Waste Management In Action

Identifying known and unknown risks: DriveRisk

DriveCam’s algorithms and predictive analytics help to define risk profiles and enable operators to prioritise action.

Waste vehicle fleet operations are inherently risky from a driving perspective. As such, drivers need to be monitoring and mitigating these risks every day to run a safe operation. But what is the most efficient way?

According to Mark Dudman, DriveRisk Senior Risk Consultant, “Known Risks” in lay terms are things drivers know are risky – crossing a flooded roadway, and in context of transport operations, insufficient maintenance, or letting an unqualified person drive.

“You know that there is an exceedingly high probability for things to end badly,” he says.

“Unknown Risks” are the things that happen without the knowledge of a business owner – mobile phone use while driving, tailgating or cornering with excessive speed.

“These behaviour-based risks happen all day, every day and not just in the commercial driving sector.This is a societal issue and is a major contributor to collision rates increasing on our roads and its unfortunately getting worse,” Dudman says.

He adds that identification of risk is a challenge.

“You need a system that captures and identifies risky behaviour before it ends in disaster. A system which has the intelligence to provide meaningful data and report on previously unknown risk,” Dudman says.

“Once this risk has been captured, operators need to take meaningful action to prevent or mitigate this from becoming repetitive.”

DriveCam’s algorithms and predictive analytics help to define a risk profile and enable operators to prioritise action.

“Prioritisation based on severity or collision likelihood means you are actively reducing your risk footprint and managing risk reduction processes aligned directly with your CoR (Chain of Responsibility) obligations,” Dudman says.

“The idea of monitoring your driver in general has negative connotations, but this is not how DriveCam targets risk. Whilst there is an element of risk monitoring involved, it is not constantly recording video of the driver.”

There are serious concerns from a CoR obligation with this approach, Dudman explains.

He adds that trawling through hours of video data to uncover potential risks or non-compliant behaviours and take appropriate action to mitigate against repeat behaviour is costly, both in man hours and potential legal issues.

To avoid those issues, Dudman recommends a exception-based closed loop system.

“An exception-based process empowers drivers to control what is captured,” he says.

“Our Machine Vision and Artificial Intelligence enabled system only looks for patterns of specific risk. It is not continuously recording. The algorithm simply uses known or learned patterns and measures the time this risky behaviour occurs and will capture a sample video clip for coaching.”

Dudman explains that the video event data is then used to coach drivers to change their behaviour.

“Finding the right tools for the task requires companies to adopt an appropriate safety system and supporting video technology,” he says.

“Businesses looking to build a safety culture can utilise technology like DriveCam, a leading-edge tool that captures risky driving behaviour and allows you to mitigate your on-road risk profile in a timely and cost-effective manner to prevent incidents and save you money.

“Once you have mitigated your risk everyone wins.”

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