Skip to main content

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.

For more information on companies in this article

Related Content

  • Manchester seeks smart but not selective transport solutions
    January 25, 2018
    Smarter transport relies on better communications both with travellers and between transport providers. Andrew Williams reports. Inrix’s prediction that the cost of traffic congestion will rise by 63% to £21bn per year by 2030 clearly illustrates that, in addition to the ongoing inconvenience and inefficiency, ongoing gridlock is a significant drain on the economy. It is against this backdrop that a Cisco-led consortium has launched CitySpire, a smart transport programme that uses location-based services a
  • New ANPR solutions overcome variables
    May 18, 2018
    The sheer range of variables makes it difficult to find a single algorithm to ensure a 100% standard of ANPR. David Crawford investigates new processing technology. Automatic number plate recognition (ANPR), using optical character recognition and image-processing to identify vehicles, plays key roles in traffic monitoring and law enforcement, access and parking control, electronic toll collection, vehicle security and crime deterrence. Overall, system performance is well rated, with high levels of
  • TM 2.0 boost TMC data feed and driver influence
    November 15, 2017
    TM 2.0 views connected vehicles and V2I as two-way communications channels, benefitting traffic management and drivers, as Alan Dron discovers. As connected vehicles are progressively rolled out there will come a point at which traffic managers and traffic management centres (TMCs) will have to gear up to cope with a rapidly-evolving road scenario. The TM 2.0 Platform (see box) is promoting a concept of new-generation traffic management (which carries the same TM 2.0 title) and is studying how future T
  • New opportunities in a data-rich future
    March 19, 2014
    Jason Barnes looks at where the detection and monitoring sector is heading. In the future, there will be no such thing as an un-instrumented road. Just a short time ago, that could have been a quote from a high-level policy document but with the first arrivals of vehicles with 802.11p connectivity – the door-opener to Vehicle-to-X (V2X) applications – it’s a statement which has increasing validity. The technology which uses our roads will also provide information on road conditions but V2X isn’t the only