Top chart: Metropia’s point distribution profile was adjusted to lure drivers away from am/pm rush hours. Bottom chart: The blue line represents the % change in trip departure times following the deployment of the New Point Profile. Below zero signifies a decrease in trips departing at that time; Above zero signifies an increase in trips at that time.

The Metropia app empowers drivers to make informed travel decisions regarding what time to leave and what route to take in order to avoid traffic on their commutes. By planning trips in advance, users can clearly see how shifting their departure time in 15-minute increments can yield big savings in travel times.

Alongside the travel time savings displayed, Metropia employs behavioral economics through an intricate system of reward points which further nudge users away from heavy traffic and toward less-congested travel times. Trips taken during peak traffic receive minimal points, while trips during free flow traffic are higher. Points can be redeemed within the Metropia app for rewards like gift cards to local merchants, or donated to charitable causes like feeding the elderly or planting trees.

In an effort to test drivers’ willingness to shift travel times beyond current levels, Metropia revised its point distribution system and conducted a month-long experiment in El Paso.

  • To incentivize more users to shift their departure times outside of peak traffic, Metropia greatly lowered the number of points earned for travel during rush hour both in the morning (7:30am - 8:30am) and evening (4:15pm-5:15pm) to just 20 points. Conversely, the points available on the shoulders of rush hour spiked to 100 points in an effort to lure drivers away from gridlock and in favor of freer flowing roads (see New Point Profile, top figure). A more gentle tapering of points outside of those spikes assured that drivers wouldn’t be lured toward the shoulders of peak traffic from outside times.
     
  • Metropia conducted a month-long study of existing users comparing travel departure times before and after the implementation of the New Point Profile to gauge the new system’s efficacy.
  • The study revealed that user behavior closely mirrored the new point profile (see % of Departure Time Change, top figure).
     
  • There was a 13% overall decline in trips taken during morning rush hour with a 7% rise in trips taken during the subsequent, less-congested hour, reflecting the shift in departure times. Evening travel experienced similar patterns, with trips increasing before and after peak congestion while dropping below previous levels during rush hour itself.
     
  • The new point distributions system proved so effective that we deployed it in our other markets with equal success in shifting our users’ departure times and mitigating their impact on regional traffic.