BETT - Battery Electric Truck Trial

Deep Dive Analysis 2: Driver Behaviour

The second report looking deeper into the data and performance of the BETT trial vehicles. This report looks at the effects of driver behaviour on energy consumption. Initially, via a data-driven approach deriving insights from vehicle telematics. Secondly, adopting a qualitative approach presenting the training provided during the trial and reviewing available literature on driving behaviour and training in other fleets across the world.

Key Points

  • While there is variation in driving behaviour between BETT vehicles, it is difficult to understand the size of the effect on energy consumption due to other factors, principally payload and weather.

  • The shift to electric vehicles presents an excellent opportunity for new habits to be formed. Strong expectations, training and coaching in eco-driving when drivers start using the new vehicles are likely to improve chances of developing good habits. 

  • Driver behaviour training and interventions that aim to encourage eco-driving have the potential to reduce energy consumption of a BEV. These interventions include training sessions to form initial behaviours, in cab nudges to strengthen a driver’s self-regulation, coaching to encourage habitual driver behaviour and create a positive culture of continuous driver improvement, and rewards and penalties to maintain the positive behaviour change.

  • Effectiveness ultimately depends on the willingness of drivers to change their behaviour. Training interventions that aim to encourage autonomy, competence and readiness are the most effective.

Introduction to driver behaviour and vehicle performance

Driving behaviour is a general term for the style and actions of a driver while they operate a vehicle. In this context we’re interested in the behaviour that affects the energy efficiency of the vehicle, and not in behaviour that affects safety or attitude to other road users, although often they go hand-in-hand.

Driving behaviour can affect the performance and efficiency of a vehicle, which means that through improved driver behaviour from effective training, a vehicle can have reduced emission and greater range.

Data Analysis

This section contains results from the analysis of telemetry data collected as part of the BETT trial to identify variations in driving behaviour.

The most important driver actions that impact performance and efficiency are acceleration and braking. Generally harsher actions will reduce efficiency while gentler actions will improve efficiency and range.

  • Braking more gently shows more anticipation of the read ahead, the driver will have not accelerated unnecessarily before needing to slow down.

  • More gentle braking allows more regenerative braking, harsh braking is more likely to engage the friction brakes.

  • Gentle acceleration demonstrates calmness and anticipation of the road ahead.

Telemetry data recorded from BETT vehicles includes speed, the rate of acceleration and deceleration, accelerator and brake pedal positions, and energy consumption. These can all be used to build a picture of the range of driving behaviour.

To understand the trends across the BETT fleet, individual acceleration and braking events (defined as a continuous change of speed of more than 10 km/h) have been identified and analysed to see how the various markers of driver behaviour vary by vehicle.

This example shows a typical journey segment:

  • Rapid acceleration to 40 km/h followed by slower acceleration to 50 km/h.

  • A short braking event with only light application of the brake pedal followed by small speed increases.

  • A final large braking event to bring the vehicle to a stop.

Behaviour Trends

The following two sections show trends for acceleration and braking events. In each section two vehicles are chosen to represent the “best” and “worst” behaviours and these are compared across several markers of driving behaviour.

To ensure like-for-like comparisons, the data is taken only from events which are on flat road. Only speeds below 50 km/h are considered to avoid skewing the results as some vehicles do relatively little higher speed motorway driving; also the motorway drive cycle has fewer acceleration and braking events so there is less scope for driver behaviour to impact energy consumption.

Each graph is a histogram (rendered as a line for clarity) showing the proportion of events falling into the categories on the horizontal axis.

Behaviour Trends - Acceleration

For acceleration events, vehicle D-2 shows more “aggressive” trends and vehicle J-2 shows more “eco” trends.

Maximum Accelerator Pedal Position

This is the furthest the accelerator pedal is pushed in the entire acceleration event. Higher values indicate more aggressive driving.

Across the fleet only 8% of events reach “full throttle”, but it's over a quarter of events for D-2, with half of events reaching over 70% throttle position.

Conversely J-2 has almost no events above even 90% and the median event is at only 45% throttle.

Mean Accelerator Pedal Position

This is the average position of the pedal across the entire acceleration event. Higher values indicate more aggressive driving.

J-2 shows a much lower position in total with nearly all events having an average position of less than 50%.

