A common trend globally is the decline of bus use by the public. There are many reasons for this and nearly as many reports arguing over which factors have the most impact on ridership. Ultimately the nuances of why ridership drops are different for different cities but the main factors are common to all:
Big leaps in A.I are happening so fast that they are hard to keep track of. You may have heard of an A.I milestone which occurred in June when IBM’s Project Debater drew with human debaters. Or that a program built by two Carnegie Mellon researchers beat several top poker players over a 20 day contest. But why are these big events? And does this mean that A.I could really be trusted to make decisions to boost revenue in mobility solutions for the likes of car-sharing and on-demand micro-transit?
Using Simulators to assess On-Demand Microtransit
Setting up an on-demand micro-transit operation is a significant commitment of time and money so it pays to do your homework as much as possible and get On-Demand right the first time. One of the best ways to do this is with a simulation that can model various service scenarios and provide performance metrics like wait time and cost per trip for each scenario. Simulations can address the important concerns municipalities and transit agencies have when setting up and on-demand service.