Automation in the road goods transport sector
The very act of driving a truck places enormous demands on motor and cognitive skills. The sheer weight of the vehicle and, possibly, the load mean that truck drivers need to drive such that they are always aware of the traffic situation far ahead of them because, say, an emergency braking process takes much longer. In addition to a working knowledge of the relevant traffic regulations, professional drivers also need special cognitive skills such as a high level of attention, the ability to process information quickly, a good sense of direction and the ability to see things from different perspectives. So truck drivers need to see things from the perspective of other road users so that they can anticipate potential hazards. Assistance systems can provide drivers with all the support they need here.
In particular, trucks equipped with automation technology are expected to penetrate the market faster and in higher volumes than other vehicle types equipped with automation technology. There are a number of reasons for this including that legislature specifies the mandatory introduction of safety-relevant assistance systems when a vehicle is first registered; systems include the anti-blocking system (1991), the electronic stability program (2014) and emergency brake assist (2015). The estimated market penetration of truck assistance systems is shown in the Table below. With 2.85 percent annually, the rate of introduction of ACC systems is slightly above that for ABS (2.5 percent).
When it comes to the performance requirements of drivers of (highly) automated vehicles, the test for assessing driver alertness should play a central role in the future. Continuous system monitoring, which is necessary when automated systems are used, demands special skills to sustain attention – a form of alertness, also referred to as “vigilance.” Vigilance, therefore, also needs to be tested, especially among drivers using partially and highly automated support systems in a vehicle.
The ability of a driver to shift their attention from one stimulus to another (“shift of attention”) is also important. In this context, the “working memory” – which has so far not played any role in the assessment of a person’s ability to drive – has taken on a particular significance. According to Baddeley (2012), the working memory consists of four components:
1. the central executive, which undertakes control, organization and monitoring tasks
2. the phonological loop, which processes acoustic and verbal information
3. the visuospatial sketchpad, which is responsible for processing visual information
4. the episodic buffer, which establishes a connection to the semantic and episodic knowledge of the long-term memory
2. the phonological loop, which processes acoustic and verbal information
3. the visuospatial sketchpad, which is responsible for processing visual information
4. the episodic buffer, which establishes a connection to the semantic and episodic knowledge of the long-term memory
The role of the working memory is to store information for a short period of time and simultaneously manipulate it. The latter differs from the short-term memory, which is used only for storing information. The processes performed by the aforementioned working memory play a role in the executive functions, such as logical thinking, problem- solving and the planning of actions. In view of the higher rates of automation in the goods transportation sector in particular, the definition of basic (cognitive) requirements for truck drivers and, if applicable, the dimensions to be tested need to be optimized.
It can be anticipated that an increasing number of driving sub-tasks will shift from the driver to the in-vehicle technology. Attempts are already being made in the goods transport sector to transition from partially automated driving – i.e. the use of driver assistance systems – to highly automated driving, which enables drivers to effectively relinquish control of the vehicle, at least in certain situations such as driving in convoy on a highway or rural road. Corresponding research projects have already been successfully completed or are ongoing.
Automation in vehicles can cause safety issues
But as in-vehicle automation technology becomes more common, the role of the driver is shifting from that of an active operator to a passive supervisor. This shift in roles places new demands on drivers. A passive supervisor rule reduces one’s level of alertness and activity, which in turn can cause safety problems. Drivers can become over-reliant on the in-vehicle technical assistance systems, even if they have been expressly advised that, despite the ongoing technological refinement of these systems, they should not expect their vehicle to master all potential scenarios in active traffic situations in the foreseeable future. It is then very difficult to take over control of the vehicle in the event of an emergency, also known as the “out of the loop” problem. This describes the state in which drivers are in when they are not required to steer the vehicle.
But drivers who can temporarily “switch off” must be able to reliably assume certain driving tasks should the assistance systems be stretched to their limits (i.e. in highly complex situations). The driver must therefore be brought back “into the loop” by the vehicle. But it takes a certain amount of time for drivers to properly understand the situation so that they can retake control of the vehicle without making any errors. A report compiled by the German Insurance Association in 2016 addresses this issue of switching roles. In this report, a review of various studies into the amount of time required for the switchover from (highly) automated driving to manual control shows that anywhere between 2 to 20 seconds can elapse until drivers are in a position to perform their task. However – and as the authors of the report expressly emphasize – the studies are comparable only to a very limited extent due to the varying test conditions.
Furthermore, in the long term, vehicle automation will result in drivers either forgetting the skills they have acquired or not even acquiring these skills in the first place. This effect becomes particularly pronounced if a driver has to control a vehicle manually because, for example, an automated function fails or if a driver hires a vehicle equipped with only limited automation technology. These are critical or demanding situations in which the driver would have to fall back on patterns of behavior based on little training. The associated decrease in active driving practice means that drivers in the future will have fewer driving- related skills to draw on than drivers today who possess at least a certain level of expertise.
The lesson is clear: Driving (highly) automated vehicles does in principle have the potential to prevent accidents, but the users of these systems must meet certain requirements especially regarding cognitive performance, which today is not tested. In addition, the regular use of “autopilot” functions in vehicles, for example, could mean that drivers risk losing their “standard” driving skills. The time required for drivers to retake control of their vehicle also needs to be considered.