How can Artificial Intelligence Determine Fleet Management in Future?

Artificial Intelligence (AI) is one of the trending topics these days. Its disruptive power has impacted various industries, with fleet management being no exception. According to expertmarket.com, the AI global market is set to grow from $25.5 billion in 2022, to a jaw-dropping $52.4 billion by 2027!  The average fleet driver depends heavily on telematics solutions and smartphones, while scalable algorithms work autonomously in conjunction with predictive vehicle performance models. They use detailed data analytics to generate optimal routes in real-time. Fleets can be enormously benefited thanks to AI, starting from recommending routes to analyzing on-road risk management data and even draining drivers to ensure safety isn’t compromised.

What is the role of AI in fleet management?

Fleet management involving AI involves leveraging AI-based technology to oversee fleet operations. Technologies are evolving fast, so it is imperative to put them to good use, as it streamlines the work of fleet managers by eradicating human error. AI-powered solutions recommend how fleet drivers, managers, and other stakeholders can make better decisions to boost fleet performance in the long-term. It is basically assistive tech, which ensures that drivers retain autonomy during each transport cycle.

There are several issues related to fleet management, such as:

• Prioritizing risks and generating efficiency
• Dangerous driving behaviors that lead to accidents
• Collecting data and analyzing it properly
• Risks on the road
• Adhering to compliance standards
• Reducing costs

Normally, managers depend on their drivers to avoid these signs as they have no way of knowing whether a driver has been texting while driving or dozing off at the wheel. However, AI systems can be structured to detect missed exits, head turns, blinking frequencies, yawning, and other signs of risky behavior. These signals can be sent to fleet managers in real-time to let them implement required action.

How can fleet management benefit due to AI?

AI basically analyzes large amounts of data, which is generated from telematics devices installed in vehicles, and makes accurate predictions based on this data. Telematics devices such as GPS trackers, dash cams, and sensors (Internet of Things or IoT-enabled sensors), generate a lot of information regarding vehicles’ status, including data on its movement, speed, location, fuel consumption, and more. As IoT develops, AI is advancing beyond predictive capabilities such as monitoring and automating maintenance schedules, training drivers to engage in safe practices, and optimizing routes.

Fleet analytics in real-time

Collating data is a crucial aspect of every operational process. If you don’t have sufficient data at your fingertips, it won’t be possible for fleet managers to generate insights and then make informed decisions. Historical data and data points in real-time, allows them to prioritize opportunities and risks – they can decide upon the best course of action during problematic situations.

AI systems can accumulate data for predictive analytics, including information on traffic and road conditions, real-time weather, environmental hazards, and mechanical faults. This data can be used to predict incoming risks and make better routes, schedules, maintenance deliveries, and dispatch arrangements to improve your business activities and outcomes.

Thanks to telematics devices installed in the vehicles, AI fleet management systems can monitor vehicles in real-time and identify potential issues, improve fuel efficiency, and even detect vehicle misuse. Once a problem is detected, an alert is triggered so fleet managers can implement corrective actions right away. It helps reduce risky accidents, lower fuel costs, and ensure your fleet’s safety 24/7.

Vehicle maintenance

Rather than depending on scheduled maintenance or waiting for signs of breakdown to occur, AI can evaluate and analyze vehicle use patterns, along with real-time data from IoT enabled sensors. Thus, they can detect minor issues of wear and tear, before they become bigger problems with exorbitant costs!

Using the data collected from your vehicle’s On-Board Diagnostics (OBDII), AI-powered fleet management software can alert you of the smallest problems. It goes a step further to immediately recommend specific actions you can take, such as replacing worn brake pads or changing engine oil, before they cause significant damage. This helps prevent breakdowns and reduces the risk of accidents on the road. AI can be used to automate your entire fleet’s maintenance record-keeping and scheduling. Thus, no vehicle is neglected, and you can rest assured that all assets are being utilized properly. 

