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:
- 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.
- 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.
- Transportation infrastructure, in general, 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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