Navigation methodology for vehicle city route optimal choice

Abstract

Relevance. The study is a fundamentally new approach to such an extremely important problem as the congestions in large cities. The solution of this global problem is a step in the realization of a smart city concept.  

Goal. The aim of the study is to create basic elements of technology that can stabilize urban traffic and bring it to a qualitatively new state. To achieve this goal, the following tasks have been formulated:

– to create a model of a city transport network in the form of an oriented weighted non-planar multigraph with dynamically loaded arcs;

– to activate a city electronic map in the Traffic Management Centre (TMC) which allows tracking each vehicle;

– to navigate the time-optimal routes for all those vehicles that request the route;

– to implement the work of the software algorithm in real time with constant updating of the route of each tracked vehicle. That will allow monitoring changes in city traffic in real time and making adjustments to the route of each vehicle.

Research methods. The research is based on the use of mechanisms for modeling and working with various networks – the graph theory and the A-star algorithm. The latter traces the route on the graph (transport network) between two selected positions of the vehicle graph theory – origin and destination. The heuristic A-star algorithm – a powerful computational method of graph theory has been used in the study. This makes it possible to synchronize vehicles flows and therefore provides a qualitatively new level to the control of urban traffic.

The results. The problem of traffic load registration for the city transport network essential for navigating a vehicle route in metropolis has been solved. Traffic data of the real transport network have been reproduced on the city electronic map. Each vehicle received a unique marker consisting of an origin-destination pair and can be tracked on the map. Since each vehicle is under control of the Traffic Management Center (TMC), it is possible to track it along the optimal route, taking an urban traffic dynamic into account. Support is provided via the General Packet Radio Service (GPRS) channel, which allows each driver to receive instructions as to an optimal travel path.

Conclusions. The study has proposed a working software module that navigates a time-optimized route on the graph that represents the model of the real transport city network.