For D-2, less than half of events have an average position less than 50%, and notably 5% of events have an average of 100%, meaning the entire acceleration event was at full throttle.

Maximum Accelerator Pedal Rate

This is the fastest the accelerator pedal is moved in each acceleration event, measured in % of total pedal travel per second (i.e. 100 means it would take 1 second to push the pedal from zero to full). Lower numbers indicate more gentle application of the accelerator.

The D-2 driver is very similar to the average, but the eco-driver in J-2 moves the pedal much more slowly during most events, indicating they are exceptionally calm.

Behaviour Trends - Braking

For braking events the trends are a little more subtle, vehicle C-1 shows more “aggressive” trends and vehicle H-1 shows more “eco” trends.

Mean Deceleration Rate

This is the average deceleration rate across the event, higher numbers mean the vehicle is slowing down faster.

C-1 shows a peak slightly higher than the fleet average indicating that they brake more harshly than most vehicles, while H-1 has a peak slightly lower.

Maximum Brake Pedal Position

This is the furthest the brake pedal is pushed in the entire braking event. Higher values indicate more aggressive driving.

The feature to note is that 18% of braking events for H-1 have no brake pedal application whatsoever, the driver is slowing down entirely using regenerative braking.

Vehicle C-1 is close to the fleet average. Overall brake pedal travel is lower than accelerator pedal travel: less than half of events feature pedal travel of more than 15% indicating relatively light brake application across the fleet.

Coast Fraction

This is the amount of speed lost without using the brake pedal. It’s not true coasting as regenerative braking will slow the vehicle down.

The important features are at the edges. On the left side the more aggressive C-1 driver does no coasting at all in 30% of braking events, indicating they are using the brake pedal suddenly and often, this contrasts to only 13% in H-1.

The right hand side shows (like the previous graph) that in 18% of events all the speed is lost without use of the brake pedal for H-1, while this happens in only 5% of events for C-1.

Analysis of the raw data shows that across all events, H-1 loses 36% of speed without touching the brake pedal, while C-1 only loses 9%.

Driver Behaviour and Energy Consumption

While driving behaviour will likely impact energy consumption, and therefore vehicle range, other factors can have a much bigger impact on energy consumption.

The biggest is likely to be the payload which can cause the weight of the empty vehicle to double. Unfortunately this parameter is not measured by the telemetry system so it has not been possible to remove the effects of varying payload from the energy data. As such, it’s not possible to determine how big an impact the variation of driving behaviour seen has on energy consumption and range.

Other factors also cloud the assessment of driver behaviour including weather, which affects energy consumption. Markers of driver behaviour are themselves affected by payload and traffic conditions. It is a challenging task to unpick the intermingled factors from real world driving data.

Driver Training Review

This section contains information on the training provided as part of the BETT project. Thanks to input and insight from the DAF, dealership and fleet trainers, we show how the vehicles were received by the fleets and important things to consider when trying to encourage fuel efficient driving. 

BETT Trial Training

The training in place for the battery electric truck trial vehicles happened in three main stages:

  • DAF provided classroom training

  • A vehicle display and coaching session

  • further training by the dealership driver trainers, who worked with the fleets and drivers when the vehicles arrived.

The aim of the whole programme has been to provide a good solid foundation with opportunities for refresher training. 

DAF Classroom Training

DAF trainers provide classroom sessions for all fleets on the use of the battery electric trucks. During these sessions the drivers are taken through the vehicle, the history and need for electric vehicles. 

  • The session begins by looking at the differences between electric and diesel trucks. This includes the powertrain, how the vehicles are built differently, and the impact of regenerative braking on vehicle efficiency. 

  • Following an introduction to the vehicle, trainers cover daily checks and dos and don’ts on the vehicle.

  • There is a strong emphasis on safety both for the drivers and pedestrians around them. 

  • The resources used include animations, videos and real work photographs. 

  • They finish with a 10-question quiz to ensure all the information was understood. 

Things to consider for classroom based training:

  • Ensure that the materials used are developed for the right audience. 

  • Best results are found when those taking the training are away from their day-to-day job, ideally at a training centre. This allows for full concentration to be given to the session, prevents interruption and demonstrates that the training is important. 

  • Training should be considered for the planning, supervising and driving staff so that:

    • All staff fully understand the vehicle capabilities. 

