TOWARDS SUSTAINABLE URBAN TRANSPORTATION PLANNING IN DEVELOPING COUNTRIES: “DRT” MOBILE APPS AS A CATALYST FOR BIG DATA-BASED DECISION SUPPORT SYSTEM
Free (open access)
229 - 241
ABDEL RAHMAN RAGHEB, MAI ABDO, KHALID S. AL-HAGLA
The term big data refers to huge data sets which have high velocity, high volume and high variety. Using decision support system (DSS), big data can manage transportation demands, budgets, goals, and regulations. Moreover, it can manage different stakeholders and minority groups’ needs and requirements, while adapting to environmental, economical and current social concerns. Transportation planning and decision-making faces rapid urbanization challenges in both developed and developing countries since urban planning process and decision makers depend essentially on data collection and analysis. This paper aims to discuss technological mutual line of big data, public transportation types, and DSS through transit mobile apps. The present paper discusses an assumption of reasons to explain why transit apps existed in both the developed and developing countries. It focuses on the developing countries, with a study on six demand responsive transit apps (DRT) used in Egypt to address the existing transit concerns. As a result, a comparison is drawn to comment on these apps’ features and big data usage in enhancing transportation decision making in Egypt. Finally, the paper provides comments on still existing concerns and proposes recommendations for a new app development based on the previous apps, to sprint big data-based DSS.
big data, urban planning, transportation planning, DRT, mobile apps, decision making, Paratransit, informal transportation