Electric shuttle on-demand mobility cab service with LIDAR sensors

Massachessets July 28: Carmaker Ford is working with MIT on a research project that will deploy a new fleet of on-demand electric shuttles that can ferry students from class-to-class both on campus and on city roads at MIT’s Cambridge, Massachussets . Students can hail one of three electric shuttles using an app on their smartphone, and a driver will arrive quickly to pick them up. The research projects hopes to shed light on pedestrian traffic patterns, using LiDAR and other sensors combined with data including weather info and class schedules to optimize the on-demand service.

From September the Massachusetts Institute of Technology’s Cambridge campus will become the testing ground for a fleet of three electric shuttles that will be hitting the roads and walkways around the campus.

“The [shuttles’] onboard sensors and cameras gather pedestrian data to estimate the flow of foot traffic,” said Ken Washington, vice president of Research and Advanced Engineering at Ford.

The key to these sensor arrays is LiDAR, which a growing number of carmakers, Ford included, believe is the most accurate way for detecting individual objects and understanding their position relevant to a vehicle, whether those objects are other cars on the road or pedestrians on the pavement or waiting to cross.

However, instead of spotting and avoiding a pedestrian, as with an autonomous vehicle, in these shuttles, they are identifying people in order to understand how and where people move in order to calculate the optimum geographical location to wait at any one time between ride hails. Think an elevator that can “guess” which floor it should stop at before it is summoned.

“Through the mobility-on-demand system being developed for MIT’s campus, the Aeronautics and Astronautics Department’s Aerospace Controls Lab can investigate new planning and prediction algorithms in a complex, but controlled, environment, while simultaneously providing a test bed framework for researchers and a service to the MIT community,” said ACL director Professor Jonathan How.

Bryan Goodman, Ford’s Manger and Technical Leader of Autonomous Vehicle Analysis and the project lead says that data is being analyzed to accurately predict demand, which processed by algorithms that try to identify the best places for the shuttles to be positioned to maximize customer service.

These locations are then fed back to drivers to inform their driving routine, and the process continues cyclically to try to achieve the best possible results regardless of time of day, weather conditions or other variables.

Goodman said that the current phase of the project is scheduled to run through the end of this year, but MIT and Ford are already working on what the next phase or phases might look like.

One of the next steps, he says, will be to replace the driver-operated electric shuttles (which Ford terms “mobility-on-demand” or MOD vehicles) with fully autonomous versions, and the data and learning acquired during this phase will be key to achieving that goal.

“This helps us develop efficient algorithms that bring together relevant data. It improves mobility-on-demand services, and aids ongoing pedestrian detection and mapping efforts for autonomous vehicle research,” said Washington.