No one knows for certain what heavy duty commercial vehicles will look like in 40 years, or even 20 years for that matter. There is no magic portal that allows a glimpse into the future to find out what technologies will be available. We can, however, make predictions based on what we know about the present.
A review of technologies available on today’s commercial vehicles can give us a good idea of the direction in which the industry is headed. Features such as advanced driver assistance systems (ADAS) may eventually lead to fully autonomous vehicles. Likewise, telematics, artificial intelligence (AI), and machine learning (ML) will likely lead to prescriptive maintenance practices that allow fleets to service parts and components before they fail and adjust operations to extend the life of a vehicle.
An autonomous commercial truck that prescribes its own maintenance sounds like a promising tomorrow, but there are several developments that need to take place before the industry can reach that point.
ADAS today, autonomy tomorrow
The Society of Automotive Engineering (SAE) and the National Highway Traffic Safety Administration (NHTSA) outline five levels of automation; Level 0 being a vehicle with no automation or driver assist systems and Level 5 being a vehicle that can fully drive itself anywhere in any conditions with no driver necessary. Many trucks on the road today offer driver assistance systems allowing for Level 1 autonomy, with some OEMs starting to reach Level 2. Levels 1 and 2 provide passive warnings and temporary active driver assistance, but the driver must remain in control of the vehicle at all times, even when these systems are engaged.
Levels 1 and 2
Current active driver assistance systems available on commercial vehicles include features such as adaptive cruise control (ACC), automatic emergency braking (AEB), lane keep assist, and automatic windshield wipers and headlights (both on/off and high beam functionalities). This is in addition to numerous passive systems like lane departure warning, blind spot monitoring, and tire pressure monitoring.
In the coming years, truck OEMs will look to solidify Level 2 automation in vehicles. Many who have yet to reach this level will roll out features such as lane keep assist and ACC, and those already at Level 2 will enhance features to be more helpful to the driver and offer earlier and more accurate warnings and adjustments.
ZF is one provider of safety technologies for heavy duty commercial vehicles. Dan Williams, director, ADAS & autonomy at ZF, says the company currently offers an electronic adaptive steering system called ReAX that works in conjunction with the truck’s hydraulic steering system. As part of the ReAX system, Williams says ZF will launch a lane keep assist system called OnTraX in North America this year.
“OnTraX offers further capabilities with the addition of short-range radar, including lane change and city drive assist,” Williams says. “The side-mounted short-range radar can see in the blind spot where the driver cannot. When integrated with ReAX … the system can be programmed to deliver a haptic warning to the driver if they are approaching an obstacle or vehicle in a blind spot. The system can also be programmed to urge the driver away from the obstacle.”
Williams adds that ZF’s acquisition of WABCO, a provider of electronic braking, stability, suspension, and transmission automation systems for heavy duty commercial vehicles, will allow the company to combine longitudinal and lateral control.
TJ Thomas is the director of marketing and customer solutions - controls at Bendix Commercial Vehicle Systems, a company that designs, develops, and supplies active safety technologies for heavy duty commercial vehicles. Thomas says Bendix currently offers active cruise control with braking and enhanced collision mitigation as well as multiple passive monitors, warnings, and alerts through the company’s Wingman Fusion system. He adds that more active systems are coming soon.
“[We will] soon be releasing an active steering system that will interface with Wingman Fusion to provide lane keep assist, active return, and a few other features,” Thomas says.
Volvo Trucks North America (VTNA) offers ACC and AEB based on the Bendix Wingman system as standard features on their Class 8 trucks. Ashley Murickan, product marketing manager, VTNA, outlines some of the features currently offered.
“Current Volvo Trucks ADAS systems provide automation ... assistance to the driver in completing their driving tasks,” Murickan says. “For example: lane change support [and] blind spot detection, lane departure warning, adaptive cruise control, automatic emergency braking, and dynamic steering.”
