Trucking was traditionally considered a low-tech industry. However, recent events have shown that the sector is way more technophilic than previously thought. From route planning applications for mapping out secure roads to artificial intelligence (AI) software for predictive maintenance, here are the latest technological innovations driving the trucking industry. 1. Self-Driving Trucks Driverless automobiles date back to the 1980s. But if you read many trucker news, you’ll realize that the concept of autonomous trucks only caught on recently. Like other self-driving cars, driverless trucks are controlled by computer programs that utilize advanced machine learning (ML) algorithms. The complex algorithms work in conjunction with cameras and electronic sensors installed in different parts of the vehicle to generate maps of their surroundings in real-time. While initially attributed to legacy automakers like Mercedes-Benz, driverless cars have since piqued the interest of more automobile companies. Tesla, Daimler, and Volkswagen have all been keen to cash in on this growing market segment. 2. Electric Trucks If you floated the idea of electric trucks about half a century ago, many would probably dismiss your suggestions as unrealistic and unattainable. But like self-driving trucks, electric trucks are now a stark reality. In the recent past, renowned automobile companies like Tesla and Rivian have dared to disrupt the trucking industry by releasing electric-propelled trucks. Electric trucks operate on rechargeable batteries. As such, they do not emit toxic fumes to the environment. Besides, electric trucks are more fuel-efficient since they don’t run on gas or diesel. The lack of complex engine systems also makes these vehicles easier to drive and maintain than their gas-powered counterparts. 3. Green Trucking Switching to electric trucks isn’t the only way to attain net zero emissions. The past few years have witnessed an emergence of other eco-friendly practices in the trucking industry. One such trend is the gravitation towards alternative fuels like propane and natural gas. Trucking companies like Heavy Duty Trucking (HDT) already use renewable natural gas in their fleets, signaling a shift from traditional diesel fuels. The F1T by Japanese startup Folofly is another classic example of an energy-efficient truck. We’ve also seen a surge in the demand for hybrid trucks, which operate on both renewable and non-renewable fuels. The idea is to significantly cut back (if not entirely eliminate) greenhouse gas emissions. 4. Intelligent Route Mapping With AI Planning trucking routes the traditional way is tedious, costly, and inaccurate. Changing weather patterns and unpredictable traffic conditions can make it difficult to pinpoint what lies on the road ahead. That’s where artificial intelligence (AI) comes in. With AI-powered route planning software, fleet managers can get real-time insights into traffic data and weather conditions. These tools use advanced algorithms to analyze current and historical data, thereby pointing truckers to the most efficient routes. AI route planners can reduce travel times and ensure timely deliveries, enhancing customer satisfaction. 5. Predictive Maintenance with AI and ML Frequent vehicular breakdowns can cause massive service disruptions for trucking companies and lead to unprecedented shipment delays. While you may not entirely eliminate road incidents, you can minimize their occurrence by investing in predictive maintenance. The emergence of AI-powered predictive maintenance tools has proven to be a game-changer for trucking companies seeking to optimize their efficiency. These programs use AI and ML to monitor a vehicle’s health by tracking critical parameters like engine performance, fluid levels, and tire condition. They then notify the maintenance technicians of anomalous patterns, allowing them to schedule repairs before the issues escalate to significant breakdowns. Volvo is a renowned automobile company that uses AI-driven predictive maintenance to monitor their trucks’ mechanical health. Thanks to this technology, trucking companies can prolong their trucks’ lifespan, avert costly downtimes, and enhance operational efficiency. 6. Big Data and Fuel Efficiency Big data is concerned with managing and analyzing large amounts of data sets. It’s a more reliable option than traditional data processing methods, which explains its popularity in the trucking industry. One way trucking companies utilize big data is by enhancing fuel efficiency. Truck drivers can utilize big data to predict expected fuel consumption based on factors like load weight, road conditions, and engine performance. They can then implement strategies to minimize fuel wastage. A classic deployment of big data in logistics is evidenced in FedEx, which uses its SenseAware platform to analyze various metrics from its shipments in real-time, such as temperature and humidity. 7. IoT and Inventory Management The Internet of Things (IoT) is another tech innovation that has recently found its place in the trucking industry. Fleet managers utilize the Internet of Things, AI, and ML for robust route planning and predictive maintenance. IoT also drives GPS and telematics devices for real-time insights into a truck’s location. However, perhaps the biggest application of IoT in the trucking industry pertains to inventory management. Logistics companies rely on this technology to automate data collection, improving the accuracy of current inventory data. Using IoT-based technologies like Radio-Frequency Identification (RFID) devices, dispatchers can pinpoint the location of each inventory and determine when it’s time to restock. The Bottom Line With so many technologies driving the trucking industry, now is the time to revolutionize your business from a struggling venture to a profitable one. All the above innovations can minimize overheads, enhance operational efficiency, and accelerate growth for your trucking company. Just remember to integrate them carefully into your system, as that will ensure you maintain fleet uptime during the adoption process.