No driver required! The future of autonomous trucks

Volvo Group recently unveiled a self-driving refuse truck that learns where to pick up bins in a neighbourhood after just one session of been ‘trained’ by a manual driver.

In Singapore, meanwhile, convoys of driverless trucks carry freight between terminals at the city’s bustling shipping port, while, in Germany, truck-maker MAN and operator DB Schenker plan to test two-truck platooning with HGV drivers behind the wheel – rather than testers – on the A9 motorway between the company’s Munich and Nuremberg depots by Spring 2018. Likewise, Daimler’s driverless ‘Future Truck 2025’ has already travelled its first journey on a public highway.

Although these real-world examples do not yet match the promise of fully self-driving trucks, they are a genuine sign that automated driving technology has advanced to the point to which the vision of self-driving trucks on the world’s roads is nearing reality.

Analysts at Ronald Berger expect autonomous trucks to hit the road sometime before 2025. Although that sounds far off, it is just 8 years from now.

Technical vs. legal

In fact, it is not technology that’s likely to inhibit the reality of automated trucks – although there is some way to go – rather it is the legal framework and the supply chain that needs to evolve and catch up before the promise can be fully realized. Overcoming these hurdles, however, will certainly be worth the effort.

Despite the myriad challenges, autonomous trucks offer significant benefits, including fewer traffic-related deaths and injuries, significantly lowered costs, reduced emissions and less traffic congestion.

It’s estimated that over 90% of all vehicle accidents are caused by human error, so automated vehicles promise to cut this human cost dramatically. According to Roland Berger, in Europe alone, 26,000 people died in 2013 in road accidents, with another four victims suffering permanently disabling injuries for every death. The situation is even worse in emerging markets, with the number of motor accident-related deaths and injuries expected to double between now and 2030.

Safety first

Existing systems, such as adaptive cruise control (ACC), have been estimated to reduce truck-related rear-end collisions – the most common type of truck-related accident today – by over 70%. As a result, the European Commission has mandated that from 2015 onward all newly registered trucks must be equipped with lane departure warning systems (LDWS) and from 2018 onward with advanced emergency braking systems (AEBS). However, as autonomous technologies evolve further, this figure should drop further still.

Autonomous trucks also offer the promise of significant cost savings to the industry. Advanced driver assistance systems (ADAS), for example, reduce the total cost of ownership (TCO) of trucks by cutting the two largest cost factors: fuel and driver costs. ACC already enables fuel savings but, in future, ADAS, combined with advances in vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communications, will greatly increase the potential for further savings.

By reducing acceleration and deceleration, and the ‘concertina’ effect, such technologies should smooth out traffic flow, not only significantly cutting fuel costs, but also reducing emissions and congestion, particularly in urban areas.

It’s not technology that’s likely to inhibit the reality of automated trucks – although there is some way to go – rather it is the legal framework and the supply chain that needs to evolve and catch up before the promise can be fully realized.

Continental, for example, has developed Static eHorizon, which by using data from the vehicle’s sensors can adjust the engine train, and suggest gear-changing shifts, according to the terrain. Used in Scania trucks, it has been shown to deliver 3% fuel savings, which may not sound significant, but across the Scania fleet that equates to 90 million litres of fuel saved. Continental is now developing a dynamic version of eHorizon, which should deliver even more significant fuel savings.


Another technology, platooning – whereby a number of vehicles are ‘coupled’ electronically together to drive in very close proximity – has been shown to reduce the fuel consumption of the lead truck by 8% and that of the following trucks by 14% when traveling at 85 km/h.

Of course, autonomous trucks can also dramatically reduce, and even eliminate, the second-largest cost factor for operators; the driver. Fully autonomous vehicles, in which the driver does not need to be present, are a long way off, however, Level 3 functions (see box) could allow drivers to relax or perform administration work as the vehicle controls speed, braking, lane changing, and so on, in ‘simple’ driving conditions, such as on motorways.