Daimler Trucks North America (DTNA) currently offers full Level 2 automation in some of the company’s Class 8 trucks, in addition to multiple passive alerts and warnings.
“The Detroit Assurance 5.0 suite of safety systems is currently available on the Freightliner Cascadia as well as the Western Star 49X truck,” says Len Copeland, product marketing manager, Detroit Products, DTNA. “Detroit Assurance’s Active Lane Assist (ALA) technology provides temporary automated steering and acceleration/deceleration.”
Levels 3, 4, and 5
In a vehicle operating at Level 3 automation, the driver does not need to be in control of the vehicle at all times but must be able to take over operation should the vehicle request it by providing an alert.
Level 4 automation will be achieved when the vehicle can operate itself completely with no driver input required as long as certain parameters are met. This means the vehicle may only be able to operate without a driver on previously mapped roadways or only in certain weather conditions. Level 5 is the same as Level 4 but without any restrictions; a 100 percent driverless vehicle.
When the industry will reach these levels of automation is anyone’s guess, but progress is being made toward that end.
“Two key trends driving the industry are highly automated driving and electrification,” Thomas says. “Bendix will continue to evolve its suite of brake and ADAS systems to support these trends. For example, EBS (electronic braking systems) will offer features desirable to both trends, such as smoother and more balanced braking.”
Thomas and Williams both state that the evolution of various cameras and sensors will play a major role on the road to vehicle autonomy, as will data processing power.
“Sensors with greater range and environmental sensing capabilities can be paired with increasingly more powerful electronic control processing units, like ZF’s ProAI,” Williams says. “Higher processing power will enable higher levels of system redundancy to help ensure they work in all conditions, including piloted or automated modes. When these are combined with electronically-controlled chassis systems, they help set the stage for the next generation of mobility.”
Lidar is another technology that will come into play, Williams notes. It combines some of the advantages of both camera and radar, and has some additional capabilities that neither of those technologies have.
“Since higher levels of automation will demand both increases in sensing capability as well as redundancy, lidar is very appealing moving forward,” he says.
Williams adds that ZF has teamed up with self-driving truck company TuSimple to co-develop sensors needed in autonomous vehicle technologies, such as cameras, lidar, radar, and a central computer. ZF’s role in the partnership will be to contribute engineering support to validate and integrate TuSimple’s autonomous system into the vehicle.
As the commercial vehicle industry eventually reaches higher levels of automation, it is likely that vehicles performing simpler tasks will be the first to become driverless, with more complex operations coming later on.
“We believe the first automated vehicles will appear in duty cycles that are relatively easy to navigate, such as hauling from a mine pit to a railhead on a remote road, or maintaining a lane on a limited access highway, such as platooning,” Williams says.
Maintenance: preventive, predictive, prescriptive
Fleet maintenance programs have traditionally been reactive and preventive. Parts and components on vehicles are serviced regularly to increase their longevity, and they are replaced as they fail or come close to failing.
That is beginning to change, however, as telematics become more commonplace on trucks. While telematics has existed in the heavy duty commercial vehicle industry for some time, fleets are now beginning to use it to turn their preventive maintenance programs into predictive maintenance.
Sensors on the truck monitor different parts and components, and alerts are sent to the fleet via mobile networks or satellites. The fleet can then use this information to determine future maintenance for the vehicle.
“The use of telematics to monitor vehicle conditions in real-time allows fleet managers to tailor the formerly rigid maintenance-by-checklist procedures in favor of a more needs-focused maintenance schedule,” says Nicola Zingraf Bolton, digital connected services leader, North America, commercial vehicle control systems, ZF. “Combining fault code alerts and tracking information from telematics with operations information on scheduled transports allow fleets to plan ahead and can minimize time spent in the shop.”
Zingraf Bolton explains that while fleet managers were once dependent on the driver’s input to report issues while on the road, telematics can provide a more accurate decision base to prioritize and schedule maintenance before a non-urgent event becomes critical.
