Companies like Bridj, Ford and Sweden’s Kutsuplus have shut down their microtransit shuttle services, in part because optimizing the trips has proven both difficult and costly.
The big picture: In theory, moving more people with fewer vehicles is a good business model. But microtransit requires companies to purchase and maintain vehicles and to pay drivers for the duration of their shift, not just when they are carrying paying passengers.
AVs could eliminate driver costs and reduce navigation errors, but improving the efficiency of their routes requires crunching massive data loads in real time.
Where it stands: Cities, companies and researchers are reworking algorithms to make shared routes more efficient, to minimize both congestion and extra transit time for passengers.
• Microtransit provider Via and the Los Angeles Department of Transportation are running a pilot that focuses on “last mile” travel from transit stops.
• Using computer models, a team at the University of Texas found that 1 shared vehicle could replace 11 single-occupancy vehicles around Austin, with wait times between 20 seconds and 5 minutes.
• Bestmile data scientists found that 200 shared, on-demand vehicles could accommodate the 31,000 rides taken in 2,700 Chicago taxis each day with average wait times of five minutes and added ride times of six minutes.
• A McKinsey analysis found that, as soon as 2030, shared “seamless” mobility could accommodate 30% more traffic while cutting travel time by 10%.
What to watch: The EU’s AVENUE project is rolling out last mile autonomous shuttles in four cities to connect workers and residents with long-haul public transit and to determine the requirements for replicating successful service elsewhere.