    • Planning of routes adapts to the different vehicle types (electric vs diesel).

    • The right workplace culture is created, because this is important for success in the trial of new vehicles.

Vehicle Display and Coaching

The second element in the training programme is to take those participating outside to look at the vehicle. 

  • This includes ‘show me, tell me’ run through of different functions and parts of the truck. They emphasize the safety features, such as making sure no one touches or tampers with anything amber/red-labelled.

  • Trainers also take the drivers through charging the vehicle, getting everyone to attempt plugging in and unplugging from the chargepoint. They also encourage them to try unplugging when the vehicle is charging to demonstrate that is it not possible, and they showcase the safety features involved in the charging process.

  • Next, the trainers take drivers out on the road in the truck. The trainer drives the truck first to demonstrate the different features, including the regenerative braking and smooth driving techniques; such as anticipating when driving, and being gentle on the brake and accelerator. 

  • Then drivers drive the same route to experience what driving the truck is like.

Things to consider for coaching sessions:

It is useful for drivers to watch someone drive and then drive themselves. Some find it easier to take in information when they are watching rather than whilst driving.

Dealership Driver Training

The dealerships work closely with the fleets using the DAF battery electric trucks to support the introduction of the vehicle onto the depot and the continued use. They are the first point of contact for fleets and contact the fleet to see if they need any further support or information. The dealership teams:

  • Develop a long term relationship with fleets.

  • Support in the initial handover of the vehicles at depot. This includes taking all relevant staff through the vehicle features.

  • Ensure all the staff who may be required are present for the handover – who this is will vary depending on the fleet and depot.

  • The dealership trainers take the drivers through the vehicle and take them for a test drive, either on depot or out in the local vicinity.

  • The dealership trainers check in with the fleets on a regular basis to make sure any questions are addressed.

  • Training experts have found that drivers have been receptive to training on the battery electric trucks, often more so than when they are working on diesel vehicles, as they are new and different and there is an element of uncertainty.

Things to consider for follow up:

  • Having access to data makes it easier for the dealership driver trainers to spot if there is a need to follow up on some training.

  • Regular contact is important, to provide refreshers and make sure new drivers are trained.

  • Culture in the fleet has a big impact with engagement from drivers on fuel efficient driving. Some incentives can be at odds with encouraging best practice (e.g. rewards for the highest number of trips and time based incentives, like ‘task and finish’).

  • Working with drivers should be organic, training should focus on helping them to get the most out of the vehicle and understanding their pressures and requirements.

Fleet Driver Activities

  • Fleets have not yet introduced any additional training activities for fuel efficient driving in the BETT vehicles. Some fleets are considering introducing this towards the end of the year.

  • Most drivers have been very positive about the vehicles and found them easier to drive compared to diesel alternatives.

  • In terms of fuel-efficient driving across all vehicles, the priority and motivating factor varies between fleets: for some it is safety, for others it is cost savings, and for some it is carbon savings.

  • Carbon savings seems to be the biggest motivating factor for most public sector fleets, and it is growing in importance.

  • Experience of league tables, rewards and incentives for better driving from fleets has shown that they can work, but there are also risks of causing unease amongst drivers. When rewarding good driving behaviour, it is important to consider improvement and workplace environment, rather than just overall performance.

  • Fleets use data to assess the driving style of their drivers and will start by feeding back informally on how they can improve. They rarely find the need for taking more formal action. 

Key Considerations and Recommendations for Battery Electric Truck Driver Training

  • Give training the time and space. 

  • Make sure planning and supervisory staff understand the vehicle and requirements.

  • Long term and repeat activities are needed.

  • Regenerative braking and faster response to acceleration are the main differences between an EV and ICE.

  • Concern about range can encourage smoother and more efficient driving.

Driver Behaviour Change

We have assimilated and reviewed existing research on fleet driver behaviour. The literature review consolidates our knowledge of EV driver behaviour, fleet driver behaviour change, and helps to confirm the proposed factors to consider when developing a successful training programme to encourage efficient driving.

