Driving Examiners’ Perceptions and Awareness of Advanced Driver Assistance Systems: A Survey-Based Analysis ^†

Abstract

Advanced Driver Assistance Systems (ADASs) can have a significant role in contributing to road safety. However, technological innovations are gaining user acceptance at different rates, which is a key factor for their widespread deployment. In Hungary, learning about ADASs is not part of the curriculum in driving schools. In the present research, a questionnaire survey was conducted among driving examiners to assess their level of ADAS awareness. The results show that, in general, examining officers have a positive attitude towards the technology and are quite knowledgeable about it, compared to drivers. However, education and information are also essential for them, as there are few places to obtain credible information.

1. Introduction

Vehicle technology, and with it semi- and full automation systems, is evolving at a rapid pace along with other technological innovations. Advanced Driver Assistance Systems (ADASs) are increasingly being used in more and more vehicles, making research into these systems essential for safe driving. One of the largest groups of fatal accidents is of those resulting from inattention on the road [1]. In Hungary, Statista reports that in 2022, there were more than 14,000 road accidents involving some form of personal injury [2]. Research suggests that ADAS technologies can reduce the number of accidents and contribute to road safety [3,4]. Research by Cicchino (2018) found that vehicles equipped with lane departure warning systems reduced the number of accidents by 24% [3]. Systems such as Distance Alert, Autonomous Emergency Braking, Intelligent Speed Adaptation, Lane Departure Warning, Blind Spot Monitor, Backup Camera and Alcohol Interlocks have had a positive impact on passenger safety. In addition to safety benefits, automation systems can also play a positive role in promoting sustainability [5].

The SAE classifies vehicles into six levels based on their level of automation [6]. Level zero represents vehicles with no automation and level 5 is full automation, where the human driver is no longer required to control the vehicle under any circumstances [7].

In relation to ADASs, examining the level of knowledge and awareness is a major topic, along with confidence and acceptance. In many cases, drivers are not fully informed about these systems, and in many cases, they become familiar with these systems through experience without prior information [8]. Boelhouwer et al. (2020) conducted a survey on the level and amount of information participants received from dealerships in the Netherlands about ADASs. Around half of the respondents claimed that they had not received full information and 24% claimed that they had not been provided with any information [9]. Kaye et al. (2022) conducted a survey in Australia also on the location of information sources related to ADASs. In their study, 56% of the respondents reported that they had not requested any prior information about ADASs. In addition, results from the Technology of Acceptance (TAM) model suggested that perceived usefulness and perceived ease of use were positive predictors of use [10]. Besides the metrics of acceptance and trust, purchase intention and willingness to pay are also significant areas of interest in relation to autonomous vehicles [11].

The level of confidence in adopting ADAS technologies has a big impact on the acceptance of ADASs, as it influences how actions are taken when driving a vehicle. With a low level of trust in the technology, the driver is unlikely to use ADASs, and with a very high level of trust, the driver is likely to rely on ADASs in situations where he or she should take control of the vehicle [12]. In their experiment, Victor et al. (2018) found that 28% of participants did not take control of a vehicle with Adaptive Cruise Control (ACC) and Lane Keep Assist (LKA) to avoid a collision. The in-depth interviews revealed that the participants were overconfident that the systems would be able to handle the situation [13].

In the present research, a questionnaire survey was conducted among driving examiners to find out their level of awareness and attitude towards ADAS technologies. A literature search revealed that several studies have been conducted to investigate this among drivers. The novelty and purpose of the present research is to investigate this among individuals who can be considered as experts in the subject as they work as driving examiners. This was felt necessary because in Hungary, in driving schools, students do not receive information about these systems and it is not part of the curriculum.

2. Materials and Methods

A questionnaire survey was carried out to assess the examiners’ perception of ADASs and their level of awareness of this technology. The questionnaire was completed by 49 Hungarian driving examiners, which is considered to be a representative sample. The experts estimate that there are around 300 vehicle examiners in Hungary in 2024. The questionnaire was sent to a total of 256 respondents, 49 of whom completed it. Based on these data, 16.33% of the population was reached. The questionnaire covered several areas, such as travel and driving habits, technological attitudes, knowledge of ADASs and attitudes towards ADASs. The attitudinal statements were assessed by the participants on a 5-point Likert scale and the data were analysed using SPSS software 29.0 (IBM, Armonk, NY, USA). The questionnaire included additional questions and attitude statements related to the acceptance of ADASs and willingness to buy. These dimensions were not investigated in the present research.

3. Results

Demographic Characteristics of Driving Examiners

Table 1. Demographic data of driving examiners.

Demographic Data
Gender
Male	89.80%
Female	10.20%
Education
Secondary education	34.69%
College degree	40.82%
University degree	16.33%
Master’s degree or higher	8.16%
Age
31–40 years old	4.08%
41–50 years old	4.08%
51–60 years old	42.86%
61–70 years old	38.78%
71–80 years old	10.20%
Driving instructor
Yes	83.67%
No	16.33%
Subject of the examination
Theory	2.04%
Practice	26.53%
Theory and practice	71.43%

shows the demographic data of driving examiners in terms of gender, graduate and age distribution. The table also describes whether the respondents also work as driving instructors and whether they teach theory or practice.

A significant proportion of the interviewed examiners, 89.80% of whom were male, had a secondary education (34.69%) or a college degree (40.82%). In terms of age, the examiners tended to be in the older age group, with the sample consisting mostly of persons aged 50–70 years. In addition to being a driving examiner, 83.67% of the respondents were also driving instructors. Again, the highest proportion (71.43%) also teach theory and practice.

