Algorithm Engineering for integrated multimodal route planning

该子项目的目标是设计多式联运网络路线规划的有效算法，并将其用于综合公共交通规划。第一个重点是扩展的时间表信息算法的多式联运路线规划。本文主要研究了两种时刻表信息算法：连接扫描算法（CSA）和基于轮的公交路由算法（RAPTOR）。在将这些算法扩展到无限人行道的第一个融资阶段的结果之后，下一步将整合更多的交通模式。这将需要加速CSA或RAPTOR算法，以及将以前考虑的优化标准旅行时间和换乘次数扩展到四个或五个优化标准。 研究已经开始在第一个资金阶段使用路线规划算法的公共交通分配和估计的整体乘客将继续。第一步，纯公共交通网络也将扩展到不受限制的步行。对于路线选择的评估模型，将考虑其他标准，特别是车辆容量，以便实现更现实的乘客路线选择。

The objective of this sub-project is the design of efficient algorithms for route planning in multimodal transport networks and their use in integrated public transport planning. The first focus is on the expansion of timetable information algorithms for multimodal route planning. We focus mainly on the two timetable information algorithms Connection Scan Algorithm (CSA) and Round-Based Public Transit Routing (RAPTOR). Following the findings of the first funding phase for the extension of these algorithms to unlimited footpaths, further modes of transport will be integrated in the next step. This will require an acceleration of the CSA or RAPTOR algorithms, as well as an extension of the previously considered optimization criteria travel time and number of transfers to four or five optimization criteria.The second focus of this sub-project is on the use of route planning algorithms to improve integrated planning in public transport. Research started already in the first funding phase on using route planning algorithms for public transit assignment and estimation of the overall passenger will be continued. In a first step, the pure public transport network is to be extended as well to unrestricetd walking. For the assessment model for the route selection, additional criteria are to be taken into account, in particular vehicle capacities, in order to achieve a more realistic route selection of the passengers.