@phdthesis{,
    author = {Hedderich, Mareike},
    title = {Universal Routing},
    editor = {},
    booktitle = {},
    series = {},
    journal = {},
    address = {},
    publisher = {},
    edition = {},
    year = {2020},
    isbn = {},
    volume = {},
    number =  {},
    pages = {},
    url = {},
    doi = {},
    keywords = {Routing, parking, optimization},
    abstract = {In this thesis, routing procedures are described that aim to support the driver in finding a parking space and arriving punctually in a city. This enables the driver to reach their destination on time while avoiding unnecessary stress. The optimisation of the route to find a parking space also means that urban traffic can be relieved. The side-effect of the lower frequency of traffic on the roads is explicitly desired, as it contributes to reducing the volume of traffic and the associated emissions, which also makes a potential contribution to noise prevention and air pollution control. How the algorithms developed in this thesis contribute to the equalisation of overall traffic and to stress reduction is described below. In the first part of the thesis, a method for searching for a parking space is presented, which is an instrument to control and optimize the search for a parking space along the preferences of the user. First, the basic mathematical concepts necessary to map the road system are presented. Factors that influence the decision for a parking space are investigated. The park search route developed is based on a fastest way algorithm with integration of parking probabilities. Evaluation functions will be developed to evaluate the resulting route. In a second step, parts of these functions are included in the cost function of the park search algorithm. In a simulation with real parking data, the procedure proves to be better than the fastest route in terms of guidance through streets with higher parking probabilities, which also results in an increase in the probability of finding a parking space. It is shown that the presented parking search algorithm can include both street-side parking lots and parking garages in its route calculation. The second method represents a further development of the preference-controlled parking search described above by adding an additional user-relevant criterion: the driver’s punctual arrival at their destination. The evaluation functions presented in the first part will be extended accordingly. The presented procedure is based on a routing algorithm that focuses on the observance of a user-defined time budget. The combination of the park search algorithm with the method for punctual arrival uses historic travel time data of a vehicle fleet. This data can be used to estimate the extent to which a certain time horizon can be met. Simulations in a real road network with parking data and historic travel time data show that the presented procedure can support the search for a parking space and at the same time contribute to a punctual arrival.},
    note = {},
    
    school = {Universität der Bundeswehr München},
    
}