Driving down the AI highway - Motive pitches platform upgrades at the trucking sector

While software vendors are all shouting loudly about having ‘gen AI-ed’ their products, it is interesting to see some applications of AI being used to provide genuine user advantages that can be quantified in terms of both bottom line and impact on real lives.

At the same time it demonstrates some AI modelling developments that can be seen to have real potential in market sectors well outside of the core marketplace for which the technology was developed. In addition, it is possible to see it as a significant example of edge computing in action, where the whole of the USA is the current reach of the network - but the whole world is the goal.

AI is, without doubt, the hot topic du jour. The range of applications varies widely, from the stunning bio-science discoveries now appearing almost daily. Coming across not one but a whole suite of related applications, matched to a platform to bring them altogether, that aims to solve many of the operational problems of a major industry is a fascinating alternative.

That suite comes from San Francisco-based Motive, a manufacturer and developer of the hardware and software underpinning that major industry  - trucking. Getting everything from food to fripperies moved efficiently, cost-effectively, reliably and, most important of all, safely from the point of production to the point of consumption, touches every part of everyone’s life. It is widely said that everything anyone has ever bought has spent some of its life in the back of a truck, and if the vehicle has seats, that also includes us as bus passengers travelling to work, school or shops, right through to rock and roll stars travelling the country `on the road’ in surprising levels of luxury and protection.

Doing any of these safely and reliably is key to the running of countries, cultures and communities, and given the inevitable complexities of the process, one fraught with dangers and inhibiting problems. Showing ways in which they can be managed and resolved, led Motive to host its first corporate convention last week in Nashville, a city that is a major trucking hub, situated as it is on the major i-40 east/west interstate highway across the USA, as well as being the proud home of trucking’s permanent soundtrack, Country and Western music.

CEO Shoaib Makani acknowledged, at the start of his keynote presentation, that the counter to trucking’s importance to the economies of the world is its potential for damage to its people and communities.

Our roads are more dangerous than ever. There is an epidemic of unsafe and distracted driving, and it has consequences. There were almost 50,000 road fatalities in North America last year, and also 5,500 worksite deaths, and unfortunately, the legacy technology in this industry has not helped to overcome these challenges. Fleets have been forced to use a patchwork of disconnected software tools to manage their operations, with each one of your teams using a different point solution.

That fragmented approach results in data silos, and it actually prevents you from taking advantage of the advances in AI to automate operations. The end result is greater technical and organisational complexity, which ultimately translates into higher operating costs and reduced productivity. Getting your people working on the same system, with the same set of tools, you can eliminate manual work and perform way better as a team. And importantly, you can leverage AI to automate major workflows in your operations.

Standing at the platform

The key development the company has come up with this year is a platform that links together the growing suite of what would otherwise be a growing collection of point solutions. This creates what does seem to be a good example of how AI, working with shared data across a range of such solutions, can build a capability that is potentially greater than the sum of its parts. The range and scope of those parts are, however, wide and comprehensive.  

They also provide some sound, practical examples of AI at work. Some will argue that, with the advent of generative AI, what Motive is offering is no longer AI. But is its certainly Augmented Intelligence and Machine Learning taken to a high level. 

Motive properly started down this road a couple of years ago, with one of its first targets being road safety, including activities inside the cab. In 2023 it released a number of new AI models to detect a wide range of behaviors by drivers, including unsafe interpretation of road signs. The best example in the USA is the Stop Sign, not least because it is also widely used in many other guises and applications, such as billboard adverts and tee-shirt artwork. For the driver, deciding whether it is or isn’t a Stop sign can be a problem. 

So the high grade camera the company has developed - which can be used in multiple locations on the vehicle – feeds an AI system trained to differentiate between real signs and those many other applications of ‘fake’ ones. The system can then warn the driver accordingly. This not only makes them a safer, less violation-prone driver, but also less likely to be distracted by reactions such as frustration. 

With both external cameras and those inside the cab, observing the driver, it becomes possible for fleet managers, and fleet safety officers in particular, to observe drivers in action and build personalized training programs for them. But when accidents then happen, these same tools can be used to provide valuable evidence of what happened and why. 

That evidence then has significant additional value. For example, the size of the USA means that accidents commonly occur in remote locations where first response time is important. The Motive platform can pull together information – including videos - about location, position/condition of the vehicle, condition of the load and full details of driver condition, and transmit it all directly to the relevant services. That same data is also sent to the fleet management so they can have accurate records and follow up as necessary. This can include post-event analysis of all relevant information about the vehicle, the road, the driver, and any third-party activities.

This is important. Fifty-four percent of fatal crashes that involve large trucks are in rural areas and it frequently takes up to 90 minutes for first responders to arrive. Fatalities can be reduced by 13% for every minute saved in first responders arriving at the scene.

According to Deborah Smith, Senior Product Manager at Motive, the company is now working on seven different AI models in this one application area. Each has its own level of complexity and use case, including a driver fatigue model, a Forward Collision Warning model, an unsafe parking model, and a safe distance detection model.

Makani claims that Motive is the only suite management platform with embedded tools designed to cope with the scale of the trucking and heavy equipment marketplace: 

This is really hard to do, even for one driver, let alone trying to do that for thousands of drivers. Across Europe, that's just not possible to do it at scale. That is where bringing all of that data into one single platform, using AI to find these patterns, enables us to do this at scale across the USA.

Spend, spend, spend - carefully

Perhaps the most significant tool integrated into the platform was launched at the conference. This is a full Spend Management system that fits together with the Motive credit card service launched last year. The goal is to provide fleet finance teams with full 360-degree visibility of all spending, some of which is currently at the discretion of individual drivers. 

The most important, and expensive, choice is where to refuel. Fleet managers would obviously like drivers to choose sources with the best prices. But other factors can get in the way, such as a driver’s personal preferences based on other services (types of food available or free cups of coffee, for example). Saving even a few cents per gallon can result in significant savings at fleet level.

Using GPS and other vehicle status logging tools, managers can know when a truck needs refuelling, the location of the nearest source, and the cost/gallon at that source. The driver can therefore be directly advised, in real time, on the choice of fuel source should it be considered necessary. In addition, it gives the fleet managers the opportunity to set up preferential supply arrangements that their drivers can exploit.  

The card will normally be held directly connected to the system so should a driver decide to continue using a more expensive provider, the fleet managers can go so far as to instruct the card to decline to make any payment. Using the card also helps to reduce fraud, particularly on fuel sales where fuel is purchased, but for another vehicle. 

My take

One other new tool that has been enabled by the arrival of the platform is known as Mistakes, which piggy-backs off the other existing tools to collect together insights into every driver’s driving practices and the mistakes and quirks of their driving behavior. The objective is to help drivers improve their driving, which in turn usually results in changes that contribute to lower operating costs, and more reliable operations.

With some fleets spending more than $1 million a month on operating costs, making a wide range of small cuts in costs can have a significant impact on the bottom line, and a development like the Motive platform allows AI capabilities to be used not only vertically, in each individual tool, but also horizontally across any and all of them.