Aimsun launches new solution for modeling on-demand transport

January, 2020

Aimsun launches new solution for modeling on-demand transport

Aimsun has kicked off 2020 with a brand new launch – Aimsun Ride. The latest offering is designed to help AI start-ups and Mobility as a Service (MaaS) operators evaluate business models and design and test different types of mobility service. Aimsun can also advise transportation authorities or research groups on the potential impact of the move towards MaaS, or work out how MaaS and on-demand transport could fit together with the wider public transportation system.

“We recognize that the automotive industry is on the cusp of profound change,” says Paolo Rinelli, Global Head of Product Management at Aimsun. “Younger consumers increasingly value user experience over ownership and are comfortable with sharing and renting cars, so car makers are adapting to the demand for mobility as a service; many are rebranding as mobility companies promoting ride-sharing, bike-sharing and, in the near future, self-driving cars. Aimsun Ride is a simulation platform that models and analyzes the efficiency of these new demand-responsive transportation services.”

Offered as a bundle of standard software, specially configured modules and professional services, Ride can help develop a business case for running a service or optimize operations plans. With Ride you can connect fleet management algorithms to the Aimsun simulator and then overlay a fleet of demand responsive vehicles on regular traffic so that it shares the road with other users. This gives insights into how a new offering will fit into the mobility space and how it is likely to combine with and compete against alternative modes. Then it’s a matter of testing and refining your fleet management algorithms until you develop a coherent, watertight business case – whether you model individual vehicle-to-vehicle interaction or use aggregate representations of a transportation network and demand, Ride will help find the perfect pricing point, fleet size, hub locations, parking arrangements, hours of operation, and levels of service that you can expect for each scenario.

Ride is underpinned by dynamic simulation of all flavors of on-demand or flexible transportation services so you can see how congestion impacts your service; experiment with pooling for taxi-style vehicles; explore the feasibility of fixed routes versus semi-fixed or completely free routes; model on-the-spot demand versus scheduled pick-ups, and a long etcetera. “That’s the beauty of Ride, “ says Rinelli. “Simulation eliminates the guesswork and the expensive testbeds and lets you analyze infinite parameter tweaks and ‘what if’ scenarios until you get it all just right.”

 
 
 

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