“That’s us in a nutshell: insights and incentives to attack congestion,” says CEO and co-founder Shiva Shivakumar, a former Google engineer. “The better you can understand both sides of the [supply-demand] equation, the better you can start optimizing it.” On the insight side, Urban Engines relies on an approach called “crowd-sensing” to understand what’s happening across an entire city transport system. Let’s take the example of a subway. Each fare card entry swipe delivers basic information on rider location and (at least for cities that require a swipe in and out) total travel time. Using algorithms and supplemental data, such as real-time transit schedules, Urban Engines can deduce what’s happening at any given subway station or train at any given time. (via Using Insights and Incentives to End Rush Hour - CityLab) […] The incentives side of Urban Engines draws from programs that Prabhakar has helped conduct that pay commuters to travel at off-peak hours. Recognizing that too few cities had implemented congestion pricing plans, Prabhakar and collaborators have taken the opposite tack — rather than charge commuters who traveled during rush hour, they reward them for traveling outside it. In behavioral terms, it’s a carrot instead of a stick, and Prabhakar says it’s been successful so far in Bangalore, Singapore, and Palo Alto.

Publié le 16 Mai 2014

“That’s us in a nutshell: insights and incentives to attack congestion,” says CEO and co-founder Shiva Shivakumar, a former Google engineer. “The better you can understand both sides of the [supply-demand] equation, the better you can start optimizing it.” On the insight side, Urban Engines relies on an approach called “crowd-sensing” to understand what’s happening across an entire city transport system. Let’s take the example of a subway. Each fare card entry swipe delivers basic information on rider location and (at least for cities that require a swipe in and out) total travel time. Using algorithms and supplemental data, such as real-time transit schedules, Urban Engines can deduce what’s happening at any given subway station or train at any given time. (via Using Insights and Incentives to End Rush Hour - CityLab)
[…]
The incentives side of Urban Engines draws from programs that Prabhakar has helped conduct that pay commuters to travel at off-peak hours. Recognizing that too few cities had implemented congestion pricing plans, Prabhakar and collaborators have taken the opposite tack — rather than charge commuters who traveled during rush hour, they reward them for traveling outside it. In behavioral terms, it’s a carrot instead of a stick, and Prabhakar says it’s been successful so far in Bangalore, Singapore, and Palo Alto.

“That’s us in a nutshell: insights and incentives to attack congestion,” says CEO and co-founder Shiva Shivakumar, a former Google engineer. “The better you can understand both sides of the [supply-demand] equation, the better you can start optimizing it.” On the insight side, Urban Engines relies on an approach called “crowd-sensing” to understand what’s happening across an entire city transport system. Let’s take the example of a subway. Each fare card entry swipe delivers basic information on rider location and (at least for cities that require a swipe in and out) total travel time. Using algorithms and supplemental data, such as real-time transit schedules, Urban Engines can deduce what’s happening at any given subway station or train at any given time. (via Using Insights and Incentives to End Rush Hour - CityLab)

[…]

The incentives side of Urban Engines draws from programs that Prabhakar has helped conduct that pay commuters to travel at off-peak hours. Recognizing that too few cities had implemented congestion pricing plans, Prabhakar and collaborators have taken the opposite tack — rather than charge commuters who traveled during rush hour, they reward them for traveling outside it. In behavioral terms, it’s a carrot instead of a stick, and Prabhakar says it’s been successful so far in Bangalore, Singapore, and Palo Alto.

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