STOCKHOLM, March 12, 2020
STOCKHOLM, March 12, 2020 /PRNewswire/ -- A significant number of groups in traffic globally have recently started to drive much more unfocused and insecure according to Greater Than's AI and driving analysis Enerfy. The AI has over the past four weeks began to recognize a significant change in driving patterns. The change occurs extraordinarily amongst user groups that previously drove with overall low-risk behavior. The same sample and groups today suddenly show a far more dangerous driving behavior in traffic and are sliding towards medium or higher risk behavior groupings.
"We're now facing both health and financial crisis, causing overall stress amongst individuals in almost all societies. This big hit generates waves everywhere, also riskier driving patterns," says Anders Lindelöf, CTO and co-founder Greater Than.
Otherwise, when the Enerfy AI reacts with such bright and direct indicators it's usually before specific holidays - when more people are more stressed. Such times are days prior to New Year's Eve, spring breaks, and other major holidays. Times when a lot of people are on the move at the same time. A collective change towards a much risky driving behavior generally affects both the overall traffic pattern and the individual driving behavior per se. This significantly transforms the total traffic environment and makes it more unsafe, unfortunately also with more accidents as a result.
"We at Greater Than always make in-deep analysis when our AI reacts and identifies sudden changes in driving behavior - both for the better but in this case, sadly to the worse. All we can hope for now is that people will calm down and to put extra focus when behind the steering wheel," continues Anders Lindelöf.
This type of reaction happens periodically when individual and collective changes of stress level occur over periods, in this example, when whole societies go into an enormous crisis. The Artificial Intelligence Enerfy identifies real-time driving patterns with 99,98% accuracy to factual risk and level of accident probability.
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