StreetLight Data releases AAHT metrics

StreetLight Data is making annual average hourly traffic (AAHT) counts and monthly annual daily traffic (MADT) counts available to transportation planners via its cloud-based software platform InSight. The company says AAHT and MADT help identify and forecast traffic conditions for specific days or months of the year. StreetLight co-founder Laura Schewel says: “Transportation planners have always found it difficult to deliver accurate monthly and daily traffic data due to technological constraints, increa
September 17, 2019 Read time: 2 mins

8830 StreetLight Data is making annual average hourly traffic (AAHT) counts and monthly annual daily traffic (MADT) counts available to transportation planners via its cloud-based software platform InSight.

The company says AAHT and MADT help identify and forecast traffic conditions for specific days or months of the year.

StreetLight co-founder Laura Schewel says: “Transportation planners have always found it difficult to deliver accurate monthly and daily traffic data due to technological constraints, increasingly tight budgets, small survey response numbers and datasets, as well as complex seasonality factors.”

For example, a community in Florida may want to gather traffic information during April and then estimate monthly metrics from that data. The AAHT and MADT metrics allow the community to obtain information on heavier tourist traffic during winter months or lighter travel mid-summer with near real-time results, the company adds.

These metrics can also help determine funding needs for highway improvements and forecast road maintenance expenditures, it says.

Urban Traffic Control

For more information on companies in this article

Related Content

  • Lyft, Uber have mixed impact on San Fran mobility
    May 14, 2018
    The extent to which ride-hailing has become a real force in the mobility landscape of San Francisco is great for consumers – but there are downsides, a report finds. Andrew Stone takes a look. Uber and Lyft, the two major ride-hailing platforms in San Francisco, are out-competing local cab firms in many ways - and are firmly established as a significant part of the daily mobility mix there, a recent study reveals. Researchers mined publicly-available data derived from the application programming interface
    Read More
  • PTV simulates York’s future
    August 26, 2021
    PTV’s predictive software modelling is helping one of England’s historic cities to improve traffic flow
    Read More
  • GIS mapping of road-related assets can pay dividends
    June 6, 2014
    Map-based computerised road asset management can pay dividends as Colin Sowman discovers.
    Read More
  • Healthy prospects for floating vehicle data systems
    February 3, 2012
    Elmar Brockfeld, Alexander Sohr and Peter Wagner from the German Aerospace Center's Institute of Transport Systems look at the prospects for floating vehicle data systems. Although Floating Vehicle Data (FVD) or probe vehicle fleets have been around for about a decade, the idea behind them is of course much older: from probe vehicles that flow with the traffic it should be possible to get a precise, fast and spatially near-complete picture of the prevailing traffic flow conditions in an area under surveilla
    Read More

Highlighted Content