Walter Wurm

The inspiration behind dreyev.

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

Virtual Passenger

Walter mimics the behavior of a dependable passenger

Walter can evaluate the risk and match it against the level of attention exhibited by the driver.  The risk is associated with the current speed, acceleration, braking, cornering, pavement, weather and vehicles, people or objects on the road. 

Computer Vision

Cost-effective technology

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.

• 360° View of fleet daily operations
• Driver ID via facial recognition

Timely Alerts

Artificial Intelligence

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.

• Driver performance dashboard and insights
• Track fleet in real-time