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The rise of Transportation Network Companies (TNCs)–the industry name for peer-to-peer ridehailing services like Uber and Lyft have, in many cases, disrupted public transit and with it, urban planning and management. While promising to reduce congestion, like TNCs have in fact worsened traffic and decreased public transit utilization.

Transit analyst Bruce Schaller found that “TNCs have added 5.7 billion miles of driving annually in the Boston, Chicago, Los Angeles, Miami, New York, Philadelphia, San Francisco, Seattle and Washington D.C. metro areas.” Schaller also found that “About 60% of TNC users in large, dense cities would have taken public transportation, walked, biked or not made the trip if TNCs had not been available for the trip.”





Taking Back the Streets

One proposed alternative to private peer-to-peer ridehailing services is autonomous and human-driven micro-transit services — on-demand, shared vehicles that carry groups of passengers to and from transit hubs. The goal is to solve the “last-mile” problem that forces many commuters to drive or use ridehailing services — the lack of a convenient means of getting to bus and train stations.



Getting it Right

Implementing successful micro-transit solutions can be challenging. There have been notable failures, with micro-transit providers like Bridj and Chariot going out of business due to lack of utilization. In order for micro-transit to be successful, it has to do a better job of moving people than the alternatives — a private car or a hired ride. The computations involved in pooling passengers and getting them from “point A” to points B, C and D are not simple. Factors like demand locations, fleet size, fleet location, dispatching, routing, and ride efficiency all have to be considered.



Phasing In

Bestmile has helped design, deploy, and manage successful micro-transit services in cities around the world. What we’ve found is that a phased approach works best, where the factors listed above can be tested and planners can learn and adjust over time. We’ve found that the following steps make for a successful implementation.


Phase I: Fixed-Route
The first phase in planning micro-transit solutions is to test a fixed-route service that goes from station to station. This is a simple service that can be used to test vehicles and to win initial public acceptance — especially important for autonomous services.


Phase II: Fixed-Route with On-Demand Stops

Phase II shifts to a fixed-route to a route that offers on-demand and/or fixed stops along the way, usually by extending the Phase I route.


Phase III: On-Demand in Defined Area
The next step is to test a fully on-demand service where travelers can board at arbitrary locations within a defined area which would be geofenced in the case of autonomous services.


Phase IV: Integration with Public Transit
The final stage of the implementation is to integrate the service with public transit. This may involve further extending the route to a transit hub such as a bus or train station. It is important to synchronize schedules to make the service as convenient and accessible as possible.



Not One-Size-Fits-All

White these phases sound simple, there is a great deal of planning and analysis needed with each one. Every city is different, and understanding local regulations, demand profiles, vehicle capabilities, physical issues such as traffic lights and roundabouts on routes, technology requirements for dispatching and routing and integrating services with the public transit all need to be considered. The decision of whether to start with a human-driven or autonomous service will, of course, influence these decisions.



Simulating Success

It is also possible to use data and analytics to test services in advance using existing ride matching and dispatching algorithms. Using historical or estimated data to simulate how services might perform in advance of deployment can give planners and operators invaluable information to help ensure that the service works as planned. Bestmile’s Mobility Services Platform, used to manage and optimize on-demand shared mobility services, can also be used to test and simulate these services in advance of deployment.



Making it a Win-Win

In order for cities and transit agencies to reduce congestion and increase ridership, they need to offer services that are more efficient and convenient than private alternatives and still meet business objectives. Shared autonomous or human-driven micro-transit offers a relatively low-cost solution that can move more people with fewer vehicles. It’s important that services efficiently match supply and demand, and that they be synchronized with transit schedules to make the service as convenient as possible. Using a phased approach, along with virtual and actual testing can help ensure that the service meets both traveler and operator requirements.



Latest Webinar

To learn more about how to implement effective autonomous vehicles and services in your service area, watch the recording of our latest webinar here.



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