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

机译:探索车辆指导的新型电气建模路线规划

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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的电气建模的路线规划员(COMB),用于城市街道网络(地图)内的车辆指导,其使用考虑交通流向,长度和街道的其他物理属性作为参数的等效线性电路电路分支电阻的数学模型。因此,将城市建模作为电路导致线性方程的系统,其使用在非对手多重包装(UMFPACK)库中实现的多重载体方法来解决。另外,提出了一种修改的局部电流比较算法(MLCCA),目的是找到满足正确的交通流向的合适路由。 elsp具有在从公共数据库中提取的街道参数中接受用户定义符号模型的功能,允许不同的路由计划应用程序。例如,可以探索低风险路线规划方案,也可以仅使用多个起源和单个目的地的路由,并且可以仅使用单个模拟绘制单个目的地。通过描述九个实际案例研究的描述说明了植物。根据所获得的结果,通过该提议实现了合适的规划路线和小型计算时间。在内存消耗和计算时间方面,在植物中的绩效比较,启发式A?呈现算法和HSPICE数字引擎。最小的计算时间是由植物实现的。 COMBRP对于研究路线规划技术和新街道模型的工程师和研究人员可用于特定应用。

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