10.14489/vkit.2016.08.pp.029-033

DOI: 10.14489/vkit.2016.08.pp.029-033

Щербаков М. В., Садовникова Н. П., Парыгин Д. С., Голубев А. В., Чечеткин И. А.
АВТОМАТИЗАЦИЯ ПОДДЕРЖКИ ПРИНЯТИЯ РЕШЕНИЙ ПО РАЗРАБОТКЕ МАРШРУТОВ ОБЩЕСТВЕННОГО ТРАНСПОРТА НА ОСНОВЕ АНАЛИЗА ДАННЫХ О КОРРЕСПОНДЕНЦИЯХ ЖИТЕЛЕЙ
(c. 29-33)

Аннотация. Рассмотрена задача модернизации маршрутной сети городского пассажирского транспорта. Предложен метод, позволяющий на основе данных о предпочтениях жителей по перемещению формировать и оптимизировать новую маршрутную сеть. Разработаны алгоритмы для кластеризации геораспределенных данных, синтеза вариантов сети маршрутов и поиска оптимального варианта. Тестирование разработанных алгоритмов проведено на модельных данных (12 000 точек) для города с населением около 300 000 человек.

Ключевые слова: городской пассажирский транспорт; планирование транспортной сети; поддержка принятия решений; анализ больших данных; предпочтения жителей; транспортные корреспонденции; геоинформационная система.

Shcherbakov M. V., Sadovnikova N. P., Parygin D. S., Golubev A. V., Chechetkin I. A.
DECISION SUPPORT AUTOMATION FOR THE PUBLIC TRANSPORT ROUTES DEVELOPMENT BASED ON THE CORRESPONDENCES POPULATION DATA ANALYSIS
(pp. 29-33)

Abstract. The paper has a deal with a problem of creation the public transport networks based on the big geospatial data analysis. The decision support problem for improving public transportation is considered from the standpoint of satisfying transport demand. The proposed method allows creating public transportation routes schemes based on data about the users preferences of moving in the urban infrastructure. The method implements the following steps: the clustering of source and destination transportation correspondence points, the initial route network generating, the route network improving using the evolutionary algorithm implementation. To collect user preferences data, the application Gathering was developed by authors. This solution provides an interface for input data about the most frequent movements in an urban environment. The application Scatter was developed to generate modeling data for further experiments. To reduce the number of initial source/destination points, the approach based on clustering was proposed. The main advantage, the new approach use urban terrain metric to take into consideration natural or artificial obstacles. Also, the algorithm for initial route creation was developed. The main idea of the algorithm is sequentially adding new nodes towards minimization of the total length of the route. The evolutionary modification of the initial routes network is performed by the other algorithm, which uses mutation and crossover operations to optimize the route network length. The obtained algorithm are implemented as a software and are tested using a large amount of modeled geospatial data. For example, 12 000 points of simulated data for the 300 000 population city were processed and grouped into cluster 41. Clusters centers might be considered as stopping points, which included in network routes. Initially, the network was built with an average route length of 7444 m and a total network length of 37 222 m. As the result of the evolutionary algorithm, the obtained network has the average route's length 3125 m and the total network length is 15 627 m.

Keywords: Urban public transportation; Transportation network planning; Decision support; Big data analytics; Population preferences; Transportation correspondence; Geoinformation system.

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М. В. Щербаков, Н. П. Садовникова, Д. С. Парыгин, А. В. Голубев, И. А. Чечеткин (Волгоградский государственный технический университет, Волгоград, Россия) E-mail: Этот e-mail адрес защищен от спам-ботов, для его просмотра у Вас должен быть включен Javascript

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M. V. Shcherbakov, N. P. Sadovnikova, D. S. Parygin, A. V. Golubev, I. A. Chechetkin (Volgograd State Technical University, Volgograd, Russia) E-mail: Этот e-mail адрес защищен от спам-ботов, для его просмотра у Вас должен быть включен Javascript

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