Overcoming supply chain challenges

With the onset of the Covid-19 pandemic, the supply chain landscape has been marked by complexities and unpredictability, as a majority of consumers started shopping online. However, AI-powered solutions can address challenges such as frequent disruptions and heavy order volumes. Fleet managers are able to gain insights into supply chain dynamics, anticipate disruptions, and proactively adapt strategies. This is particularly significant in handling the surge in e-commerce orders, where rapid deliveries are paramount. Managers can optimize real-time routes, ensuring timely deliveries and meeting growing customer expectations for flexible delivery options.

Route planning

Planning and optimizing routes for a fleet can be tedious, especially if it is large in size. There are several aspects to consider such as traffic patterns, weather conditions, vehicle availability, etc. to ensure all assets operate efficiently and on time. By tracking fleet paths and locations in real time, fleet managers can prevent driver detouring, unauthorized stops, or inefficient routing. They get complete visibility into the movement of vehicles, thus allowing quick decision-making. For instance, if a delivery has to be completed on priority basis all of a sudden, managers can plan and alter routes on the fly, since a fleet management system is continuously mapping out the best routes. It means fewer delays, satisfied customers, and more revenue.

Improve efficiency and performance

If drivers are engaging in particularly risky behavior such as taking sharp turns, accelerating at rapid speeds, or braking harshly, it is up to fleet managers to correct these patterns. Real-time feedback mechanisms integrated into AI-enabled systems provide drivers with insights into their driving behavior. These systems collect data on driving habits such as acceleration, braking, and speed. Drivers receive immediate notifications and feedback regarding their performance, allowing them to make instant adjustments. This promotes safer driving practices, enhances fuel efficiency, and reduces vehicle wear and tear.

Over time, fleet management systems that use AI can be used to assess overall performance. It takes into account important metrics like compliance with speed limits, following of traffic and road safety rules, and implementing fuel-efficient driving. Thus, managers are able to identify those who consistently excel, along with drivers who require more coaching.

Safety of drivers

Safety of drivers is very important in fleet management. Vehicles can be equipped with sensors and cameras, so fleet managers can track factors such as speed, braking patterns, and adherence to traffic rules. It will help in reducing accidents, by allowing prompt intervention via alerts in case of reckless driving.

AI-powered telematics devices, such as dash cams and speed sensors, can automatically record, detect, and send alerts of unsafe driving behaviors such as speeding, harsh braking, and distracted driving. Furthermore, they can also send real-time in-vehicle audio prompts to drivers to help them make safer driving decisions.

Dash cams are valuable for monitoring driver behavior and protecting drivers against false incident claims too. But then again, reviewing hours of dash cam footage is a time-consuming job. AI-powered dash cam software can help by automatically flagging and categorizing footage relevant to unsafe driving behavior. You can quickly review the driver’s performance and provide targeted coaching to them. It allows development of customized training modules by identifying key areas where drivers need to improve and upskill.

Moreover, simplified footage review makes it easier to locate and share crucial clips with the police or your insurance provider in the event of an incident. This can expedite the claims process and improve accuracy when determining fault or liability.

What does the future look like?

Vehicles that utilize AI for fleet management are looking at reduced operational costs, lesser driver retention problems, predicting routes based on road conditions, and so on. Stakeholders can benefit from the reliability and efficiency of this technology due to the reduction in accidents, costs, driver turnover, and other problems that may reflect on fleet service pricing. AI not only guarantees driver safety, but also the safety of pedestrians and other commuters on the road.  The technology continues to become more sophisticated, so exciting developments can be expected in the future. For instance, AI can be used to improve vehicle-to-vehicle communication, so they can coordinate with each other in real-time to avoid accidents and traffic congestion.

Needless to say, AI is swiftly transforming the fleet management industry – its ability to analyze humongous amounts of information from telematics devices, make it possible to manage operations more smoothly.  The more data AI takes in, the better it gets at making predictions. That means more accurate routes, better vehicle diagnosis, and hopefully, safer and more intuitive automated vehicles that require minimal driver and fleet management efforts. Be it location tracking, monitoring safety of drivers, or vehicle health reports, Anstel’s AI-powered solutions make use of valuable sensor data, to allow fleet managers to make smart decisions for streamlining operations.