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Smart Traffic Signals

 
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When? This feed was archived on June 04, 2017 15:55 (7y ago). Last successful fetch was on May 02, 2017 17:32 (7y ago)

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Manage episode 166463205 series 1220677
Content provided by The National Academies. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The National Academies or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Anchor Lede: Even the most sophisticated traffic signal timing systems only respond to local conditions, and might cause more harm than good on your drive home. Randy Atkins: City-wide traffic disruptions could result from even well-intentioned signal adjusting in one place. Carolina Osorio: You have to be able to forecast how people are going to react to that, and that is typically very difficult. Randy Atkins: Carolina Osorio , an MIT engineer, is creating models with data from driver surveys and observations aimed at synchronizing traffic lights across an entire city. Carolina Osorio: Were simulating tens of thousands of travelers and for each traveler he or she is making thousands of travel decisions throughout his or her trip. Randy Atkins: That takes time, even for a computer, and signaling decisions need to be made within minutes. So there are engineering challenges still to be worked out, but Osorio says the system could ultimately both reduce travel time and make it more predictable. With the National Academy of Engineering, Randy Atkins, WTOP News. MIT News Release
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50 episodes

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Archived series ("Inactive feed" status)

When? This feed was archived on June 04, 2017 15:55 (7y ago). Last successful fetch was on May 02, 2017 17:32 (7y ago)

Why? Inactive feed status. Our servers were unable to retrieve a valid podcast feed for a sustained period.

What now? You might be able to find a more up-to-date version using the search function. This series will no longer be checked for updates. If you believe this to be in error, please check if the publisher's feed link below is valid and contact support to request the feed be restored or if you have any other concerns about this.

Manage episode 166463205 series 1220677
Content provided by The National Academies. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by The National Academies or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.
Anchor Lede: Even the most sophisticated traffic signal timing systems only respond to local conditions, and might cause more harm than good on your drive home. Randy Atkins: City-wide traffic disruptions could result from even well-intentioned signal adjusting in one place. Carolina Osorio: You have to be able to forecast how people are going to react to that, and that is typically very difficult. Randy Atkins: Carolina Osorio , an MIT engineer, is creating models with data from driver surveys and observations aimed at synchronizing traffic lights across an entire city. Carolina Osorio: Were simulating tens of thousands of travelers and for each traveler he or she is making thousands of travel decisions throughout his or her trip. Randy Atkins: That takes time, even for a computer, and signaling decisions need to be made within minutes. So there are engineering challenges still to be worked out, but Osorio says the system could ultimately both reduce travel time and make it more predictable. With the National Academy of Engineering, Randy Atkins, WTOP News. MIT News Release
  continue reading

50 episodes

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