Smart mobility means making better use of existing resources whether it’s natural resources, roads, underground systems, tramways, railway lines or parking spaces.
Electronic transactions, data from grids of connected sensors in the streets, mobile apps and social network contributions of travelers provide a wealth of information on mobility yet, up to now, very little value has been captured from all this data. XRCE research in transportation analytics and ethnography are being used to transform this data into meaningful information to develop smart mobility applications along three axes:
Making services more reactive to users’ needs.
Transportation infrastructures can be adapted to the ever-changing needs and behaviors of citizens. We have developed visualization, optimization and simulation technologies that allow city transportation authorities and planners to better understand how services are used, monitor performance and improve their transportation offerings more quickly.
Our transportation analytics technologies have been experimented with real data from more than ten cities around the world and have resulted in the commercialization of the Xerox Mobility Analytics Platform, a unique offering for integrated spatio-temporal transportation analytics from operations data. Today we are experimenting how we can use this data to predict the impact of changes on demand (link paper ITS Asia PaC). With our data driven micro-simulation environment we are able to automatically reconstruct a public transport network usage that matches reality by more than 90%.
Smart mobility: Providing personalized guidance to travelers
Individual travelers can be guided in real time using our optimization and prediction technologies. We have developed a powerful multimodal trip planner engine able to propose the optimal combination of all different modes of transportation in an urban area. Trip planning in the context of a rich mobility-as-a-service offering creates new challenges. A wide variety of options are possible and many criteria (transportation modes, waiting time, transfer time, walking time, reliability of services) can be used to distinguish between them. Having a personalized recommendation relative to your preferences and goals and in the context of the trip is therefore critical. In addition, the multiple combinations of multiple services implies increased uncertainty with respect to the completion of the plan. Our technology has therefore been designed to incorporate real time information and traffic prediction in its computation.
Smart mobility is also about helping people be smarter in organizing their mobility. Findings for our ethnography studies allows us to design solutions that take into consider the entire user experience. We also propose solutions that not only consider the individual’s goal but conciliate it with the surrounding travelers’ needs and the transportation authority’s incentives. We do this using gamification techniques. Such expertise led to the design of the multimodal trip planning application launched in the cities of Los Angeles and Denver.
Smart mobility: Managing demand
Urban areas concentrate a lot of people in a limited space where the transportation infrastructure will always remain a limited or scarce resource. Our competencies in mechanism design and machine learning help us to develop solutions that enable city authorities to predict demand and manage it by setting the right incentives. We have for example helped the city of Los Angeles manage its on-street parking pricing policies by combining a dedicated sensor system, smart demand based pricing algorithms, and advanced parking guidance solutions. The result is a reduction of parking congestion, and better use of previously underused spaces.