Integrated Mobility

Challenges

Approximately 67% of the global population is projected to live in urban areas by 2050 (United Nations, 2018). Population growth and demand for urban centers inherently demands extensive mobility and alternate strategies extrapolated from present urban planning, policy and transport management. An approximate $100 billion could be generated by improving mobility and promoting an integrated mobility system in the MENA region (HSBC, 2019), targeting mass mobility, first/last mile and mobility-as-a-service. As fast and integrated mobility systems such as Industry 4.0, electro-mobility, automation and smart mobility technologies are being developed, a pertinent query for logistics and freight mobility remains regarding the increased speed, shrinking distances between trade centers and access to goods. A major challenge is to develop computational models that can better reflect this change in mode choices for people and goods. RG4 researchers are evaluating mass and goods mobility, transit load distribution, urban planning and mode choice modules as an inter-related problem. RG4 is investigating the optimisation of mobility across multiple modes (private cars, mass-mobility systems, shared and autonomous mobility, public buses and goods and logistic vehicles) to address the friction points of the current fragmented mobility solutions.

Aim

The purpose of the project is to analyse travel demand, multi-mode planning, spatial demand management, urban sprawl and mobility cost optimisation, and GHG emissions from an integrated perspective. The Integrated Mobility research group aims to explore the practicality of adaptive mobility systems to predict mode choices in a complex environment, thereby preparing the UAE and beyond for an integrated, improved, sustainable and efficient mobility network.

Ongoing Research Projects

• Innovating the Travel Demand Modelling: Developing the Origin-Destination Matrix With the Help of a Dedicated Mobile Application
• Agent-Based Simulation Enhanced with Big Data and Artificial Intelligence Methods to Simulate and Optimize Traffic Flow