27 How to cite this article:
Azman, M. ‘Izzuddin, Nawi, N. S. M., & Sukadarin, E. H. (2022). Is The Malaysian Driver Ready To Use An Automatic.
Journal of Technology and Operations Management, 17(2), 27–39. https://doi.org/10.32890/jtom2022.17.2.3.
IS THE MALAYSIAN DRIVER READY TO USE AN AUTOMATIC EMERGENCY BRAKING (ABS) SYSTEM?
1Muhammad ‘Izzuddin Azman, 2Nur Syazwani Mohd Nawi, 3Ezrin Hani Sukadarin
1-2School of Technology Management and Logistic, Univeristi Utara Malaysia
3Faculty of Industrial Sciences and Technology, Universiti Malaysia Pahang
Corresponding author: nursyazwani@uum.edu.my
Received: 10/08/2022 Revised: 11/09/2022 Accepted: 8/11/2022 Published: 29/12/2022
ABSTRACT
Autonomous Emergency Brake (AEB) is the safety system technology for the vehicle that functions to prevent a crash or reduce the high impact of injury or accident. AEB systems are designed to assist the driver only in emergencies situation and to ensure that the driver is always in control of the vehicle.
This study aims to identify influencing factors of drivers that continuance intention to use an Automatic Emergency Braking (AEB) system in Malaysia. This study is supported by Technology Acceptance Model (TAM). This study shows that 3 factors have significantly related to continuance intention; perceived ease of use, attitude, and perceived usefulness. In contrast, the safety of drivers was found to be insignificantly related to the continuance intention to use automatic emergency braking among drivers in Malaysia. The AEB system is a sophisticated system that helps alert the driver to a lack of human response. Therefore, the successful use of this system needs the full support of the government and industries.
Keywords: Autonomous Emergency Brake (AEB), Technology Acceptance Model (TAM), influencing factor, continuance intention to use, Malaysia.
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INTRODUCTION
Road accidents are currently one of the main causes of fatality and injury. The World Health Organization (WHO) reported that road traffic accidents are the main cause of death, especially for pedestrians, cyclists, and motorcyclists, who account for 54% of fatalities nowadays. In Malaysia, accidents on the road are one of the main causes of serious injuries and death. A report from the Malaysian Ministry of Transportation shows that accidents on the road in Malaysia increase from 2009 to 2018 (Ministry of Transport, 2019). These accidents happen from various causes and one of them is from vehicle’s condition. Safety features are important for vehicles in order to prevent or reduce the case of deaths in Malaysia. With safety features applied in vehicles, it can help to increase the awareness among the drivers for using the safety features in cars.
Thus, safety is considered an important factor in the decision-making process by the users when buying a used or new car. Automatic Emergency Braking (AEB) is a new safety technology used in current cars that can help the driver alert and autonomously stop when the necessary human response is not available in critical situations (Mokhtar et al., 2019). The AEB system for the technology of vehicles has been developed and implemented to reduce accidents of vehicles caused by humans (Mokhtar et al., 2019). This system has been created and used worldwide as one of the car’s safety systems after many incidents related to vehicles, pedestrians, cyclists, and motorcyclists with the car.
The Advanced Driver Assistance System (ADAS) in vehicles are now increasing in the automotive industry, especially in safety assist technology, however the level of acceptance ADAS such as AEB systems among the drivers still remains moderate. Certain drivers prefer to use ADAS, and some of the drivers are highly against using ADAS (Syafiq & Mohamed, 2017). Drivers who still have no experience using the AEB system are usually suspicious of the AEB system, which is felt trying to interfere with the driver during driving (Stave & Strand, 2015). Hence, the factor of continuance intention to use technology for AEB systems among drivers is a highly relevant issue among Malaysian drivers, especially the AEB system which is slowly making its way to the common market in Malaysia. Therefore, this study aims to identify the influencing factors of perceived ease of use, the driver’s safety, attitude, and perceived usefulness towards intention to use of Automatic Emergency Braking (AEB).
