Planning driving routes is a common yet challenging task. Previous solutions that often suggest the shortest or time-dependent fastest paths for drivers are incompatible with the diversity of user requirements. Recent years are witnessing an increasing need of utility gained along the driving path and more advanced pathplanners are developed correspondingly, such as the safest and the most beautiful paths. Similar to the travel time on the edge, the utility score actually changes with the time as well. In this paper, targeting a more realistic path planning system, we allow both time cost and utility on the edge to vary from time to time. Over such two-fold time-dependent road network, we aim to discover the optimal driving path for the given user query. To address this NP-hard problem, we propose an approximated algorithm called 2TD Path-Planner, which mainly consists of three components, i.e., edge reachability computing, chromosome encoding, and chromosome decoding.

中文翻译：

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2TD Path-Planner：在两重时间相关道路网络上建立更现实的路径规划系统[应用说明]

规划行车路线是一项常见但具有挑战性的任务。以前的解决方案通常会建议驾驶员使用最短或与时间有关的最快路径，因此与用户需求的多样性不兼容。近年来，沿着行驶道路获得实用性的需求不断增长，相应地开发了更先进的道路规划器，例如最安全，最美丽的道路。与边上的旅行时间类似，效用分数实际上也随时间而变化。在本文中，针对更现实的路径规划系统，我们允许时间成本和边际效用随时间而变化。在这种基于时间的两倍时间依赖的道路网络上，我们旨在为给定的用户查询发现最佳的驾驶路径。为了解决这个NP难题，我们提出了一种称为2TD Path-Planner的近似算法，