Table 2. Awareness level of ADAS.

Technology	Mean	Median	Mode	Std. Deviation
Adaptive Cruise Control (ACC)	4.20	5.00	5	1.14
Rear View Camera (RVC)	4.04	4.00	5	1.09
Lane Change Assistance (LCA)	3.90	4.00	5	1.22
Forward Collision Warning (FCW)	3.82	4.00	5	1.29
Adaptive Light Control (ALC)	3.73	4.00	4	1.16
Traffic Sign Recognition (TSR)	3.73	4.00	4	1.12
Lane Departure Warning System (LDWS)	3.71	4.00	5	1.21
Back-Over Protection (BOP)	3.63	4.00	4	1.08
Automatic Parking System (APS)	3.63	4.00	4	0.98
Collision Avoidance System (CAS)	3.45	4.00	4	1.21
Lane Centering Assist (LCA)	3.59	4.00	4	1.24
Intelligent Speed Adaptation (ISA)	3.45	4.00	4	1.33
Blind Spot Detection (BSD)	3.37	3.68	4	1.30
Moving Object Detection (MOD)	3.33	3.00	3	1.20
Camera Monitor System (CMS)	3.31	3.00	2	1.23
Rear Cross-Traffic Alert (RCTA)	3.14	3.00	4	1.20
Semi-Autonomous Driving (SAD)	2.53	2.00	1	1.33

shows the level of awareness of the surveyed examiners for each ADAS function. The highest mean awareness scores were achieved for ACC (4.20) and RVC (4.04) technologies. The surveyed examiners also achieved positive scores for most of the ADAS functions with mean scores above 3, indicating medium to high awareness levels. Among others, the technologies FCW, ALC, TSR and LCA scored above 3. Semi-autonomous driving had the lowest average level of awareness, with a score of 2.53; one of the main reasons for this may be that these systems are still relatively rare on the roads and are still under active development.

In terms of variance, the values are found to be low to medium. Overall, respondents have similar levels of awareness of ADAS technologies. The largest variance is observed for ISA (1.33) and SAD (1.33) technologies.

In addition to exploring the level of awareness of the respondents, we also considered it an important aspect to find out where they obtain their information about ADASs, as preliminary observations and the literature suggest that consumers receive little credible information from a variety of sources.

Table 3. Sources for information on the ADAS.

	Friends and Family	Colleagues	Owner’s Manual	Internet or Television Advertisement	Television Show or Movie	Social Media	News, Articles
Mean	3.37	3.90	4.29	2.73	2.73	2.80	3.22
Median	4.00	4.00	5.00	3.00	3.00	3.00	4.00
Mode	4	4	5	3	2	4	4
Std. Deviation	1.20	1.07	1.09	1.27	1.32	1.26	1.37

shows the descriptive statistical results related to the sources of information. The results show that the owner’s manual has the highest mean value of 4.29, which suggests that the majority of consumers consider this source of information to be the most credible. The median and mode for this type of information acquisition were both 5, and the standard deviation was relatively low at 1.09. Higher mean scores were also obtained for obtaining information from colleagues and from family and friends. In these two cases, both the mode and the median were 4. Respondents were least likely to obtain information from internet and television advertising and social media.

Table 4. Correlation between awareness and technology acceptance.

		Technology Acceptance
Awareness	Pearson Correlation	0.529 **
	Sig. (2-tailed)	<0.001

** Correlation is significant at the 0.01 level (2-tailed).

shows the age correlation between awareness and technology acceptance. The results show a strong positive correlation between the two variables, suggesting that examiners who are more interested in new technology in general are also more knowledgeable about ADASs, more familiar with the functions and more experienced. The Person Correlation for the two variables examined is 0.529 **.

4. Discussion and Conclusions

In the present research, an online questionnaire survey was conducted among Hungarian driving examiners to find out their attitude towards ADASs, their acceptance of ADASs and their level of knowledge and experience. A total of 49 examining officers completed the questionnaire, which is considered to be representative in Hungary.

As expected, they have a relatively high level of awareness and experience of the technologies under investigation. They are most familiar with ACC, RVC and LCA ADAS technologies, the main reason for this being that they are already widely used in the automotive industry, so presumably, the respondents have the most experience with these technologies. They are the least familiar with advanced automation technologies such as SAD, which is a relatively new technology, and currently, there are only a limited number of these on the road.

In terms of obtaining information on ADASs, the respondents most often consult owner’s manuals or seek the opinion of friends and colleagues. However, for ordinary drivers, understanding the owner’s manual can be difficult. Furthermore, the literature suggests that drivers most often obtain information from internet sources, which may not always provide accurate and reliable information.

The literature suggests that consumers and drivers often have low levels of awareness and are not familiar with ADAS technologies. One reason for this is that they do not receive adequate information either from driving schools when they take their driving test or at the dealerships where they buy an ADAS-equipped vehicle. The novelty of the present study is that the awareness level of driving school testers in Hungary was assessed by means of a questionnaire.

A limitation of the study is that, although the sample was representative, the number of participants was low, so significant results were not obtained in all cases. In future research, we propose to gain a deeper understanding of the perceptions of examiners using qualitative methodologies such as in-depth interviews. Furthermore, it may be worthwhile conducting a survey with Hungarian drivers on ADASs to understand their different perspectives.