Report links driver assistance technology to driver complacency

Report links driver assistance technology to driver complacency (Photo: Nauto)

As driver assistance technology continues to expand in the transport sector, there has been a visible increase in the number of distracted driving cases, primarily due to drivers who place too much trust in technology to back them up during critical events on the road.

A report compiled by the AAA Foundation for Traffic Safety highlights that conclusion. Drivers experienced with advanced driver assistance systems (ADAS) technology were nearly twice as likely to be distracted while driving when ADAS is switched on, compared with when they were driving without help. ADAS is a technology ecosystem that improves driving experience by assisting drivers with features like adaptive cruise control, lane departure warning, and even automatic parking  

In contrast, drivers with limited experience using ADAS technology were far more attentive. AAA’s report stated that these drivers were less likely to drive distracted with or without ADAS being switched on. FreightWaves spoke with Stefan Heck, the CEO of Nauto, a Palo Alto-based startup that uses artificial intelligence to monitor driver behavior, about the impact of ADAS on driver behavior as it becomes an all-encompassing part of transport.

To understand the correlation between technology percolation and distracted driving, it is critical to distinguish the reasons why drivers get distracted. “For years, drivers have faced a multitude of distractions while driving — from eating, applying makeup, reviewing paperwork, shaving and talking to passengers,” Heck said. “But various in-vehicle technologies becoming more available and popular in the last few years has increased the number of things fighting for drivers’ attention.”

The foremost among these distractive technologies: smartphones. These gadgets have created a world where people can stay connected to work, friends, family and entertainment — all in real-time. Users check their screens every few minutes — the new normal — leading to the spike in attention deficiency cases while driving.

“Additionally, in-vehicle technology has become incredibly engaging and easy to use as we start answering emails and watching movies while on the road, representing another major source of distraction,” Heck said.

That said, ADAS as a technology does not lead to distraction but rather to driver complacency. “ADAS technology has introduced some helpful safety improvements, but these systems only cover a very narrow range of risks, like a lane departure warning when a car starts drifting into another lane,” Heck added. “ADAS has lulled drivers into a false sense of security, giving them overconfidence that their vehicles will automatically protect them while they check their phones on the road.”

In essence, it is critical for drivers to focus on the road ahead of them because current ADAS technology does not factor in driver attention or risky driver behavior. Existing solutions to this predicament include options such as installing in-cab cameras and video-based safety tools, which can scrutinize driving patterns and help improve driver behavior.

However, Heck contended that these technologies have limited scope as they are primarily reactive rather than proactive. “Standard in-cab and dash cameras are simply that — cameras with post-facto insights. Instead, an AI-based hardware/software combination can monitor and analyze both drivers’ attention and exterior risks; providing actionable in-vehicle alerts in real time when dangerous situations are detected is paramount,” he said.

Nauto uses interior cameras to identify and analyze not just driver movement, but also monitors the use of objects like phones and cigarettes to detect distracted, drowsy and risky driving. Exterior cameras, meanwhile, detect threats from the driving environment.

Nauto fuses all sensor data — including vehicle speed, location and telemetry data — to build a complete, real-time risk assessment and predict risky events in context.

“By analyzing billions of data points from over 500 million AI-analyzed video miles, Nauto’s machine learning algorithms continuously improve and help to impact driver behavior before events happen, not after,” Heck said. “Eventually, when you can redirect the driver’s attention back on the road, the need for many of the other types of common safety alerts decreases dramatically.”