Working Zone Identification for Specialized Micro Transportation Systems Using GPS Tracks

The utilization of Intelligent Transportation System (ITS) technologies often requires modifications to vehicles and/or roadside infrastructure. However, in this paper, we investigate some special transportation cases, which we call Specialized Micro Transportation Systems (SMTS), and find the applications of information technologies for them promise great benefits with simple and quick-to-implement solutions. We focus on working zone identification for two cases from agriculture and road maintenance, respectively. An expert system was developed to recognize harvested area and generate up-to-date field boundaries, using GPS data collected for combine harvesters. Similar rules from the system were adapted for patching zone identification.

[1]  Carolina Burnier,et al.  Intelligent Transportation Systems Benefits, Costs, and Lessons Learned: 2014 Update Report , 2014 .

[2]  Rebecca S McDaniel,et al.  Pavement Patching Practices , 2014 .

[3]  Miad Faezipour,et al.  Progress and challenges in intelligent vehicle area networks , 2012, Commun. ACM.

[4]  Rebecca S McDaniel,et al.  National Cooperative Highway Research Program, NCHRP Synthesis 463, Pavement Patching Practices - A Synthesis of Highway Practice , 2014 .

[5]  Michel Gendreau,et al.  Intelligent Freight Transportation Systems : Assessment and the Contribution of Operations Research , 2009 .

[6]  Lin Yan,et al.  Automated crop field extraction from multi-temporal Web Enabled Landsat Data , 2014 .

[7]  Bruce G. Buchanan,et al.  Principles of Rule-Based Expert Systems , 1982, Adv. Comput..

[8]  Henryk Zähle,et al.  Travel Time Prediction Using Floating Car Data Applied to Logistics Planning , 2011, IEEE Transactions on Intelligent Transportation Systems.

[9]  Curt H. Davis,et al.  An integrated system for automatic road mapping from high-resolution multi-spectral satellite imagery by information fusion , 2005, Inf. Fusion.

[10]  Isaac Skog,et al.  Insurance Telematics: Opportunities and Challenges with the Smartphone Solution , 2014, IEEE Intelligent Transportation Systems Magazine.

[11]  José Eugenio Naranjo,et al.  Modeling the Driving Behavior of Electric Vehicles Using Smartphones and Neural Networks , 2014, IEEE Intelligent Transportation Systems Magazine.

[12]  David G. Kirkpatrick,et al.  On the shape of a set of points in the plane , 1983, IEEE Trans. Inf. Theory.

[13]  J.L. Martins de Carvalho,et al.  Towards the development of intelligent transportation systems , 2001, ITSC 2001. 2001 IEEE Intelligent Transportation Systems. Proceedings (Cat. No.01TH8585).