A new offset optimization method for signalized urban road networks is described in this dissertation. The method is capable of optimizing offsets in both undersaturated and oversaturated conditions and of finding quasi optimal results. The method is converted prototypically in a C++ program, which consists of three modules: (1) the input module; (2) the optimization module consisting of a genetic algorithm (GA) based optimizer; and (3) a traffic analysis module that serves as the fitness function for the GA-based optimizer. The analysis module is based on Cell Transmission Model; models spatial as well as temporal formation; and is able to predict build-up, propagation and dissipation of queues. Furthermore, its calculation time for repeated simulation runs of module permits online application. The analysis module also serves as the fitness function for the signal timing optimizer and is validated against well-known queuing models and AIMSUN, a state of the art microscopic traffic simulation. The GA-based optimization module consists of two search algorithms that generate timing parameters (offsets) for the analysis module and then optimize these parameters. The first algorithm performs a simultaneous search over all offsets by the process of variation of reproduction - crossover - mutation of the entire chromosome. The second routine varies a group of offset values and therefore only a part of the chromosome until the best solution is found. In the next step, the offsets of the next group of intersections are optimized. A method is developed for the determination of the search order, since the order of treating the intersection and searching the offset has great influence on the optimization results. AIMSUN is used as the unbiased estimator for comparing the developed method against well-know control software TRANSYT-7F, the full enumeration of the offset variables and a manual method based on engineering practice called dominance method. The comparison is carried out for three case studies to benchmark the performance capabilities of the developed method against existing ones. These case studies are a two-way street with 3 intersections; a small realistic network with 6 intersections; and a relatively large grid network with 12 intersections. The results obtained from comparing the first two case studies show that both PGA and SGA can find the optimal solution as well as the full enumeration, whereas the SGA could reduce the CPU-time significantly. For these two case studies, PGA and SGA are superior to both the dominance method and TRANSYT-7F.


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    Title :

    A new offset optimization method for signalized road networks


    Additional title:

    Eine neue Versatz-Optimierung für signalisierte Straßennetze


    Contributors:


    Publication date :

    2006


    Size :

    177 Seiten, Bilder, Tabellen, 105 Quellen




    Type of media :

    Theses


    Type of material :

    Print


    Language :

    English