LITERATURE REVIEW
AEB system is one of the recent technologies for the safety system on cars which has been developed to reduce human mistakes that cause accidents on the road (Mokhtar et al., 2019). This technology has been implemented in many cars such as Honda, BMW, Audi, Ford, and others. The AEB system is equipped with remote sensing technology such as radar, LIDAR, and cameras to avoid rear-end collisions and sense potential hazards in front of the vehicle (Rani et al., 2019). This system also operates when the previous vehicle suddenly brakes caused by an accident, or suddenly when having the object enters the driveway of the vehicle on the road (Kim & Lee, 2020). This system shows that automatic emergency braking (AEB) at low speed can reduce crash rates by around 43% and crash rates for the injury front-to-rear around 45% (Tan et al., 2020). Thus, the AEB system can effectively improve vehicle driving safety, reduce the incidence of crashes and injuries, and driver intensity (Hamid et al., 2017). For that reason, it is assessed as an important system for accident prevention and reduction.
Figure 1 illustrates how the distances between vehicles can be determined in order to set a safe range.
The AEB system is to stop or slow the car until it reaches the Minimum Safe Distance (MSD). It must be noted that the AEB itself is different from the normal braking system. The AEB is a sophisticated
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system that alerts the driver to a lack of human response during critical situations and independently brakes (Mokhtar et al., 2019). Moreover, this system is designed to prevent a collision or minimize severe injury impacts by using sensor technologies and recognition algorithms to detect vehicles and pedestrians. The potential advantages of AEB are due to the efficiency, which can reduce the number of target crash populations and the proportion of all crashes (Newstead & Budd, 2020). The AEB systems will allow an emergency brake with an automatic when a vulnerable road user (VRU) is detected while a driver does not respond in a timely manner to prevent or mitigate a collision, saving innumerable lives, lesions, and social costs (Song et al., 2020). Although AEB played a key role in reducing road accidents, numerous studies have been carried out to improve its performance (Song et al., 2020).
a: Collision
b: Minimum safe distance
c: Collision imminent braking distance d. Normal braking range
e: Warning mark
Figure 1. The Distance of Threshold for the System of Braking (Source: Sharma et al., 2019)
The AEB system in Malaysia
Malaysia is one of the countries that has implemented the AEB system in its local vehicle. One of the local vehicles that use this system is the Perodua Myvi model 2017. From the Malaysian Automatic Policy 2014, it states that there are a few advancements that will take place in Malaysia by 2020, 2030 and 2040 in order to guarantee the country keeps following up with the latest technology of land transport and also from the Global Automotive Roadmap (NCAP, 2017). Malaysia has admitted road safety as one of the critical problems that need to settle with fast. ASEAN NCAP has listed during the press release the AEB induction as a condition in their New Rating Protocols for 2017-2020 (Baharuddin et al., 2019). From this, the implementation of the AEB real-time must be performed and expanded in all states of Malaysia. Due to the high price for the models of vehicles implemented for this AEB system in Malaysia, this technology system still not yet can give some benefit to the general masses. For now, AEB systems are not created in Malaysia for vehicles. The two main car manufacturers in Malaysia such as Proton and Perodua still do not offer the AEB system in all their car models except the Perodua Myvi model 2017 (Baharuddin et al., 2019). Thus, they should be focused on the AEB research area in the coming year. A few factors that should be considered, especially for
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the design of the AEB system. Therefore, Malaysia still does not have any plan for fully implementing the AEB system until 2025 (Anwar et al., 2017).