There are 5 levels that have been described by the NHTSA and are becoming universally adopted to describe the sophistication of autonomous vehicles:

  • Level 0 – No autonomy: All steering, acceleration, braking, and controls are controlled by the driver (includes auto lights and wipers etc).
  • Level 1 – Function-specific autonomy: Covers ACC, self-parking, emergency brake assist, stability control, and so on. Still requires the driver to be present and in full control of the vehicle.
  • Level 2 – Combined function autonomy: Technology can take control of the vehicle in specific situations, but the driver is still expected to be ready to take back control at any time.
  • Level 3 – Limited self-driving autonomy: The vehicle can control most driving duties, including lane changing and steering, but the driver will still need to take control in certain situations. Cannot negotiate hazards such as pedestrian behaviour, so best on motorways.
  • Level 4 – Full self-driving autonomy: Vehicle performs all driving functions and monitoring for an entire trip. Driver does not need to present.

The technology is relatively mature, but work is still needed. Connectivity technologies, such as Wi-Fi, 4G, LTE, and soon-to-arrive 5G, are maturing to ensure V2V and V2I communications that are essential for connected/autonomous driving. Platooning has already been tested, but to get to production-ready levels, fail-safe connectivity will be required.

Meanwhile, in-vehicle processors will be able to handle many autonomous driving functions. To achieve higher levels of autonomous driving, data will almost certainly need to be processed in the cloud. Higher functions such as sensor data fusion, spatial recognition, trajectory planning, and control and decision making will require 300GB of data per hour to be processed through a centralized architecture – today that falls some way short of the requirements for full autonomy.

Advanced technology

The hardware is relatively advanced. There are already vehicles in production that incorporate smart sensors (in-vehicle), short- and long-distance radar, LiDAR (which works on the principle of radar, but uses light) and cameras that collect, monitor and upload real-time data regarding the vehicle’s environment, road conditions, driver behaviour, hazards, and so on.

Likewise, companies such as Google, HERE (owned by the consortium of Daimler, BMW and Audi, as well as investors from China and from Intel), and TomTom already own sophisticated HD, real-time, 3D mapping platforms that can collect, aggregate and update road data instantly to warn the vehicle of incidents and traffic congestion, and ultimately enable fully automated driving.

Such technology is already appearing in production models – BMW, for example, expects to include HERE’s location platform technology in some of its cars from 2018, while the recently launched Audi A8 already incorporates HERE mapping technology.

Software innovation

However, in order to process the vast amount of data collected by the vehicle’s sensors, significant innovation on the software side is required before self-driving vehicles can become a reality.

Early-stage ADAS functions require the processing of sensor data and the ability to override driver control, but moving up the functionality stack requires even more advanced software – essentially the realm of artificial intelligence (AI).

For example, combined function automation needs to further understand the immediate environment of the vehicle and the exact location of the vehicle within that environment (the traffic) – known as ‘static’ spatial recognition.

Limited self-driving automation is even more complex, requiring the ability to predict and anticipate the behaviour of other vehicles, pedestrians, animals, and so on, while simultaneously taking into account the movement of the vehicle – known as ‘dynamic’.

While AI has seen significant advances, and investment, in recent years, it is still some way off these capabilities. Furthermore, it will need to meet stringent safety requirements, be free from errors, and ensure that the vehicle always defaults to the ‘safest option’ in the event of an incident.

Inhibitors to autonomous trucks

Aside from technology, one of the largest inhibitors to autonomous vehicles is the requirement for a new legal (and insurance) framework. Today, autonomous driving is prohibited by law. Key questions to be addressed by a revised legal framework are liability (OEMs, suppliers, drivers), ethical concerns, and criteria that can be used to determine if the vehicle meets required safety standards.

This will require OEMs, suppliers, and governments to work closely together, and may as a result lag behind technological advances.

Furthermore, in order to meet both technical and legal/ethical requirements, the entire industry supply chain will need to evolve. Platooning, for example, will require fast communication between other vehicles and infrastructure, which in turn will need much closer co-operation between OEMs, Tier 1 suppliers and government.

If the promise of automated trucks is to be realized, it will certainly require action from both OEMs and suppliers. Analysts expect specialists to dominate specific ‘functional clusters’ that require specific competencies. For OEMs the focus needs to be on developing the technology further to enable limited/full self-driving automation.

For suppliers, meanwhile, the focus needs to be on both the technology and the business model to build effective business models for providing OEMs with both complete systems and ADAS components.

Certainly, it won’t be long before we see convoys of trucks platooning their way along the lanes of our motorways.

Gary Eastwood, Technology Copywriter 

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