Study by Virginia Tech Transportation Institute Reveals Motive's AI Dashcam Successfully Alerts Drivers to Unsafe Driving Behavior 86% of the Time

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The Motive AI Dashcam successfully alerted drivers to unsafe driving behavior 86% of the time, compared to 21% for Samsara and 32% for Lytx.

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Business Wire, Inc.Business Wire, Inc.
Retrieved on: 
Tuesday, July 25, 2023
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Automotive, Technology, Trucking, Transport, Other Automotive, Software, Artificial Intelligence, Audio, Video, Internet, Fleet Management, Hardware, Accident, Research, Fatality, Human voice, S&P Global, S, Weather, Brazilian jiu-jitsu ranking system, Medical device, Mobile phone, Distribution (marketing), Tea, Motive, Lytx, AI
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UNITED STATES, NORTH AMERICA, CALIFORNIA
⚠ generated by AI ↴
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MOTIVE, VIRGINIA TECH TRANSPORTATION INSTITUTE
Summary
Key Points: 
  • The Motive AI Dashcam successfully alerted drivers to unsafe driving behavior 86% of the time, compared to 21% for Samsara and 32% for Lytx.
  • Even worse, the principal cause of these accidents – including distracted and unsafe driving behavior – are 100% preventable,” said Shoaib Makani, co-founder and CEO at Motive.
  • We will work tirelessly to improve our AI models and overall safety solution until we and our customers reach that goal."
  • “The study highlights significant performance differences between the AI-powered dashcam providers in alerting drivers of unsafe driving behaviors across multiple conditions and scenarios,” said Susan Soccolich, Senior Researcher, Virginia Tech Transportation Institute.


Motive, the leader in Automated Operations for the physical economy, today announced the results of a controlled test track study conducted by the Virginia Tech Transportation Institute (VTTI) that found Motive’s AI Dashcam successfully generated alerts related to six unsafe driving behaviors 3-4 times more than the latest models from Samsara and Lytx. The Motive AI Dashcam successfully alerted drivers to unsafe driving behavior 86% of the time, compared to 21% for Samsara and 32% for Lytx.

“There is an epidemic of road accidents and fatalities that continues to worsen but, with advancements in AI, they should be getting better. Even worse, the principal cause of these accidents – including distracted and unsafe driving behavior – are 100% preventable,” said Shoaib Makani, co-founder and CEO at Motive. “The results of VTTI’s research are not just about comparing products. They show that these technologies don’t all perform the same, which can have major implications for accident prevention. At Motive, our goal is to achieve zero harm and zero preventable accidents. We will work tirelessly to improve our AI models and overall safety solution until we and our customers reach that goal."

The study specifically observed the likelihood of each system (the Motive DC-54, Samsara’s HW-CM32 and the Lytx Drive Cam SF400) to generate alerts for common unsafe behaviors, and found the Motive AI Dashcam to be associated with statistically significant, higher likelihoods to achieve this. Distracted driving behaviors where this was particularly prominent included:

  • Phone Call Overall Alert Rates: Motive: 95%, Samsara: 38%, Lytx: 28%
  • Texting Overall Alert Rates: Motive: 71%, Samsara: 30%, Lytx: 13%

The unsafe behaviors the study observed were close following, rolling stops and not using seat belts. At least one competitor model showed no successful alerts for either rolling stops or not using seatbelts, and there was a stark difference between the models in likelihood of generating an alert for close following:

  • Rolling Stop: Motive 77%, Samsara 0%
    • The study excluded Lytx's rolling stop alerts due to Lytx’s decision to deactivate the alert feature for all customers during the study period.
  • Seat Belt Use: Motive 100%, Lytx 100%, Samsara 0% alert rate overall
  • Close Following Overall Alert Rates: Motive: 67%, Samsara: 18%, Lytx: 28%

Finally, the AI Dashcam had significantly shorter time to alert compared to Lytx for phone call tasks, 45-degree texting, and no seatbelt trials and significantly shorter time to alert for close following trials compared to Samsara.

“The study highlights significant performance differences between the AI-powered dashcam providers in alerting drivers of unsafe driving behaviors across multiple conditions and scenarios,” said Susan Soccolich, Senior Researcher, Virginia Tech Transportation Institute. “VTTI conducts research to first and foremost save lives, from driver to passenger to pedestrian. Studies like this one can help progress safety in the transportation industry by identifying situations where technologies can improve its real-time alerts of unsafe behaviors to drivers.”

“When it comes to facilitating and reinforcing safety, enterprises increasingly understand the value of driver monitoring for their distributed operations,” said Mark Fontecchio, research analyst at S&P Global Market Intelligence. “Our recent Voice of Enterprise survey revealed that 64% of commercial trucking companies have driver monitoring in place today, underscoring the potential value for the industry and wider physical economy in continuing to innovate and improve the performance of these technologies, particularly with the integration of AI and IoT.”

Motive recently announced the launch of the AI Omnicam, the first ever AI-enabled camera built for side, rear, passenger, and cargo monitoring to provide an intelligent 360 degree view of fleet assets. In addition, the company recently rolled out a series of enhancements that expand the functionality of its leading Driver Safety Solution to combat worsening safety conditions.

To view the full report, visit here. To learn more about Motive’s Driver Safety Solution, visit here.

Methodology

The study methodology involved protocols designed to mimic real-world conditions and driver behaviors on a closed test track. Testing was conducted across three placement locations and three different times of day (daytime, dusk, and nighttime). The systems were installed by a certified, professional third-party installer to ensure that the placement of the cameras met each technology provider’s installation standards. Factors that could influence system performance, such as weather conditions, driver identity, and system placement, were carefully controlled to maintain the integrity of the study. For the full methodology and results, please find the full report and data here.

About Motive

Motive builds technology to improve the safety, productivity, and profitability of businesses that power the physical economy. The Motive Automated Operations Platform combines IoT hardware with AI-enabled applications to automate vehicle and equipment tracking, driver safety, fleet compliance, maintenance, spend management, and more. Motive serves more than 120,000 businesses across a wide range of industries, including trucking and logistics, construction, oil and gas, food and beverage, field service, agriculture, passenger transit, and delivery.

About Virginia Tech Transportation Institute

For 35 years, VTTI has conducted research to save lives, time, and money and protect the environment. In their world-class facilities, they investigate, invent, design, develop, refine and test transportation systems of the future. As one of seven premier research institutes created by Virginia Tech to answer national challenges, VTTI is continually advancing transportation through innovation and has affected public policy on national and international levels. VTTI is known for robust transportation studies, both with public partners, as well as with private partners, original equipment manufacturers, and suppliers on proprietary research. Established in 1988 as the University Center for Transportation Research, VTTI is now the second largest university-level transportation institute in the U.S. and is home to the largest group of driving safety researchers in the world.

Disclaimer: This research was funded by Motive. Although care has been taken to ensure complete and accurate study results, recipients of this document accept the possibility of unintended errors or omissions. The results expressed in this document are based on data collected from March 13th 2023, through May 2nd 2023, under specific testing conditions that may not apply to other circumstances. This study does not imply endorsement of any products mentioned in this report.

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