Driver Behaviour Change: Training Sessions

Research has identified the need for a combination of training approaches and interventions (both theoretical classroom and practical training) in order to change engrained driver behaviour and habits.1

  • Training sessions are a traditional behavioural intervention, forming a key initial step when introducing drivers to a BEV instead of an ICEV. The learning process allows the driver to adapt to new driving features (e.g. low noise emission, regenerative braking) and to the challenges of the BEV (e.g. range, available charging opportunities).

  • Training sessions are knowledge-based, providing theoretical information about maintaining a constant speed and anticipating traffic. These sessions can also include coaching and practical in-vehicle feedback devices that imitate energy efficient driving practices.

  • Training sessions can get drivers thinking about the importance of driver behaviour and driving style, promoting the efficient use of regenerative braking. This results in energy-efficient driving styles that lead to a longer usable range per charge.4

  • Training approaches in the form of eco-driving sessions can have a significant effect on the efficiency of a driver’s behaviour, extending range per charge.2 Research has shown that the usage of eco-driving strategies, including sailing, moderate acceleration, slowing down, and anticipatory driving have the potential to reduce energy consumption of a BEV by 25%.5 6

Driver Behaviour Change: Training Sessions

Studies based on ICEVs have shown correlation between eco-driving training sessions and reduction in fuel consumption and CO2 emissions.  

  • Public transport training in Serbia: eco-driving training by JGSP Belgrade recorded an average saving in fuel consumption of 8.6%.7

  • Truck driver training in Kazakhstan: eco-driving training saw a reduction in fuel consumption by 13.6% on average.8

Things to consider:

  • Maintaining the long term effect of reduced energy/fuel consumption in BEVs/ICEVs requires long term support. Studies have shown a drop in the continued efficiency of drivers without support to reinforce the behaviour change. 

  • Encouraging a sustained application of these techniques by drivers with the use of on-board devices or long-term driver support after completion of training. This would provide a constant assessment of fuel efficiency and encourage sustained eco-driving. 

  • Driver training schemes and eco-driving techniques can reduce fuel consumption, but their effectiveness ultimately depends on the willingness of drivers to change their behaviour. Training should make use of onboard driver assistance systems (in cab nudges) to encourage continuous driving style improvement.

Driver behaviour change: in cab nudges

A dynamic approach to eco-driving involves the use of in cab nudges. These include vehicle mounted devices that provide direct feedback to the drivers whilst driving through visual feedback, audible prompts and haptic modalities.9

In cab nudges for drivers can improve drivers behaviour, making them more energy efficient and effective by providing them with information on their driving style.

  • Studies have shown in cab nudges are important in maintaining drivers’ ability to adapt their behaviour and encourage long-term behavioural change. 

  • In cab nudges, as a behavioural approach to emissions reduction, hold significant potential in reducing CO2 emissions and maximising energy and cost savings.

  • Real-time traffic sensing, telematics and advice: A US study showed that in cab nudges smooth the traffic flow and decrease fuel consumption by advising vehicles to travel at specific speeds. This method helped reduce fuel consumption and CO2 emissions by 10–20% without significantly affecting overall travel time. The percentage savings depend on the congestion level: for severe congestion, the savings are considerable. 10

  • In cab prompts and behavioural feedback: In cab nudges strengthen a driver’s self-regulation. The use of prompts and behavioural feedback helps drivers enhance their constant awareness of their good intentions, as well as their implementation efforts. Using in cab nudges activates the recall of drivers’ intentions about eco-driving.11

  • Informational nudges: In cab informational nudges help improve the performance of ICEV drivers who were not intrinsically motivated to drive well. In a field experiment of a German logistics company, average CO2 emissions were significantly reduced from 838 g/km to 793 g/km (-5%).12

Things to consider:

  • Studies have identified the potential for in cab nudges to draw attention away from the driving task, presenting a distraction risk for drivers. The studies recommended intermittent over continuous eco-driving feedback, to encourage fewer glances on the display, hence reducing distraction.13 14

  • Detailed feedback on driving style or driver scores should be checked before or after a journey to avoid distractions and improve conscious awareness on the next drive.

  • In cab systems should also account for weather conditions and load factor, which can affect driving styles and fuel consumption.

Driver behaviour change: coaching

Coaching teaches drivers how to improve their driving behaviour through one-to-one sessions in combination with telemetry data to review their driving style. This approach differs from training sessions in that it provides one-on-one tailored on-the-road sessions as part of continuous improvement and culture change.

