In recent years, RAPTOR based algorithms have been considered the state-of-the-art for path-finding with unlimited transfers without preprocessing. However, this status largely stems from the evolution of routing research, where Dijkstra-based solutions were superseded by timetable-based algorithms without a systematic comparison. In this work, we revisit classical Dijkstra-based approaches for public transit routing with unlimited transfers and demonstrate that Time-Dependent Dijkstra (TD-Dijkstra) outperforms MR. However, efficient TD-Dijkstra implementations rely on filtering dominated connections during preprocessing, which assumes passengers can always switch to a faster connection. We show that this filtering is unsound when stops have buffer times, as it cannot distinguish between seated passengers who may continue without waiting and transferring passengers who must respect the buffer. To address this limitation, we introduce Transfer Aware Dijkstra (TAD), a modification that scans entire trip sequences rather than individual edges, correctly handling buffer times while maintaining performance advantages over MR. Our experiments on London and Switzerland networks show that we can achieve a greater than two time speed-up over MR while producing optimal results on both networks with and without buffer times.

翻译：近年来，基于RAPTOR的算法一直被认为是无需预处理、支持无限换乘路径寻径领域的最先进方法。然而，这一地位主要源于路由研究的发展历程——基于Dijkstra的解决方案在未经系统比较的情况下就被基于时刻表的算法所取代。本研究重新审视了基于经典Dijkstra的无限换乘公共交通路由方法，并证明时间依赖型Dijkstra算法（TD-Dijkstra）的性能优于MR算法。但高效的TD-Dijkstra实现依赖于预处理阶段对支配连接的过滤，该过滤假设乘客总能换乘到更快的连接。我们证明当站点存在缓冲时间时，这种过滤方法存在缺陷，因为它无法区分无需等待即可继续行程的座位乘客与必须遵守缓冲时间的换乘乘客。为解决这一局限，我们提出了转移感知型Dijkstra算法（TAD），该改进通过扫描完整行程序列而非单独边段，在保持对MR算法性能优势的同时，正确处理缓冲时间。在伦敦和瑞士交通网络上的实验表明，本方法在有无缓冲时间的情况下均能获得最优结果，同时实现超过MR算法两倍以上的加速比。