Table 1
Local and Import Cars that install AEB System in Malaysia Category of Car Brand of Car
1. Local Car -Perodua Myvi (manufactured in 2017) -Perodua Ativa
-Proton SUV X70 and X50
2. Import Car Audi, BMW, Ford, Mercedes-Benz, Honda, Toyota, Volvo, Hyundai, Kia, Land Rover, and Volvo
Driver Behavior of Using AEB System
The driver is an important individual with full authority over the vehicle being driven. Driver’s behaviours may cause risk in the road accident, such as mistakes and violations. In addition, the expectations of drivers about potential crashes also influence their braking response significantly (Duan et al., 2017). If the brake does not function efficiently, possibly a harmful effect will happen to the drivers. This situation will influence the driver’s behavior and then influence their action to remain with the existing manual braking system or consider the new advanced technology, i.e. AEB. The new technology produced by the manufacturer for the vehicles proved can reduce the severity of road crashes and help the driver react during driving. The driver’s behaviour towards car safety, such as using the car equipped with the AEB system, was dependent on the driver. The buying decision based on safety characteristics is not the driver's decision only but also influenced by other factors such as social groups and situation factors (Kassim et al., 2016). In Malaysia, the level of vehicle safety has been increased by regulation and by driver’s positive attitude towards the developed regulation. The correct attitude behavior among drivers is important to indicate the acceptance rate of the AEB system.
Suppose the attitude of drivers towards safety is positive. In that case, it will give the impact to the driver to accept and purchase (ultimate behaviour in this study) the cars that have the AEB system.
Technology Acceptance Model (TAM)
This study seeks to apply the theory of the Technology Acceptance Model (TAM) to investigate driver factors of using the AEB system. Perception of AEB among users or potential drivers in Malaysia has been explored recently using a different set of human psychological theories (Ishanuddin, et al. (2021a); Ishanuddin, et al. (2021b). The Technology Acceptance Model (TAM) created by Davis (1989), which is one of the most extensively used models explaining user acceptance behaviour. The TAM model has been constructed by four factors: perceived usefulness, perceived ease of use, behavioural intention to use, and actual use. The TAM models explain to find the factor of user continuance intention to use the technology, which was determined by two things such as perceived usefulness and perceived ease of use. Even though, it contributes to the behavioural intention of use (accept) technology and then brings to the real user actions. Perceived usefulness (PU) and perceived ease of use (PEOU) are the constructions that shape the ideas of end-users about technology and so
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anticipate their attitude toward it, which in turn anticipate its acceptance (Davis, 1989). The TAM has been widely applied in various fields over the past several decades, most especially when it involved using information technology. However, the TAM model is also suitable for use in other areas of study and not necessarily those related to information technology only. In this study, the components of perceived usefulness (PU) and perceived ease of use (PEOU) will be the indicator of user continuance intention to use of automatic emergency braking (AEB) system. The research framework for this study is presented in Figure 2. The TAM model with modified derived it. This study has five variables:
continuance intention as a dependent variable and perceived ease of use (PEOU), safety driver, attitude, and perceived usefulness (PU) as independent variables.
Figure 2. Research Framework
Continuance Intention to Use of AEB System Usage Among Drivers
The intention is the decision to purchase the product or service again based on a decision-making process (Bhattacherjee, 2001). Additionally, continuos use in AEB systems can be defined as the continual use of a product or service (Nabavi et al., 2016). Continuance intention to use is an action taken that results in the continued usage of a product or the decision to discontinue use in the future (Chang, 2013). Therefore, many issues influence the driver in Malaysia to accept a new vehicle system. Based on Tan et al. (2020), perceived usefulness, acceptance, and suitable level of trust are essential preconditions for purchasing and using automated assistance systems. This study has been conducted with a few factors affecting the continuance intention to use automatic emergency braking usage among Malaysian drivers.
Perceived Ease of Use (PEOU)
Perceived ease of use (PEOU) is one of the primary elements derived from Davis's theory (1989), alongside perceived usefulness (PU). The PEOU explains how the degree to which a person believes that using a particular technology would be effortless (Osswald et al., 2012). For this study, PEOU has
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been identified as a critical component for investigating and evaluating user continuance intention to use (acceptance) a technology. Perceived ease of use (PEOU) is a significant motivator for technology usage intentions (Revels et al., 2010). The PEOU is a term that typically refers to a perception of users whether completing a certain technical activity will be needed mental effort on his or her part (Rouibah et al., 2011). Hence, users can adjust their behaviour to new technology if users believe it is easy, referred to as PEOU (Morosan, 2012).
