Recent advancements in computing and Geographic Information Systems (GIS) have revolutionized the development of decision support systems (DSS) to study and simulate the future of travel demand in urban areas. While travel demand models have been widely developed and used to inform the urban planning process, very little has been done to explicitly account for the aging of population within suc...

URBAN computing is a process of acquisition, integration, and analysis of big and heterogeneous data generated by a diversity of sources in urban spaces, such as sensors, devices, vehicles, buildings, and human, to tackle the major issues that cities face, e.g., air pollution, increased energy consumption and traffic congestion. Urban computing connects unobtrusive and ubiquitous sensing techno...

Blockchain technology has been widely used in finance, transportation, education, medical treatment, network security, management science, and other industries due to its characteristics of decentralization, high reliability, traceability. Unlike studies on Urban Intelligent Transportation Systems (UITS) the past, we present a model framework applied by blockchain developing countries. After de...

Traffic congestion in urban road networks is a costly problem that affects all major cities in developed countries. To tackle this problem, it is possible (i) to act on the supply side, increasing the number of roads or lanes in a network, (ii) to reduce the demand, restricting the access to urban areas at specific hours or to specific vehicles, or (iii) to improve the efficiency of the existin...

Rapid urban growth is resulting into increase in travel demand and private vehicle ownership in urban areas. In the present scenario the existing infrastructure has failed to match the demand that leads to traffic congestion, vehicular pollution and accidents. With traffic congestion augmentation on the road, delay of commuters has increased and reliability of road network has decreased. Four s...