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

机译:探索一种基于电气建模的车辆引导路线规划

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摘要

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.
机译:这项工作描述了一种新型的基于电气建模的路线规划器(EMBRP),用于城市街道网络(地图)内的车辆引导,它使用等效的线性电路,考虑交通流向、长度和街道的其他物理属性作为电路分支电阻数学模型的参数。因此,将城市建模为电路会产生线性方程组,该方程组使用非对称多面包 (UMFPACK) 库中实现的多面方法进行求解。此外,该文还提出了一种改进的局部电流比较算法(MLCCA),旨在找到满足正确交通流向的合适路径。EMBRP 具有接受用户定义的符号模型的功能,这些模型来自从公共数据库中提取的街道参数,允许不同的路线规划应用。例如,可以探索低风险的路线规划方案,也可以探索具有多个起点的路线,并且可以仅使用单个模拟来绘制单个目的地,以及其他可能性。EMBRP通过对九个真实案例研究的描述来说明。根据所得到的结果,该方案实现了合适的规划路线和较小的计算时间。该文对EMPRP、启发式A*算法和Hspice数值引擎进行了内存消耗和计算时间的性能比较。EMPRP实现了最短的计算时间。EMBRP 对于研究特定应用的路线规划技术和新街道模型的工程师和研究人员非常有用。

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