Optimization Tools to Help Transit Agencies Recover

I spoke last week with Krishna Desai from Cubic Transportation, and we discussed three big problems facing transportation, and the ways that Cubic is approaching these challenges:

1) If (or when) more workers return to traditional on-location jobs, but feel a lingering distrust of crowded spaces, people who can afford it may opt for private cars instead of using public transit for their commute. This will create a massive influx of cars on roads that were already crowded, and more financial woes for transit agencies already dealing with budget shortfalls. Krishna told me about a suite of optimization tools Cubic is deploying in places like Mexico and San Francisco to make public transit more efficient, more transparent, and, overall, more attractive to riders.

2) For the time being, though, we’re dealing with the opposite problem. How can transit agencies find ways to influence user behavior in a way that complies with social distancing and capacity requirements? How can you incentivize riders to wait for the next bus? (In a way that doesn’t alienate them forever – see #1). Cubic has deployed a loyalty/advertising program in Miami-Dade County that was originally intended to increase ridership, but is now being used to help control crowding and social distancing on transit.

3) Transportation infrastructure, in generally, was not built to accomodate 6-feet of separation between riders – or between workers. Little things like, for example, opening gates, requires workers to be closer than 6-feet to riders, and there are examples like that throughout every transit hub. Technology can help, but creating and implementing software/hardware solutions quickly and efficiently requires experience with innovation, deployment, maintenance and more. Cubic has a program called Project Rebound that shows the possibilities.

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