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    <p>I have been involved in development of one journy planner system for Stockholm Public Transportation in Sweden. It was based on Djikstra's algorithm but with termination before every node was visited in the system. Today when there are reliable coordinates available for each stop, I guess the A* algorithm would be the choise.</p> <p>Data about upcoming trafic was extracted from several databases regularly and compiled into large tables loaded into memory of our search server cluster.</p> <p>One key to a sucessfull algorith was using a path cost function based on travel and waiting time multiplied by diffrent weightes. Known in Swedish as “kresu"-time these weighted times reflect the fact that, for example, one minute’s waiting time is typically equivalent in “inconvenience” to two minutes of travelling time.</p> <h2>KRESU Weight table</h2> <ul> <li>x1 - Travel time </li> <li>x2 - Walking between stops </li> <li>x2 - Waiting at a stop during the journey. Stops under roof, with shops, etc can get a slightly lower weight and crowded stations a higher to tune the algorithm.</li> <li>The weight for the waiting time at the first stop is a function of trafic intensity and can be between 0.5 to 3.</li> </ul> <h2>Data structure</h2> <p><strong>Area</strong> A named area where you journey can start or end. A Bus Stop could be an area with two Stops. A larger Station with several platforms could be one area with one stop for each platform. Data: Name, Stops in area</p> <p><strong>Stops</strong> An array with all bus stops, train and underground stations. Note that you usually need two stops, one for each direction, because it takes some time to cross the street or walk to the other platform. Data: Name, Links, Nodes</p> <p><strong>Links</strong> A list with other stops you can reach by walking from this stop. Data: Other Stop, Time to walk to other Stop</p> <p><strong>Lines/Tours</strong> You have a number on the bus and a destination. The bus starts at one stop and passes several stops on its way to the destination. Data: Number, Name, Destination</p> <p><strong>Nodes</strong> Usually you have a timetable with the least the time for when it should be at the first and last stop in a Tour. Each time a bus/train passes a stop you add a new node to the array. This table can have millions of values per day. Data: Line/Tour, Stop, Arrival Time, Departure Time, Error margin, Next Node in Tour</p> <p><strong>Search</strong> Array with the same size as the Nodes array used to store how you got there and the path cost. Data: Back-link with Previous Node (not set if Node is unvisited), Path Cost (infinit for unvisited)</p>
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    1. POStrategy to find your best route via Public Transportation only?
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    1. USFredrik Haglund
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    1. POStrategy to find your best route via Public Transportation only?
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    1. COThat is very nice, I hadn't thought of not including the coordinates for the route, it makes things much simpler.
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    2. COYes, creating a heuristic function with the distance from current node to destination simplifies optimization a lot since A* search algoritm automatically will truncate the tree for you. Without coordinates we had to be very creative using zones and analyzing trafic to optimize the search.
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    3. COHopefully (distance from destination * average speed) would be a good enough metric for A*, but that might not always work for public transit where the rider doesn't care about distance traveled.
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