Tailored coaching can help drivers understand the main differences when driving BEVs and learn how to get the best out of their BEV in terms of range and performance. Drivers can benefit from coaching while driving in real conditions, allowing for:

  • Improved driving style and familiarity with the truck.

  • Addressing issues and encouraging reflection and willingness to change.

Previous studies have shown that a purely class-based or theoretical eco-driving training does not sustain energy saving, drivers need actual training and practical guidance.15

Best practice for shifting driver behaviour and style would need to involve repeat coaching sessions and feedback on performance using telemetry data, to encourage habitual driver behaviour and create a positive culture of continuous driver improvement.16 The Scania Driver Support system, provides real-time coaching in HGVs with tips and feedback via a visual HMI,  improving fuel efficiency by 10% (from around 37 to 33 litres/100km) in trials in northern Sweden and Norway.17

Behavioural coaching, in combination with telemetry data can help facilitate effective coaching conversations with drivers, encouraging behaviour change.

A US individualised coaching and in cab feedback system on real-world routes showed a 2.6% fuel economy improvement for sleeper cabs (5.4% with financial incentives), and a 5.2% fuel economy improvement for day cabs (9.9% with financial incentives) after two months.18

The benefits of coaching on driver behaviour include: 

  • Tailored action plans for each driver and setting interim goals.

  • A better understanding of drivers’ existing style and teaching them how to be more efficient without cutting into their driving time on a route. 

Things to consider:

  • Cannot control driver behaviour post coaching, best practice is to establish a change in the culture and behaviour of the entire fleet.

  • Best practice would include repeat sessions and feedback on performance between sessions. 

  • Combination of coaching and training sessions helps drivers improve their behaviour better than training alone. 

  • Access to onsite coaching is dependent on the location, BEV drivers need access to a sizeable yard to allow for better results.

Driver Behaviour Change: Rewards and Penalties 

  • A key challenge in changing driver behaviour is sustaining positive change in driving habits and breaking negative driving habits.19

  • Rewards and penalties can influence driver behaviour by providing attainable goals. This goal-directed approach to behaviour change helps drivers think about the impact of their driving style. This approach recognises that a driver’s primary goal “is not to save fuel but to distribute the product […] through an optimal distribution”, linking eco-driving to a reward, meaning there is a stronger chance that improved driving styles will be reinforced.20

  • The use of rewards and penalty systems have proven popular with several fleet companies that have adopted these applications, by using telematics to monitor driving behaviour and offer targeted rewards and discounts depending on how they drive. 

  • There are several examples of rewards and penalty applications for domestic and fleet vehicles, with some tracking driver behaviour through in cab technology or phone apps to encourage improvements in driving style, while others offer monetary rewards for eco-driving.

The main concern of these applications is to create a self-motivated approach to improvement and encourage changes in driver behaviour across a fleet.  

  • In-cab technology:  the Lightfoot system combines simple in-cab technology providing real-time performance indicators and audio feedback to encourage smoother driving, including weekly prizes for ‘elite’ drivers. As their performance improves, drivers can enter competitions, win prizes, and compete in league tables through the Lightfoot app.21 

  • Eco-driving reward system: Studies have shown a positive impact of reward strategies on fuel efficiency, these can include prizes (movie tickets, fuel vouchers, etc.) and discounts associated with eco-driving behaviour.22 A study in Taiwan established an eco-driving reward system as an effective strategy for improving fuel efficiency and lowering the operating costs of bus companies, improving fuel consumption by 10% and reducing carbon emissions.23

Whilst financial incentives can double fuel savings in some studies, incentives alone may not work at a cost-effective level in changing driver behaviour 24. A German study on EV buses noted that instead of a “reward/punishment-type feedback", drivers might be more responsive to abstract feedback indicating that their driving behaviour lies within a certain ‘green range’ where no further behaviour adjustment is necessary. 25

Things to consider:

  • We need to design more effective in-vehicle devices, in combination with training and coaching programmes, as rewards and penalties used in isolation will not have lasting benefits.26

  • Without constructive feedback to behaviour there is a chance that positive behaviour change will ‘drift’- this occurs when behaviour is not monitored or reinforced. 

