Maps on mobile: applying the prisoner’s dilemma to suggested routes

Seeing red at 8:30am on Google Maps

Seeing red at 8:30am on Google Maps

This was the Bay Area traffic map this morning. The red? That’s where traffic is at a standstill. Asking for route through this mayhem brought up three different options, all through varying degrees of traffic. None took me on lesser streets, all on either the freeway or a major expressway.

Map apps are consistently among the top 10 mobile apps, by unique users, meaning that, as expected, people use them on the go all the time. Yet, when put to the morning commute test, Google Maps comes up short. Before we discuss what can be done, let’s take a look at what already exists.

  1. Real-time traffic reports are a huge benefit, down to major street level, and allows better planning of routes to avoid traffic.
  2. Waze, which was bought by Google last year and is partly integrated into Google Maps, displays real-time reports by users of road incidents such as accidents and blockages. These don’t currently add a lot of value to Maps as it is already pretty clear where an accident occurred based on the traffic accumulating behind it. Waze’s dynamic route planning doesn’t seem to have been incorporated into Maps yet (see item four, below.)
  3. Typical Bay Area traffic at 12:30 on a Tuesday

    Typical Bay Area traffic at 12:30 on a Tuesday

    The desktop version of Maps allows users to see typical traffic for any hour of the week. That’s a feature I only discovered today as I haven’t opened up Maps on the desktop in months. That’s a great planning tool.

  4. On-demand route planning in the mobile app is, well, let’s just say it could be better. Usually a maximum of three options are shown and even those three have caused me to scratch my head on a number of occasions (routing me from San Francisco to Palo Alto via the Bay Bridge, over to 880 then back to the Peninsula on the Dumbarton?)

So where could Maps be better and help everyone get to their destination faster?

I think Waze was on the right track: making constant changes to routes based on live traffic conditions. Directing drivers to avoid major congestion sends less cars that route and the congestion can ease up. Directing drivers to less busy routes helps distribute traffic and makes everyone happier. Not that this works flawlessly yet, and some routes still look ludicrous and too roundabout to be considered more efficient, but overall, this is the way to go. Also, this might mean that route-planning needs to consider not just the current user asking for a route but all users/drivers currently on the road. It would be interesting to see if users understand that by following a plan everyone benefits… sort of like the prisoner’s dilemma, but for traffic.

Then, after optimizing on-demand route planning, consider historical traffic patterns. Take, for example, an accident that occurs on a major highway during the afternoon commute. It initially blocks 3 out of 5 lanes of traffic. How long does it take for the resulting congestion to ease up? How different is this on a Friday? How long does traffic need to be routed on an alternative highway?

Use more information to create routes. For example, planned times of local events such as sports and concerts and other festivals, with live updates. A few months ago I was routed through AT&T Park in San Francisco just as the Giant’s playoff game ended. I drove straight into a traffic mess which could have easily been avoided.

Finally, learn from experience. With users’ permission, analyze the route they took vs the one Maps suggested. How long did it take compared to the suggested route? What roads did that user prefer? Does it make sense to personalize driving directions based not only on the starting point and destination but prefered roads? Constantly optimize and improve and, who knows, maybe we’ll all see less red on the road.



One thought on “Maps on mobile: applying the prisoner’s dilemma to suggested routes

  1. Pingback: The continuing evolution of Google Maps | What it all boils down to

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