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Publication
AI Magazine
Paper
Hedging the risk of delays in multimodal journey planning
Abstract
Traditional multimodal journey planners are deterministic. However, uncertainty in a transportation network can often lead to missed connections, causing delays and hurting the reliability level of the service. This article provides an overview of what is possibly the first multimodal journey advising system that is capable of reasoning under uncertainty and that provides more reliable journey plans.