Safety of Driver
Drivers always emphasize the safety aspect while driving their vehicles. The awareness of the situation is seen as crucial in system design and is even more important in the safety of the vehicle since drivers are sometimes exposed to various risks that require urgent manoeuvre such as automatic emergency braking (Payre & Diels, 2020). The safety provided in the vehicles, makes the driver feel safe to use the vehicles. Safety in vehicles can increase the confidence of drivers. Therefore, acceptance depends on drivers feeling safe with automatic system characteristics during driving that will influence safety among drivers (Koglbauer et al., 2018).
Attitude
In general, the term attitude can be defined in various ways. One of the definitions of attitude can have a long-lasting effect on behaviour and is applicable in a wide variety of circumstances (Peter & Olson, 2010). It is also defined as an positive or negative feelings (evaluative effect) about engaging in the target behaviour (Yousafzai et al., 2007). This performance is shaped by their responses and reactions in a specific situation, which are affected by their judgment/feelings when reacting in either good or bad behaviour. Moreover, in a psychological study, three parts of attitudes that can be used which are affected, cognition, and behavior (Mantle‐Bromley, 1995). These parts are referring to a level of preference for people, a knowledge about the attitudinal object, and a reactions and intentions toward the object, respectively.
Perceived Usefulness (PU)
Perceived usefulness (PU) can be described as the degree to which users believe a particular product or service is useful in terms of enhancing their everyday job performance and efficiency (Park, 2020).
From the definition, the advantage of perceived usefulness to the belief in their ability to make a decision. In other words, for this study, if a user believes an automatic emergency braking (AEB) system is ineffective, he or she may choose not to use it, as the perception has influenced the attitude.
Hypotheses
Research hypothesis is about the statement of tentativeness related to the relationship between two or more variables and also known as the what the researcher expects on the testable prediction and specific regarding for study of research (Kabir, 2016). In other words, the hypothesis needs to identify one character or variable for the sampling unit that influences the variable with the other sampling unit. The variable that affects another is known as an independent variable. Meanwhile, the variable which is affected by the independent variable is known as the dependent variable. The researcher needs to prove the hypothesis that has been developed. Thus, this study proposed the following hypotheses:
H1 : There is a relationship between perceived ease of use and continuance intention to use AEB system.
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H2 : There is a relationship between safety of driver and continuance intention to use AEB system.
H3: There is a relationship between attitude and continuance intention to use AEB system.
H4: There is a relationship between perceived usefulness and continuance intention to use AEB system.
RESEARCH METHODOLOGY
A survey was conducted to collect data from car drivers who have experience in using the AEB system. The quantitative method is an appropriate method for this study to obtain a large and accurate number of respondents and provide a quick response to their intention to use the automatic emergency brake system (AEB). The sample size of this study was around 300 using the G*Power Software sampling calculator. In total 150 respondents have answered the survey. The response rate for the questionnaire survey is 50% which is half of the sample size that can proceed to analyze the data as referring to Babbie (2007) that stated a response rate of 50% in social research surveys is acceptable.
The data collection was conducted through an online survey questionnaire. For this study, the questionnaire has been designed into 2 sections. The first section is about the demographic information that includes the gender, age, race, duration using car and category of car related to personality which can help for this study. The second section has five categories regarding the relationship between dependant variable and independent variables for the automatic emergency braking system among drivers. Section two which have the items that are needed in order to achieve the objectives for this study. Table 1 shows the item used to measure each construct. Each item has been constructed and measured by using a five-point Likert scale from strongly disagree (1), disagree (2), neutral (3), agree (4) and strongly agree (5).
Data analysis was performed using Statistical Package for Social Science (SPSS) version 26.0.
Descriptive analysis was used to analyse the information of respondent in gender, age, race, state, duration using car and category of car. In this study also using correlation analysis which is a statistical method that purpose to determine whether two variables have a relationship.
Table 1
Construct and Measurement Items
Construct Measurement items Source
Continuance Intention to Use
• I intend to use the Automatic Emergency Braking (AEB) system in my driving.
• I increase the occurrences of using the Automatic Emergency Braking (AEB) system in driving.
• I intend to use the Automatic Emergency Braking (AEB) system as often as needed.
• I expect to use the Automatic Emergency Braking (AEB) system in the future.
