We present algorithms for multi-modal route planning in road and public transit networks, as well as in combined networks.
Therefore, we explore the nearest neighbor and shortest path problem and propose solutions based on Cover-Trees, ALT and CSA.
Further, we illustrate the theory behind the algorithms, give a short overview of other techniques, present experimental results and compare the techniques with each other.
Dynamic Time-Dependent Route Planning in Road Networks with User Preferences
在道路网络上计算驾驶方向的算法方法已经取得了巨大的进展。大部分工作集中在时间无关的路线规划，其中假设每个弧上的成本是恒定的每个查询。实际上，当前的交通状况会显著影响大部分道路网络的行程时间，并且它会在一天中发生变化。人们可以区分可以使用历史交通数据预测的交通拥堵和由于不可预测的事件造成的拥堵，例如，事故为重点在这项工作中，我们研究了\emph{dynamic and time-dependent}路线规划问题，它既考虑到预测（基于历史数据）和现场交通。为此，我们提出了一种实用的算法，该算法在对用户偏好鲁棒的同时，能够整合时间相关度量的全局变化（例如，由于业务更新或用户限制），同时允许实现交互式应用的后续查询。
We study the problem of planning routes in road networks when certain streets or areas are closed at certain times. For heavy vehicles, such areas may be very large since many European countries impose temporary driving bans during the night or on weekends. In this setting, feasible routes may require waiting at parking areas, and several feasible routes with different trade-offs between waiting and driving detours around closed areas may exist. We propose a novel model in which driving and waiting are assigned abstract costs, and waiting costs are location-dependent to reflect the different q…
Dating back to two famous experiments by the social-psychologist, Stanley Milgram, in the 1960s, the small-world phenomenon is the idea that all people are connected through a short chain of acquaintances that can be used to route messages. Many subsequent papers have attempted to model this phenomenon, with most concentrating on the "short chain" of acquaintances rather than their ability to efficiently route messages. In this paper, we study the small-world navigability of the U.S. road network, with the goal of providing a model that explains how messages in the original small-world experim…
We study exact, efficient and practical algorithms for route planning in large road networks. Routing applications often require integrating the current traffic situation, planning ahead with traffic predictions for the future, respecting forbidden turns, and many other features depending on the exact application. While Dijkstra's algorithm can be used to solve these problems, it is too slow for many applications. A* is a classical approach to accelerate Dijkstra's algorithm. A* can support many extended scenarios without much additional implementation complexity. However, A*'s performance dep…
Route choice is often modelled as a two-step procedure in which travellers choose their routes from small sets of promising candidates. Many methods developed to identify such choice sets rely on assumptions about the mechanisms behind the route choice and require corresponding data sets. Furthermore, existing approaches often involve considerable complexity or perform many repeated shortest path queries. This makes it difficult to apply these methods in comprehensive models with numerous origin-destination pairs. In this paper, we address these issues by developing an algorithm that efficient…
Proposed initially from a practical circumstance, the traveling salesman problem caught the attention of numerous economists, computer scientists, and mathematicians. These theorists were instead intrigued by seeking a systemic way to find the optimal route. Many attempts have been made along the way and all concluded the nonexistence of a general algorithm that determines optimal solution to all traveling salesman problems alike. In this study, we present proof for the nonexistence of such an algorithm for both asymmetric (with oriented roads) and symmetric (with unoriented roads) traveling s…
