The computation of an optimal route for a given start and destination in a static transportation network is used in many applications of private route planning. In this work we focus on route planning for emergency cars, such as, for example, police, the fire brigade and ambulance. In the case of private route planning, typical quantities to be minimized are travel time or route length. However, the idea of this paper is to minimize the risk of a travel time exceeding a certain limit. This is inspired by the fact that emergency cars have to reach the destination within a legal time. We consider mainly two approaches. The first approach takes into account relevant information to determine the weight, i.e. the desirability of certain edges of a graph during the minimization procedure. One possible risk factor to be aware of would be a suddenly jammed single-lane road on which the emergency car has no chance to make use of the benefits of the siren for instance. The same holds for full-closure situations and railroad crossings. We present a catalogue of risk factors along with an appropriate algorithm for practical route planning in emergency situations. The second one takes into account a weekly updated set of probe-vehicle data for each minute of the week along with data of current travel times. Comparing those travel-time data allows calculation of the associated risk for traveling certain edges of a route in a road network. We expect our algorithm to be a major advancement especially for destinations that lie outside the typical region travelled weekdays. In this case, automatic route planning naturally goes along with an additional gain of time.


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    Titel :

    Risk minimal routes for emergency cars


    Beteiligte:
    Woelki, M. (Autor:in) / Nippold, R. (Autor:in) / Bonert, M. (Autor:in) / Ruppe, S. (Autor:in)


    Erscheinungsdatum :

    2013


    Format / Umfang :

    11 Seiten, Bilder, Tabellen, 15 Quellen





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Print


    Sprache :

    Englisch




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