A novel technique for optimal vehicle routing

This paper proposes a novel approach in finding an optimal solution for vehicle routing. The intention here is to find the shortest time path between different points. Dijkstra's algorithm is a very popular technique used in communication networks for data routing and in path planning of robots. Normally the implementation of Dijkstra's algorithm involves initialization of weights depending upon a particular cost metric, namely, distance. Based on an analysis of these weights, a choice of right path is made. This conventional approach states that the shortest path will take minimum time to travel. However this may not always be true. Even depending on the traffic conditions prevailing at that particular instant, the time taken may vary. The proposed work takes into consideration the traffic density in a particular path which influences the time taken for travel and then suggests an optimal path. The results are validated using concepts of Object Oriented Programming and tested in a hardware environment using PIC16F877a micro controller.

[1]  Phaneendra Kumar,et al.  Traffic Control Using Digital Image Processing , 2013 .

[2]  Bing-Fei Wu,et al.  Embedded Driver-Assistance System Using Multiple Sensors for Safe Overtaking Maneuver , 2014, IEEE Systems Journal.

[3]  Christos Makris,et al.  An information system for the effective management of ambulances , 2000, Proceedings 13th IEEE Symposium on Computer-Based Medical Systems. CBMS 2000.

[4]  Phil Blythe,et al.  Routing systems to extend the driving range of electric vehicles , 2013 .

[5]  Victor C. M. Leung,et al.  Position-Based Directional Vehicular Routing , 2009, GLOBECOM 2009 - 2009 IEEE Global Telecommunications Conference.

[6]  Ming-Der May,et al.  Location-routing based Dynamic Vehicle Routing Problem for express pick-up service , 2008, 2008 IEEE International Conference on Industrial Engineering and Engineering Management.

[7]  Reza Tavakkoli-Moghaddam,et al.  Multiobjective Dynamic Vehicle Routing Problem With Fuzzy Travel Times and Customers’ Satisfaction in Supply Chain Management , 2013, IEEE Transactions on Engineering Management.

[8]  H Lieu,et al.  TRAFFIC-FLOW THEORY , 1999 .

[9]  Feng Lu,et al.  A practical route guidance approach based on historical and real-time traffic effects , 2009, 2009 17th International Conference on Geoinformatics.

[10]  Chu-Hsing Lin,et al.  Genetic Algorithm for Shortest Driving Time in Intelligent Transportation Systems , 2008, 2008 International Conference on Multimedia and Ubiquitous Engineering (mue 2008).

[11]  Andrea Baiocchi,et al.  Infotainment traffic flow dissemination in an urban VANET , 2012, 2012 IEEE Global Communications Conference (GLOBECOM).

[12]  Li Jun,et al.  Vehicle routing problem in dynamic urban traffic network , 2011, ICSSSM11.

[13]  Zati Aqmar Zaharudin,et al.  Finding shortest path of the ambulance routing: Interface of A∗ algorithm using C# programming , 2012, 2012 IEEE Symposium on Humanities, Science and Engineering Research.

[14]  K. Athavan,et al.  Automatic Ambulance Rescue System , 2012, 2012 Second International Conference on Advanced Computing & Communication Technologies.

[15]  Yuejin Tan,et al.  Notice of violation of ieee publication principles Dynamic vehicle routing and scheduling with variable travel times in intelligent transportation system , 2006, WCICA 2006.

[16]  D. Sutariya,et al.  An improved AODV routing protocol for VANETs in city scenarios , 2012, IEEE-International Conference On Advances In Engineering, Science And Management (ICAESM -2012).