HomeResourcesBlogHow Artificial Intelligence Impacts Fleet Management
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How Artificial Intelligence Impacts Fleet Management

By Alessandro Lori, PhD December 12, 2022

Artificial intelligence (AI) technology is a familiar concept across many industries, notably for its promise to accelerate digital transformation and disrupt existing markets and businesses. However, it is a tool that is just beginning to gain traction in the fleet management landscape. Fleet managers are coming to understand that AI is not meant to replace them, but rather assist in making their role more productive and streamlined. Ultimately, AI helps managers more closely address their business needs and supports the adoption of new technologies.

Artificial intelligence and autonomous vehicles

An obvious application of artificial intelligence is in autonomous vehicles. Completely autonomous vehicles – with level 5 autonomy – will rely heavily on artificial intelligence to interpret the environment and react accordingly, though this technological advance is still some way off. Lower levels of autonomy for vehicles are already available in the automotive industry today: cruise control, autopilot modes, tracking of lane departure and other features to improve driver safety. And while early examples of autonomous cars and autonomous driving technology are promising, there is a long way to go before entire fleets are comprised of solely autonomous vehicles. For fleets, experiments in platooning and the successful completion of longer distance autonomous trips by semi trucks have shown how AI has the power to change how fleet vehicles operate more safely and cost effectively.

How is AI integrated with fleet management today?

For years, fleets have been able to track mobile assets in near real time using telematics. But the sheer volume of data collected from on-vehicle sensors and the wider internet of things available today calls for the integration of much smarter management systems to help keep pace. This deluge of data is set to increase as new technologies like 5G enable ever bigger streams of data to help inform fleet management systems. AI can be used behind the scenes to achieve more sophisticated management of this modern tech.

And the timing is ideal, given that recent Verizon Connect research indicates 79% of senior operational decision makers believe their organizations need a better way of managing mobile workforce operations, and the majority admit there are difficulties when it comes to managing operations (65%) and fleets/assets (62%).1 AI can positively influence these issues and many more, while providing the technology to help fleets remain competitive in the face of future industry shifts.

Yet, it’s only recently that fleet managers have gained the ability to apply AI-backed learnings across the organization to fundamentally change how a fleet operates and communicates. Thanks to machine learning, the component of AI that enables a system to “learn” and continually refine its interpretation of big data sets, fleets can improve the accuracy of telematics-derived data related to driving behavior, asset tracking, utilization and overall operations to improve safety, productivity and cost-efficiency.

With so many variables to consider, including both mechanical and human elements, refining the way fleet operators address drivers, staff and equipment in near real time is crucial. Managers of successful fleets can use technology to identify trends, establish benchmarks, coach driver behavior in key areas and examine changes over time to:

  • Reduce idling and driver downtime
  • Reduce unwanted driving behaviors
  • Lessen miles driven
  • Improve driving directions
  • Track vehicles and assets
  • Dampen the potential for lost or stolen vehicles/assets
  • Improve dispatching via automation
  • Improve routes
  • Improve customer service
  • Improve efficiency to reduce costs

How Verizon Connect is using AI to improve video viability

According to Transport Topics, several years ago, onboard video was still a novelty used by only a small percentage of carriers. Now it has emerged as its own segment within the trucking technology sector.2

Today’s video solutions provide visual context to help understand the circumstances around a driving event, overcoming the previous limitations of only having numerical data as reference. AI-powered video eliminates the time-consuming task of sifting through hours of footage to find the precise event a fleet manager needs to review. It eliminates extraneous footage and makes any video snippet available in near real time.

In addition, the progressive analysis skills made possible by machine learning continuously improve the accuracy of automated classification event severity, so fleet managers are notified only when an event requires review.This means managers can broadenvisibility and deepen their knowledge of what goes on with their fleet, without having to manually sift through data or hours of footage.

Specifically, Integrated Video from Verizon Connect provides fleets, managers and drivers with the ability to:

  • Review harsh driving footage
  • Gain insight into fleet operations
  • Better protect the company against liability, particularly false claims
  • Improve driver performance
  • Better protect the company brand
  • Support insurance premium and discount negotiations
  • Mitigate risk

Modern integrated video solutions provide advanced capabilities made possible by AI, which increase operational efficiency and positively impact the bottom line:

Learn how an integrated video solution can enhance your fleet operations and safety with our free ebook.

AI filtering and machine learning: By filtering out inconsequential events and classifying events correctly based on preset parameters, fleet managers can continually refine classifications to accurately assess fleet operations on an ongoing basis.

AI-based analytics: Fleet managers save valuable time by applying AI algorithms to analyze every video, classifying them by type of event/severity level (e.g. harsh driving event, tailgating, distracted driving, critical, moderate, etc.).

Advanced coaching: Fleet managers can track driving styles and trends, and identify unwanted driving behaviors like harsh cornering, hard braking and speeding. This information can be used to create a driver coaching curriculum—for all drivers or for specific individuals—based on positive reinforcement.

Risk mitigation: Fleets can leverage video to mitigate risk by reducing false liability claims. Without the ability to back up a driver's account of an incident, owners are left with few options; and often, fleet owners may opt to avoid major lawsuits by paying out when accused of fault in an accident. Video solutions offer the ability to provide evidence that backs up driver accounts, enhancing trust between owners and drivers and helping to resolve false claims.

The future of AI is here

Advances in AI will continue. The International Data Corporation (IDC)predicts worldwide spending on cognitive and artificial intelligence systems will reach $57.6 billion dollars by 2021.3 And Grand View research predicts the global smart fleet management market size was valued at USD 291.1 billion in 2016 and is expected to expand at a CAGR of 7.7% over the forecast period, with need to achieve higher operational efficiencies and enhance vehicular safety being the primary factor driving the growth of the market.4

AI is making fleets smarter and more efficient, improving the bottom line and helping them proactively avoid issues and unexpected downtime. Fleets just now considering AI-backed digital transformation are already behind the curve. As technology like AI continues to become ingrained in the fleet industry, companies that adopt innovations now will have a much easier time keeping up with best-in-class competitors and standing out from the crowd.


1 https://www.gigabitmagazine.com/mobile/how-verizon-connect-helping-customers-run-smarter-fleet

2 https://www.ttnews.com/articles/onboard-video-gains-traction-trucking

3 https://www.idc.com/getdoc.jsp?containerId=prUS43662418

4 https://www.grandviewresearch.com/industry-analysis/smart-fleet-management-market

Alessandro Lori, PhD

Alessandro Lori, PhD, has 10+ years of experience in Web Software Development and Research in the field of data science and machine learning.

Tags: Cost control, Data & Analytics, Dispatching & Scheduling, Field management, Fleet utilization, Productivity & Efficiency, Revenue & ROI

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