 .

[3]  Xing Xie,et al.  An Interactive-Voting Based Map Matching Algorithm , 2010, 2010 Eleventh International Conference on Mobile Data Management.

[4]  Kay W. Axhausen,et al.  Efficient Map Matching of Large Global Positioning System Data Sets: Tests on Speed-Monitoring Experiment in Zürich , 2005 .

[5]  Mark Hickman,et al.  Intermodal Path Algorithm for Time-Dependent Auto Network and Scheduled Transit Service , 2012 .

[6]  Carola A. Blazquez,et al.  Simple Map-Matching Algorithm Applied to Intelligent Winter Maintenance Vehicle Data: , 2005 .

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

[8]  Jon Louis Bentley,et al.  Multidimensional binary search trees used for associative searching , 1975, CACM.

[9]  Mahmoud,et al.  Issues and Strategies Involved in Developing Agent-Based Multimodal Network Simulation Model for Transportation Planning: Lessons from a Case Study on the Troronto and Hamilton Area , 2013 .

[10]  Ravindra K. Ahuja,et al.  Network Flows: Theory, Algorithms, and Applications , 1993 .

[11]  K. Axhausen,et al.  Map-matching of GPS traces on high-resolution navigation networks using the Multiple Hypothesis Technique (MHT) , 2009 .

[12]  Alexander Erath,et al.  Semi-Automatic Tool for Map-Matching Bus Routes on High-Resolution Navigation Networks , 2011 .

[13]  James Van Velden,et al.  A large-scale multi-modal implementation of MATSim for the Nelson Mandela Bay metropole , 2013 .

[14]  Stephen D. Boyles,et al.  Modeling the Traffic Impacts of Transit Facilities Using Dynamic Traffic Assignment , 2013 .

[15]  Yi-Chang Chiu,et al.  Modeling Transit and Intermodal Tours in a Dynamic Multimodal Network , 2014 .

[16]  Mark Hickman,et al.  Integration of the FAST-TrIPs Person-Based Dynamic Transit Assignment Model, the SF-CHAMP Regional, Activity-Based Travel Demand Model, and San Francisco’s Citywide Dynamic Traffic Assignment Model , 2013 .

[17]  Wolfgang Scherr,et al.  Development of a Regional Forecasting Model Based on Google Transit Feed , 2012 .

[18]  Jing-Quan Li Match bus stops to a digital road network by the shortest path model , 2012 .

[19]  Washington Y. Ochieng,et al.  A general map matching algorithm for transport telematics applications , 2003 .

[20]  Tae-Kyung Sung,et al.  Development of a map matching method using the multiple hypothesis technique , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).

[21]  J. Greenfeld MATCHING GPS OBSERVATIONS TO LOCATIONS ON A DIGITAL MAP , 2002 .

[22]  Abigail L. Bristow,et al.  Developing an Enhanced Weight-Based Topological Map-Matching Algorithm for Intelligent Transport Systems , 2009 .