At best, today's telematics solutions replicate having a virtual blindfolded passenger along for the ride to observe the behavior of the driver to increase safety and minimize the risk of accidents. But does a blindfolded passenger make you a safer driver?
Walter is the only Driver Safety Platform that analyzes driver behavior and responsiveness 100% of the time, generating real-time alerts to prevent crashes, and identifying areas of driver improvement.
State bans on the use of cell phones in cars don't seem to be effective as accidents caused by distracted driving continue to rise.
Mobile applications that intercept distracting calls or the use of apps are easy to circumvent and distractions can also come from sources other than mobile phones.
The old-fashioned way to solve the problem is to have a front seat passenger who 1) is aware of sudden driving risks, 2) can tell whether the driver is paying attention, and 3) will warn the driver when needed.
Driver Safety Platform with Co-Driver Expertise
The inspiration behind dreyev.
Having a virtual passenger that doesn't rest.
Breakthoughs in video technology have made computer vision affordable.
Driving habits will change over time and dreyev will learn them.
My grandfather, Walter, was an incredibly passionate, safe, and reliable car driver. Born in 1907 in a little town in Austria, he drove 1.7 M miles over the next 50 years, crossing Europe as a very entrepreneurial CEO of a dynamic leather manufacturing business. He always preferred driving himself to meetings over flying, even as flying started becoming more widely available.
He drove top-of-the-line Audi, Mercedes, BMW cars, enjoying the latest technologies, and sharing the pleasure of the ride with his passengers.
As I turned 18 and switched from my beloved motorcycle to driving a car, I remember that I could not wait to showcase to him, my hero, how good a driver I had become.
I remember rehearsing my trip around town several times before he sat in as a passenger (a rare event…!). I did my best to drive as smoothly and precisely as I could. At the end of the tour, he told me: “Roberto, you have good skills, but you look around too much.”
His remark hurt, as I was convinced that I had done a stellar job showing my driving skills. But later, I realized why he was so concerned about me putting attention to the road, all the time. That inspired us to name our driver solution platform after him.
- Roberto Sicconi
Driver attentiveness and alertness is measured using a computer vision technology to analyze head pose, eye gaze, and eyelid closing to flag possible distraction and drowsiness.
To increase adoption and effectiveness, Dreyev uses AI and Machine Learning to create custom model of driving habits and experiences to ensure driver tendencies and paired with road conditions.
Machine learning enables the creation of custom models of driving habits and experience to ensure that warning are only given when necessary.