Driver Behaviour Change Theory

People are hard to change; however, understanding why a particular behaviour is performed and how best to influence this gives us the best chance of encouraging sustained change. Behavioural science and psychology can help to inform measures to change behaviour. In the following slides, we present a small amount of information from behaviour change theory that may be useful.

The COM-B Model27

The COM-B model of behaviour described by Michie et al. attempts to represent the complex process that leads to behaviour based on three aspects: capability, opportunity, and motivation. The goal was to present behaviour model practitioners across all sectors to help develop, describe, and evaluate intervention functions. In the COM-B model, capability refers to one's ability, both physical and psychological, to undertake the behaviour. Opportunity can be classified as physical and social; motivation is the brain process that defines and directs behaviour and can be split into two categories, reflective and automotive. The components interact within the system to influence the behaviour. Therefore, an intervention can impact one or more components that affect the behavioural outcome.

Each element in the behaviour change wheel is split further into two definitions:

  • Physical Capability: a person’s physical and musculoskeletal functioning.

  • Psychological capability: a person’s mental functions (e.g. understanding, memory and knowledge).

  • Reflective motivation: Conscious thought process (plans, evaluations).

  • Automatic motivations: quick thinking, e.g. habit, drive-related and instinctive processes.

  • Physical opportunity: involves the environment and system (financial and material resources).

  • Social opportunity: People and organisations (social norms and culture).

Self Determination Theory of Motivation28

Self determination theory (SDT) emphasises people’s motivation for learning and growing and how this can be supported. The theory aims to explain how people learn and can be used to help develop training and teaching styles that will be effective, promote high engagement and increase wellbeing. There are three aspects to the SDT, if any of these elements are lacking, this will damage motivation and make changing behaviour more difficult:

  • Autonomy: A sense of ownership over one’s actions, an enjoyment in learning/developing. Autonomy is supported by experiences that encourage initiative and is undermined by external controlled experiences – whether by rewards or punishments.   

  • Competence: concerns feeling of mastery, a sense that one can succeed and grow. Provision of feedback and opportunities for growth support competence.

  • Relatedness: describes a sense of belonging and connection. This is supported in environments that promote respect and caring.

SDT is often discussed in relation to extrinsic (external) and intrinsic (internal) motivation.

Putting into practice:

Training and interventions that aim to encourage eco-driving should consider how they foster autonomy, competence and relatedness, for example:

  • Gamification (such as in-cab nudges) can increase the enjoyment in the process and increase autonomy.

  • Providing information on the positive impact of eco-driving (from safer driving, low air pollution, lower fuel cost and reducing carbon emissions) should seek to develop a sense of connection and respect via the company culture.

  • Eco-driving interventions should provide opportunities for growth and success. Feedback and support should be given to increase competence.

  • Rewards should be considered carefully to ensure they do not undermine the drivers autonomy and ability to feel competent.

Social Influence and Habit

How social norms impact personal decisions:

Research into driving behaviour has found that personal identity and norms significantly impact traffic behaviour. Personal identity describes how someone thinks about themselves, their skills and their ability to undertake a particular activity. Personal norms describe the moral values that an individual holds and the anticipated regret they may have if they go against these values. 29

Both personal norms and personal identity can be influenced by workplace culture. A workplace that encourages pride in eco-driving will foster a personal identity of a driver who perceives themselves as someone who drives in a fuel-efficient manner. Similarly, if the moral values of a workplace place importance on eco-driving, this will be reflected in the workforce.

In practice, this means that measures to support eco-driving must be placed as a high priority by all staff. For example, ensuring proper time away from work is given to training, not using incentives that encourage speed (such as ‘task and finish’ or the ‘number of trips’ incentives) and ensuring that all levels in the company are trained and aware of the benefits of eco-driving measures.

Habit – hard to break old ones, essential to set new ones:

Habit is a learned sequence of acts that have become automatic, unconscious responses to specific cues or triggers around us. They are efficient, independent of intention, independent of awareness and uncontrollable. 

Habit is context-specific, so specific to environments and situations and strongly linked to the habitual behaviour. One of the best times to break old habits and set new ones is when there is a change in the environment. 

Changing to a new vehicle and particularly the shift to electric vehicles presents an excellent opportunity for new habits to be formed. Strong expectations, training and coaching in eco-driving when drivers start using the new vehicles are likely to improve chances of developing good habits. 


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