Connected and Autonomous vehicles (CAVs) receive a lot of popular media coverage and scientific and technical focus during the recent years. From a futuristic concept to actual pilot and live demonstrations, recent progress leads to a more mature and realistic caption of how the implementation of solutions based on autonomy could help cities reduce accidents and traffic, along with other externalities.
In FRONTIER, one of the focus areas includes the investigation of various demand management strategies, and the actions required to translate such strategies into technical specifications so they can be tested using the simulation and other quantitative tools employed and developed during the project.
An idea as simple as who is responsible for running a shared autonomous vehicle service in a city can have major implications in the footprint of such as service; different service operators have different goals. If a private company runs robotaxis in a city the CAV fleet may be optimized to provide a seamless experience to the customer, minimizing waiting time or providing personalized services to the passenger. On the other hand, if the fleet of autonomous, shared vehicles is operated by a public transport operator, total travel time or passenger kilometers may be the variables that require minimization during the fleet management. Such scenarios investigation will allow us to further explore the implications of being able to program and monitor such indicators in real-time.
CAVs are an expected, major disruptor in the transport and mobility sector, but different applications, maximizing the capabilities of the autonomous vehicle industry, may lead to different scenarios and effects on the externalities of the transport sector. FRONTIER pioneers the research and development in this aspect and envisages to be one of the first initiatives to provide evidence on specific applications and use-cases related to CAVs.
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