The use of predictive maintenance can help fleets reduce total cost of ownership (TCO), maximize uptime, and minimize avoidable breakdowns, she adds.
As the use of telematics increases and more data is collected, predictive maintenance will only become more accurate and reliable in the coming years.
“As the growth of the data expands, even more clarity will enable a fleet to understand real concerns at more defined intervals,” says Thomas L. Kotenko, general manager, Snap-on – NEXIQ Technologies. “Preventive maintenance at a specific mileage interval can then become more of a predictive, component replacement interval. This will enable the fleet to determine components requiring replacement at a determined preventive maintenance point and ensure that the vehicle remains on the road.”
Evandro Silva, senior manager connected innovation, Volvo Trucks North America, says Volvo currently uses predictive maintenance practices by way of the company’s Dynamic Maintenance System.
DTNA also incorporates telematics and predictive maintenance, Copeland confirms, adding that the OEM is developing new predictive models for components and connecting those models to warranty data to further improve uptime.
The prescriptive future
As predictive maintenance begins to ramp up today, the process can be improved in the future with a move to prescriptive maintenance.
Prescriptive maintenance uses AI and ML to take historic service and uptime information for each individual vehicle into account, and to recognize transport type patterns, ZF’s Zingraf Bolton explains. This allows fleets to proactively service each vehicle at the proper intervals, maximizing uptime and reducing the number of times a vehicle needs to be pulled out of operation.
“Prescriptive maintenance has all the characteristics and features of predictive maintenance, but it goes one step beyond predictive,” Volvo’s Silva adds. “Prescriptive maintenance provides what type of [maintenance] and when maintenance needs to be performed, but also prescribes the necessary changes on the truck operation that will extend the time between maintenance events, maximizing the useful life of the vehicle.”
This will be especially helpful and absolutely necessary when the industry reaches the upper levels of vehicle autonomy. If there is no driver onboard to monitor vehicle systems, parts, and components, the fleet will need to know when to service the vehicle, and the vehicle will need to communicate its status consistently.
“A fully autonomous fleet benefits from prescriptive maintenance through sheer sharing of data,” Kotenko says. “The autonomous fleet of the future will share a constant flow of data with the prescriptive maintenance solution. This flow of data can provide a fleet manager with analytical knowledge and decision-making benefits.”
Safety system sensors
Safety systems rely on various sensors to provide the raw data needed to calculate risks, alert the driver of an impending event, and – in the case of active systems – take action if the driver does not.
- Ultrasonic sensors – These sensors send out audio waves at a specific frequency and wait for the waves to bounce back to determine how far a vehicle is away from another object. These are most commonly used in forward and reverse proximity sensors.
- Radar sensors – Radar sends out electromagnetic waves (rather than the audio waves used by ultrasonic sensors) to determine how far an object is away and how quickly it is approaching. Radar sensors are used in some blind spot detection and forward collision detection and mitigation applications.
- Lidar (Light detection and ranging) - A more advanced form of radar, lidar scans the environment using a non-harmful invisible laser beam to provide a three-dimensional view of the surrounding area. When combined with camera data, lidar can be used to detect what type of object the vehicle is approaching (vehicle, pedestrian, animal, etc.).
- Cameras – These are used in some forward collision detection and mitigation applications. They are also used for maneuverability at low speeds (forward, rear, and 360-degree cameras), to monitor driver awareness, and to record unexpected incidents.
- Infrared – Infrared cameras create an image using infrared radiation instead of light like a typical camera. These are used to help some vehicles “see” in the dark.
- Machine vision – This type of camera analyzes and interprets images to determine risks. It is used in some lane keep assist, blind spot monitoring, and collision warning/avoidance systems.
- GPS (global positioning satellites) – GPS pinpoints the vehicle’s location and speed by determining distance from global satellites.
- Accelerometer – This sensor measures acceleration and deceleration in a vehicle to determine sudden unexpected maneuvers or collisions.
