| Grant number: | 19/12054-4 |
| Support type: | Scholarships in Brazil - Doctorate |
| Effective date (Start): | January 01, 2020 |
| Effective date (End): | May 31, 2022 |
| Field of knowledge: | Engineering - Transportation Engineering - Transportation Planning |
| Principal researcher: | Cira Souza Pitombo |
| Grantee: | Samuel de França Marques |
| Home Institution: | Escola de Engenharia de São Carlos (EESC). Universidade de São Paulo (USP). São Carlos , SP, Brazil |
Abstract The present PhD project, whose general objective is to model and estimate the travel demand in a public transport network, based on a geostatistical approach, is a continuation of a previous master's study and is incorporated into a line of research that evaluates, over the years, the travel demand from spatial data modeling. Its design is based on the constraints and successes of previous researches. The proposed spatial modeling is applied to the number of boarding and alighting, per bus stop, and loading in the stretches, along eight bus transit lines from the city of São Paulo, Brazil. It will be analyzed the effects of explanatory variables, effects of the application of network or Euclidean distances in the process of calculation and modeling of semivariograms, as well as the effect of overlapping bus lines. In addition to providing a significant methodological contribution, the practical contribution of the research is justified by the reduction in the financial resources required to carry out the boarding and alighting survey and the potential of the geostatistical techniques for estimating the demand of users at not sampled bus stops during the survey. As tools to be used stand out the universal kriging and ordinary kriging. The fictious point test and validation for methodological suitability are proposed. In the validation, we will identify the set of bus stops and line stretches, to be considered by the boarding and alighting survey, which would generate continuous surfaces of estimated values closer to the condition in which goodness-of-fit measures are optimized. This solution, therefore, would eliminate the need to carry out this survey throughout the entire bus network, but still guarantee results close to those of the complete survey. (AU) | |
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