End-to-End Approach for Mobility-as-a-Service tools, business models, enabling framework and evidence for European seamless mobility.
The main goal of MaaS4EU is to provide quantifiable evidence, frameworks and tools to enable the MaaS concept, by addressing challenges under four pillars: Business, End Users/Customers, Technology-Data and Policies.
The MaaS Maturity Index (MMI) is a framework and calculation tool developed to assess the readiness of metropolitan areas for the implementation of MaaS. Various characteristics which affect the likelihood of a successful MaaS implementation are assessed to determine an aggregate score showing how ready a city is to implement MaaS.
The calculator can be used to demonstrate what improvements are needed to make a city ready for MaaS. Scores can be compared across cities, showing where MaaS providers could have the greatest impact.
Feasibility Study for "Mobility as a Service" concept for London – FS-MaaS
The objective of the FS-MaaS project is to propose the design of a Mobility as a Service (MaaS) concept for London, and examine its feasibility.
The feasibility study indicates that the introduction of MaaS-London will benefit both the supply and the demand side. It’s a feasible product that can well serve London transport market and contribute to London’s 2020 vision.
The main objective of this project is to develop a state-of-the-art activity-based simulation platform, aiming to quantify the impact of new mobility services and technologies (e.g. autonomous vehicles, on-demand mobility services, route-guidance systems) with respect to travel habits, traffic congestion, transportation energy use and emissions.
InoMobility steps on the advancements in technology and focuses on representing the complex and dynamic interactions between demand and supply in different levels by providing a simulation tool in which different transportation planning and technology scenarios may be tested and evaluated.
Find out more
Mobility as a Service Survey
This is an on-line survey that has been designed specifically to explore the current travel choices of individuals and their preferences and reactions towards new mobility services and MaaS. This on-line survey has been applied in London and could be easily customised for any city.
The London Mobility Survey is a smartphone based travel survey that aims study the travel habits of Londoners and their attitudes and preferences towards new mobility solutions and Mobility as a Service.
Integration of Car Sharing and Bike Sharing System: A case study of Taiyuan, China
This project proposes an integrated urban transport system based on car sharing and bike sharing for developing countries using a Chinese city as case study. It will forecast the benefit of such a system to energy savings and climate change mitigation.
Find out more
Analysing Londoners’ Transitions from Motorised Modes to Cycling
The aim of this project is to analyse the demographic and trip characteristics of cyclists in London to identify the most promising population segments and areas that cycling policies could target.
Find out more
Exploring the factors affecting Electric Vehicle Purchasing Behaviour in Greater London
This project investigates the factors affecting consumers’ electric vehicle (EV) purchasing behaviour.
By defining consumers’ preference factors, targeted corporate marketing and government policies can be developed to accelerate diffusion of EFV.
Find out more
MOT tests and Vehicle Miles Travelled
This project provides a novel analysis framework for the spatial aspects of car travel, measured by vehicle miles travelled, extended to include a variable decomposition approach that captures potential asymmetries and hysteresis in a spatial setting.
The results provide support to the car use saturation hypothesis through both the negative VMT trend and the positive impact of motorisation rate that captures car dependence, rather than car use intensity.
Residential Location Choice and Transport Energy Demand
This project uses an integrated modelling approach to capture trade-offs between housing/domestic and transport consumption costs, developing a novel methodological framework to explicitly include energy demand.