Individual multi-modal trip planning is a major task in transportation science. With increasing availability of new means of transportation personal constraints (e.g. elevator phobia or fear of flying) and preferences (e.g. train over bus) gain higher impact. Existing trip planners are mostly based on static time-tables and road-network data. Furthermore an objective function that covers individual constraints and preferences on route choice is hard to find for existing trip planners. In this position paper we present an approach that incorporates the 'wisdom of the crowd' by construction of a transfer graph based on previously successfully performed trips of other persons. By this approach personal constraints and preferences may easily be taken under consideration by filtering those routes which were performed by people with similar restrictions. Also regular congestions may be taken into consideration as these are already in the data. In case of hazards or blockages corresponding connections can be removed in the transfer graph and alternatives are provided. With a sufficiently large set of initial routes, we expect the method to produce reasonable route suggestions.
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