AI Technology is Helping Fleet Managers Improve Safety and Increase Efficiency
With the use of AI and machine learning, fleets can enhance vehicle and driver safety, monitor vehicle maintenance, and streamline work operations.
Artificial Intelligence (AI) in fleet management drastically improves how transportation businesses operate. Combined with machine learning, AI bases data on driver learning behaviors, making tailored predictions. Barrett Young, SVP, Marketing at Netradyne, shares how fleets harness the technology to improve and automate decisions, increase vehicle and driver safety, and reduce vehicle downtime.
Transportation businesses have begun to reap the benefits of Artificial Intelligence (AI) to mitigate risk in the cab and on the road, better manage costs, and improve overall compliance. The main applications of AI that help power fleet operations are the Internet of Things (IoT), Machine Learning (ML), Predictive Analytics, and Computer Vision-based automated communication.
The use of this technology creates safer roads, improves safety culture, and modernizes the trucking industry. The data provided by AI solutions help fleet managers make streamlined decisions to improve driver safety while tracking costs and tracking fleet operations.
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Prioritizing Driver and Vehicle Safety
With an AI-powered fleet safety system in place, fleets detect risky driving behavior and common compliance violations, such as speeding, distracted driving, driver fatigue, and more. This data gives fleet managers insight into drivers’ performance and track where a driver needs to improve or be rewarded.
Examples of risky driving behavior that are recognized by video safety systems are:
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- Distracted driving
- Following distance to other vehicles
- Hard braking
- Speeding
Fleet managers cannot accurately assess a driver’s skill without a reliable safety system giving real-time insight to identify risks. But AI-powered video safety systems learn to detect risky driving behaviors and alert drivers in real-time to make necessary corrections. In addition to alerting drivers when a correction needs to be made, the AI-powered dash cam will also reward a driver for practicing safe driving. This creates a needed balanced safety culture.
In-cab audio alerts notify drivers to correct dangerous driving behavior and warn of potential accidents in real-time. For example, if a driver is following too close to a vehicle, the driver will be immediately notified and can correct their driving at that moment. There is no need for a fleet manager to review the video at a later time and call the driver into their office. Making it easier to communicate with a driver and track a vehicle’s usage improves a trucking business’s proof of liability and workflow.
Fleet managers need to be able to access reliable data quickly to combat insurance claims, maintain driver compliance, and support drivers when an accident occurs. Machine learning sorts through large quantities of data, so drivers and managers know the impact and cause of an event. Also, ML-based dash cams learn from drivers’ behavior and predict risks around the vehicle by identifying and monitoring road signs, following distance, pedestrians, and other outside influences.
Improved Vehicle Maintenance Tracking
AI-based technology utilizes data to gain insights and make predictions. These data-driven predictions help identify potential wear and tear on fleet vehicles. With the ability to access this data quickly, fleet managers can better pinpoint and correct driving behaviors that cause long-term negative effects on vehicles.
With edge computing, dash cams respond to data in real-time with little lag time. Large amounts of data are processed quickly and can be accessed in remote locations. Edge computing also allows for data to be processed without having to fed to the cloud, adding an extra layer of security. Modern fleet vehicles feature a number of electronic parts and sensors that gather information about a variety of things, including fuel consumption, idling times, location, vehicle utilization, and driving hours, and more.
AI is able to predict issues and identify over-exertion points on a vehicle. Some examples would be AI-powered camera systems monitoring tire tread through miles driven or these systems being used as surveillance to provide evidence if parts are stolen from a vehicle. In addition, the Internet of Things (IoT), data analytics, and predictive maintenance enhance efficiency in vehicle care. Trucking companies better manage vehicle maintenance costs by having the advantage of these systems, trucking companies better manage vehicle maintenance costs.\
The Benefits of Reliable Data
Fleets utilize AI to improve decision-making based on diverse data types. This data is based on learning individual drivers’ behavior as they do their job. This is calculated into a score that helps determine areas the driver is improving and exhibiting risky driving behavior. An example of this would be when AI-powered technology determines that a driver turns at high speeds. Fleet managers are able to access this data and arrange for specific training for that driver. Customizable coaching also gives drivers the power to enhance their skills in their field and, in the long run, creates safer roads.
Vehicle maintenance issues like fuel consumption can be measured through data provided by AI. Data gathered from how a driver operates a vehicle, road conditions, and how the vehicle operates during service hours can be used to better pinpoint problem areas. Much like how driver data is learned over time making it customized, vehicle data collected can help make better predictions to when and how often a vehicle needs to be serviced. This technology enhances decision-making, saving time and energy for trucking companies.
Virtual coaching is another way AI enhances decision-making to optimize workflow. Fleet managers have easy access to driver videos and in-cab alerts analyzed by AI technology. By analyzing the driver’s safety risk alerts over the period of one work week, the AI algorithm gives drivers coaching tasks to resolve these behaviors. Since this is all done virtually, managers spend less time reviewing videos, and drivers improve safety more quickly.
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Driving Safety and Efficiency
Having an AI-powered safety system empowers fleets to prioritize safety without having to risk a decrease in efficiency and an increase in costs. Remote and automated coaching through the use of AI dash cams can save a company time and increase retention with drivers. With the use of AI and Machine Learning, fleets can enhance vehicle and driver safety, better monitor vehicle maintenance, and streamline work operations. Fleet managers can have a smoother workflow without compromising what’s important for their business and drivers.
Can you think of examples where AI and ML have improved safety? Share with us on Facebook, Twitter, and LinkedIn. We’d love to know!
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