The High Cost of Low-Speed Manoeuvre Collisions

Introduction

Fleet-based organisations often tell me that the highest proportion of their claims are due to collisions while reversing and parking – typically 70 to 80% of all collisions taking place. Truck and van drivers often need to park in tight spaces to load or unload their vehicles. For bus drivers, the highest risk for collisions takes place when pulling in and out of bus stops (Dorn and Muncie, 2005). Not only is this a huge financial burden for companies, but for drivers of heavy vehicle the stakes are high because vulnerable road users are at risk (NHTSA 2006). Large vehicles have blind spots; they need more space and overhang kerbs or verges when turning due to wider turning radiuses than cars. In built-up areas, parked cars may obstruct the view and make it more difficult to monitor the movements of vulnerable road users and other vehicles (Dorn and af Wåhlberg, 2008). Drivers may also fail to detect low height objects such as bicycles and road furniture.

Given the complexity of the manoeuvring task, it’s not surprising that driver error is a major contributor to collisions (Fildes et al, 2014). Numerous in-vehicle systems and technical solutions have been developed to help drivers park, but studies evaluating their effectiveness report mixed results, with some even leading to an increased risk of collisions. Drivers may rely on the system, ignore the alerts and fail to look properly and still crash. Whilst there has been a major emphasis on designing in-vehicle systems, training interventions have received comparatively little attention. Designing better training to address human error must first consider the nature of these errors.

Human Factors and Low-Speed Manoeuvres

Driver Training

Poor visual attention plays an important role in the frequency of collisions when parking and reversing and avoiding any form of distraction is essential when training drivers to manage the risks. Training should be developed to take into account four key cognitive substages for the safe execution of low speed manoeuvres. 

Perception - perceiving the potential parking hazards through correct and purposeful eye movements. When navigating the visual world, most scenes we encounter contain too much information to be processed in totality and drivers may fail to process relevant visual information. Visual fixations may be targeted whilst parking but often occur ‘just-in-time’ leaving an opportunity for error to take place (Lappi et al, 2017).

Anticipation - anticipating parking hazards via an interpretation of the visual information. During a low-speed manoeuvre, drivers must make the right decision about where to look and what to select to develop their situation awareness. To manage the demands of this highly cognitive task, drivers must look at several locations around the vehicle with frequent lateral glances to the sides as well as toward the space they want to use. At the same time, drivers must look rearward and forward when reversing into it to anticipate potential hazards.

Response Execution – executing an action or response (or lack of response) such as steering, pressing the brake, accelerator, mirror checks etc must be highly practised for precise and timely response. Too often, drivers receive insufficient practise in the safe execution of a low-speed manoeuvre, especially novice drivers.Training should focus on reflecting on the driver’s capabilities and ensure that appropriate mental models are developed for a wide range of different contexts.

Response Feedback – assimilating the learning acquired to develop and refine mental models for future parking/reversing situations. A relatively small number of drivers within any organisation may be repeatedly involved in the same types of collisions (af Wåhlberg & Dorn, 2009; Hanowski et al, 2000; Wierwille et al, 2000) suggesting that this cognitive substage is not being addressed.

Experienced drivers are guided by mental representation of the operating environment, and these mental models provide an almost automatic allocation of attention to specific sub-regions of the visual field. Experienced drivers can better interpret peripheral information around the parking area compared to novices who have less well-developed mental models for low-speed manoeuvring. They use attentional and visual resources to interpret a vague impression of motion in the periphery as something they might want to make an eye movement towards (Crundall, 2016) whereas novice drivers have not yet developed a second sense of how a traffic situations might unfold and where they need to look .

Mental Rotation, Distraction and Low Speed Manoeuvres

For safe parking, drivers are required to imagine their vehicle from different perspectives, and this involves a specific cognitive ability called mental rotation. Mental rotation is the ability to manipulate mental images of objects in three-dimensional space, as if mentally rotating them in your mind. A driver who steers towards a parking space must predict the outcome of spatial relationships between objects (including own vehicle, parking space, other vehicles, and kerb etc) as the viewpoint changes with each vehicle movement. At low speeds, experienced drivers tend to distribute glances evenly around the vehicle during a complex backing sequence such as parallel parking. If precise placement of the vehicle is not required though, and there are few obstacles, extended curved backing tasks can be executed at higher speeds as it requires fewer mental rotation demands. In these kinds of manoeuvres, drivers tend to use glances that are focused in one direction (backward over the shoulder) (Huey et al, 1995).

