Skip to main content

Ford and StreetLight Data combine on safety  

Collision data and travel patterns are overlaid to see where road improvements are needed
By Adam Hill October 16, 2020 Read time: 2 mins
Bike, pedestrian and vehicle safety issues can be tackled, the two firms say (© Monopoly Monopoly | Dreamstime.com)

Ford Mobility and StreetLight Data have launched a data package which they say offers insights into road safety for departments of transportation and local authorities.

Safety Solutions brings together Ford’s Safety Insights tool - which uses collision data and connected vehicle input on near misses to find potential accident hotspots – and StreetLight’s Software as a Service (SaaS) platform StreetLight InSight, which supplies travel pattern data based on smartphones and navigation devices in connected vehicles, trucks and Internet of Things devices.

The new bundle can overlay crash information with vehicle, bicycle and pedestrian metrics to work out in which locations authorities should act to improve traffic safety.

“This kind of collation and analysis was previously very time-consuming and often lacked any visual representation to help planners and engineers rapidly identify, analyse and recommend countermeasures for particular safety concerns,” says Cal Coplai, product owner of Ford Mobility’s Safety Insights.

In a separate announcement, StreetLight’s data analysis has revealed that Covid-19 has changed traffic patterns in the US, shifting the morning rush hour in particular. 

Instead of the typical sharp increase in morning travel, followed by a drop and then an afternoon peak, the vehicle miles travelled (VMT) analysis shows weekday traffic building gradually toward a more sustained afternoon high.

In cities there are still ‘peak PM’ commutes – but the peaks are less pronounced.

Washington, DC, now has a slightly earlier peak for PM travel than during the same period in 2019, while Los Angeles and San Francisco have a “mini rush hour” just after lunch.

PM congestion begins earlier - but ends sooner – and there is more vehicle travel around midday than was the case last year.

For more information on companies in this article

Related Content

  • China aims to boost road safety with drink driving crackdown
    April 25, 2012
    The authorities in China claim that tough new laws against drink driving are already having a major benefit for road safety, according to the official news agency Xinhua. The latest official statistics reveal a sharp drop in road accidents caused by drink driving over a recent long holiday weekend. The newly amended law imposes harsher punishments on drunk drivers, with police also taking a tough line on enforcement.
  • San Diego: Let there be (street)light
    March 30, 2020
    The influence of intelligent streetlights is spreading. David Crawford finds that San Diego’s deployment – and attendant legislation – may offer a blueprint for other cities going forward
  • euroFOT study demonstrates benefits of driver assistance systems
    June 26, 2012
    Today, the euroFOT consortium published the findings of a four-year study focused on the impact of driver assistance systems in the Europe. The €22 million (US$27.5 million) European Field Operational Test (euroFOT) project which began in June 2008 and involved 28 companies and organisations, was led by Aria Etemad from Ford’s European Research Centre in Aachen, Germany. The study looked at existing technologies and their potential to both enhance safety and reduce environmental impact. euroFOT also reveale
  • Cellint measures speed and travel time without roadside infrastructure
    April 10, 2014
    Collecting speed and travel time data without using roadside infrastructure could offer new possibilities to cash-strapped road authorities. Streaming video may be useful for traffic controllers to monitor incidents and automatic number plate recognition may be required for enforcement, but neither are necessary for many ITS functions. For instance travel times, tailbacks, percentage of vehicles turning, origin and destination analysis can all be done using Bluetooth and/or WI-Fi sensors and without video o