Car-centered mobility is the main sources of traffic congestion in most cities, resulting in high economic and social costs. To address this mobility challenge, increasing service frequency and capacity is widely adopted solutions by public transport agency. However, such a ‘local’ solution cannot meet its aim without considering users’ need and seamless connectivity between different means of transport. A number of new flexible transit or mobility on demand (MOD) services such as Uber, Lyft or Kutsuplus have emerged recently in order to provide personalized mobility services. The methodology in planning these services by considering both demand (user’s behavior) and supply (presence of a host of competing/complementary services in a multimodal transportation system) is very challenging and has been still less studied until recently. Central to the successful operations of the on-demand mobility services is the need to take into account the supply-demand interactions in such a setting. To this end, developing new modeling approaches and decision support tools for assessing the design of MOD systems is essential for its realistic applications.This project focuses on developing new methodology and tools to support the planning and design of MOD systems. At demand side, understanding users’ route choice behavior in a multimodal transport system needs to be addressed. A constrained route choice model will be developed based on the discrete games approach in order to address the congestion effect and social network influence. The second objective of the project is to develop a decision support tool/test bed to assess different operational settings of the MOD services. A simulation network will be calibrated for Luxembourg City to evaluate different operating policies for the service operators. We will use the agent-based approach to model users’ day-to-day multimodal route choice adjustment process for the multimodal MOD services based on the discrete games approach. The third objective of the project is to study the methodology of evaluating the MOD design by considering the interaction between public agency and private operators on a network. The method will be based on the concept of stable matching theory to study its impact on market equilibrium, social welfare, and ridership for different service operators. We will focus on Luxembourg City as our case study area. A participative approach by involving public agency and private operators will be used to elaborate realistic scenarios and collect empirical data in order to assess different scenarios based on the stable matching theory. In doing so, the project allows developing new knowledge and tools to support the development of MOD systems and provide useful insight for the stakeholders towards a sustainable mobility shift.