Reverse parking requires a wider visual search than front parking and drivers can little afford to be distracted during such a visually demanding task. High workload during such manoeuvres means there is little spare capacity for taking on a secondary task because drivers need additional information processing time to park safely (Rendon-Velez et al, 2016). In a study of 41 long-haul truck drivers working their normal delivery runs, telematics data relating to crashes, near-crashes, and crash-relevant conflicts were collected over approximately 140,000 miles (Hanowski et al, 2005). Of the 2737 ‘critical incidents’, 77% were due to judgment error, followed by ‘other vehicle’ and distraction was the third highest cause of the incident. The study found that truck drivers may be distracted even during visually demanding reversing tasks.

A Behavioural Intervention

Even highly trained experienced drivers are involved in low-speed collisions suggesting that skills-based training is not the only necessary intervention for reducing the risks. In many cases, drivers may be under time pressure or fatigued and fail to notice hazards in their periphery. A wide range of professional drivers for the emergency services, logistics, multi-drop or passenger services may mentally switch off whilst parking at their destination or at a bus stop and become involved in a secondary task such as reaching for paperwork or looking at devices to check routes etc. Some drivers develop overconfidence in their vehicle handling skills and attempt to park in a difficult space. Belief in your ability to perform a manoeuvre can lead to a biased assessment of one’s own capabilities. Drivers may fail to get out of the vehicle and check for potential obstacles and hazards, especially when under time pressure or when fatigued. 

Multiple collision involved drivers can be targeted for specific interventions, but the question is, what should such an intervention look like? Most organisations focus on delivering in-vehicle training to practise low-speed manoeuvring tasks. However, drivers may demonstrate appropriate behaviour when being observed by a trainer/assessor and the training often takes place in a non-operational context. An intervention that focuses on driver behaviour aims to develop greater insight into the human factors that can increase the risk of collisions during low-speed manoeuvres.

To find out more about our behavioural intervention, click on the link below.

https://www.psydrivegroup.com/driver-cpc

Develop your knowledge and skills in Human Factors

The Human Factors and Road Risk Management programme has been accredited by the Chartered Institute of Ergonomics and Human Factors as developing the competencies required of a human factors specialist. The programme is delivered online for 2 days by Dr Lisa Dorn or in person on request. The course encourages active, value-driven discussions and tailored to the specific interests of the delegates attending. The next set of course dates are shown below:

24th and 25th September

26th and 27th November

For more information, click here:

https://www.psydrivegroup.com/human-factors-course-level-1

References

Crundall, D. (2016). Hazard prediction discriminates between novice and experienced drivers. Accident Analysis & Prevention, 86, 47-58.

Dorn, L. & af Wåhlberg A. (2008). Work related road safety: An analysis based on UK bus driver performance.  Risk Analysis, 28(1), 25-35.

Dorn, L. & Muncie, H. (2005). Work related road safety: Age, length of service and changes in crash risk.  Behavioural Research in Road Safety: 15th Seminar. Department for Transport, London.

Fildes, B., Newstead, S., Keall, M., & Budd, L. (2014). Camera Effectiveness and Backover Collisions with Pedestrians: a Feasibility Study, Report No. 321. Monash University Accident Research Centre, Melbourne.

Huey, R., Harpster., J., & Lerner, N. (1995). Field measurement of naturalistic backing behavior (DOT HS 808 532). National Highway Traffic Safety Administration: Washington, DC.

Hanowski, R. J., Wierwille, W. W., Garness, S. A., & Dingus, T. A. (2000). Impact of local/short haul operations on driver fatigue, final report (Report No. DOT-MC-00-203). Washington, DC: US Department of Transportation, Federal Motor Carriers Safety Administration.

Hanowski, R. J., Perez, M. A., & Dingus, T. A. (2005). Driver distraction in long-haul truck drivers. Transportation Research Part F: Traffic Psychology and Behaviour, 8(6), 441-458.

Lappi, O., P., Rinkkala, & Pekkanen. J. (2017). Systematic Observation of an Expert Driver’s Gaze Strategy-An On-Road Case Study. Frontiers in Psychology, 8: 620.

NHTSA (2006). Vehicle Backover Avoidance Technology Study. Report to Congress accessed 4th April 2025 https://www.nhtsa.gov/sites/nhtsa.gov/files/backoveravoidancetechstudy.pdf

Rendon-Velez, E., Van Leeuwen, P. M., Happee, R., Horvath, I., Van der Vegte, W. F., & de Winter, J. C. (2016). The effects of time pressure on driver performance and physiological activity: A driving simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 41, 150-169.

Wierwille, W. W., Kieliszewski, C. A., Hanowski, R. J., Keisler, A. S., & Olsen, E. C. B. (2000). Identification and evaluation of driver errors: Task E report—Investigation of critical incidents (Interim Report for the Federal Highway Administration Contract No. DTHF-61-97-C-00051). Washington, DC: Federal Highway Administration.

af Wåhlberg, A. E., & Dorn, L. (2009). Bus driver accident record; the return of accident proneness. Theoretical Issues in Ergonomics Science, 10, 77-91.