Abstract
Trip generation rates provide essential information in the transport planning process and especially in the land-use transport interaction models. Among the general population, university students form a specific group of people which is characterized by increased mobility rates. In the framework of this paper, the results from a survey concerning the trip generation rates of the students of the Aristotle University of Thessaloniki (AUTh), Greece are presented and discussed. The main university campus which is located in the city center, covers an area of around 430000 m2 and serves thousands of students on a daily basis. AUTh is actually the largest university in the country. A face-to-face questionnaire-based survey took place during spring 2015 and a number of 595 questionnaires from the students of AUTh was collected. A sample of 1% of the population of students from each one of the nine (9) Faculties of AUTh, which were examined in the research, was collected during the questionnaire-based survey. A total number of nine (9) questions were included in the questionnaires, aiming at the determination of the trip generation rates in the University campus. Linear regression analysis was used in order to construct a trip generation model. This model shows that trip generation rate almost equals to two daily trips per student. Four (4) models with dummy predictors were also constructed, using linear regression analysis, to describe the percentage distribution of the sampled population that made the trips throughout the day. Furthermore, data concerning the mobility characteristics of the university students are also presented in the framework of the paper. The results are expected to add some knowledge to the scientists involved in the design and implementation of a sustainable transport plan in the wider area of a University campus.
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Basbas, S., Takatzoglou, K., Mintsis, G., Taxiltaris, C., Politis, I. (2019). Trip Generation Rates for a University Campus: The Case of the Aristotle University of Thessaloniki, Greece. In: Nathanail, E., Karakikes, I. (eds) Data Analytics: Paving the Way to Sustainable Urban Mobility. CSUM 2018. Advances in Intelligent Systems and Computing, vol 879. Springer, Cham. https://doi.org/10.1007/978-3-030-02305-8_2
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