Exploring a Novel Electrical-Modeling-Based Route Planning for Vehicle Guidance

Rogelio Alejandro Callejas-Molina,Hector Vazquez-Leal,Darwin Mayorga-Cruz,Javier Diaz-Carmona,Raul Lopez-Leal

doi:10.1155/2020/4348964

Abstract

This work describes a novel Electrical-Modeling-Based Route Planner (EMBRP) for vehicle guidance within city street networks (maps), which uses an equivalent linear electrical circuit considering traffic flow direction, length, and other physical attributes of the streets as parameters for the mathematical model of the circuit branch resistances. Thus, modeling a city as an electrical circuit results in a system of linear equations, which are solved using a multifrontal method implemented in the Unsymmetric Multifrontal Pack (UMFPACK) library. In addition, a Modified Local Current Comparison Algorithm (MLCCA) is proposed with the aim to find a suitable route meeting the correct traffic flow direction. The EMBRP has the functionality to accept user-defined symbolic models in terms of street parameters extracted from a public database allowing different route planning applications. For instance, low-risk route planning schemes can be explored also routes with multiple origins and a single destination can be plotted using only a single simulation, among other possibilities. The EMBRP is illustrated through the description of nine real case studies. According to the obtained results, suitable planning routes and small computing times are achieved by this proposal. A performance comparison, in terms of memory consumption and computing time, among EMBRP, the heuristic A∗ algorithm and Hspice numeric engine is presented. The smallest computing time was achieved by the EMBRP. The EMBRP can be useful for engineers and researchers studying route planning techniques and new street models for specific applications.

Highlights

In last decades many solutions for vehicular flow in city street networks have been addressed in reported works
It is important to point out that these reported methods are focused on minimizing the travel time between the origin and destination positions with defined vehicle flow conditions and using a fixed proposed model, but neither geographical and cartography data nor physical characteristics of the city network streets are taken into account. is article presents an alternative methodology to the traditional route planning methods based on graphs (Dijkstra [7] and A∗ [8]) and optimization methods. e article is focused on planning a city route by establishing an analogy of the behavior between the vehicular flow presented in city street networks and the current flow in electrical circuits
Conclusions e described Electrical-Modeling-Based Route Planning (EMBRP) is based on an analogy between a city street network and a linear electrical circuit. e resulting route is achieved by searching the branches having the local maximum branch currents within the electrical circuit, where the branch resistance values are defined from street physical characteristics obtained from [17]

Summary

Introduction

In last decades many solutions for vehicular flow in city street networks have been addressed in reported works. An equivalent electrical resistive circuit is obtained from city street database, where street physical characteristics are used for modeling the branch resistors value. (ii) A modification to the Local Current Comparison Algorithm (LCCA) is proposed in the EMBRP so that routes containing one- and two-way streets are represented as linear resistances in the equivalent electrical circuit, in contrast to other reported techniques that use nonlinear components, which notably increases the computational workload in the route planning. Some reported planning methods are limited to specific case studies, the EMBRP implementation includes street information extraction from any city map available in a public database [17] for parsing an equivalent linear electric circuit, where the resistances values are computed from real street physical characteristics. Once the operating point of the electrical circuit is known, the resulting route is sequentially obtained using MLCCA (Section 3.5) and displayed using [32]

Illustrative Example

Result

Discussion and Numerical

Case Studies