Weng et al. (2018);
Wu et al. (2008);
Rahi et al. (2017)
Perceived Ease • My interaction with the Automatic Emergency Rahman et al. (2017)
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of Use Braking (AEB) system would be clear and understandable.
• Interacting with the Automatic Emergency Braking (AEB) system would not require a lot of mental effort.
• I would find it easy to get the Automatic Emergency Braking (AEB) system to do what I want it to do.
Safety of Driver
• I feel safe while using the Automatic Emergency Braking (AEB) system.
• Using the Automatic Emergency Braking (AEB) system decreases the accident risk.
• I believe that using the Automatic Emergency Braking (AEB) system is dangerous.
• The Automatic Emergency Braking (AEB) system distracts me from driving.
Osswald et al. (2012)
Attitude • Using the Automatic Emergency Braking (AEB) system is a good idea.
• The Automatic Emergency Braking (AEB) system makes driving more interesting.
• I think that using the Automatic Emergency Braking (AEB) system would be beneficial for me.
• I would like to interact with the Automatic Emergency Braking (AEB) system.
Osswald et al. (2012);
Nastjuk et al. (2020)
Perceived Usefulness
• Using the Automatic Emergency Braking (AEB) system can improve my driving performance.
Voinea et al. (2020);
Kim, (2012)
• Using the Automatic Emergency Braking (AEB) system in driving can increase my safety.
• Using the Automatic Emergency Braking (AEB) system enhance effectiveness in my driving.
• Using the Automatic Emergency Braking (AEB) system is useful in my driving.
DATA ANALYSIS
A number of 150 questionnaires by using the online questionnaires survey were distributed to the respondents and returned to the researcher. In this study, to test the hypothesis, find answers to research questions and research objectives created. It shows that data analysis is one of the crucial part to clarify the study. The data analysis generated by using Statistical Package for Social Science (SPSS) version 26.0. Table 2 presents demographic profile.
Table 2
Respondents’ Profile
Variable Frequency (N=150) Percentage (%)
Gender
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Male 62 41.3
Female 88 58.7
Age
20 – 29 34 22.7
30 – 39 31 20.7
40 – 49 45 30.0
50 – 59 34 22.7
60 and above 6 4.0
Race
Malay 139 92.7
Chinese 4 2.7
India 3 2.0
Others 4 2.7
Duration Using Car
0-5 years 27 18.0
6-10 years 16 10.7
11-15 years 25 16.7
16 years above 82 54.7
Category of Car
Local Car 98 65.3
Import Car 52 34.7
To measure the relationship between each variable, the researcher conducted a correlation test.
Correlation examines the association between two metric variables (Hair et. al., 2007). It is measured by correlation coefficient. Table 3 shows the inter-correlations coefficients (r) values among variables.
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Table 3
Pearson Correlation Analysis
Continuance Intention to Use
Perceived Ease of Use
Safety of Driver
Attitude Perceived Usefulness Continuance
Intention to Use
1.00 Perceived Ease of
Use
0.602 1.00
Safety of Driver 0.433 0.393 1.00
Attitude 0.726 0.659 0.633 1.00
Perceived Usefulness
0.732 0.651 0.623 0.907 1.00
As shown in Table 3, all the correlation coefficients were statistically significant with strong and moderate correlations. The highest correlation is (r = 0.907), that is, between attitude and perceived usefulness, while the weakest correlation is (r = 0.393) between perceived ease of use and safety of the driver. Overall, the correlations between independent variables (perceived ease of use, safety driver, attitude, perceived usefulness) and dependent variable (continuance intention to use) have a positive relationship. For example, if attitude shows increases of value, then the value of continuance intention to use will also increase and vice versa.
CONCLUSION
The results showed that most of the respondents who were car drivers who have ever used AEB had moderate opinions about continuance intention to use automatic emergency braking (AEB). It is clear that the car drivers who have ever experienced using AEB intended to continue using it. This means the car drivers feel good when using the AEB in driving a car. Meanwhile, the result shows that the attitude factor is important on continuance intention to use an AEB system in Malaysia. It shows the car driver showed his good attitude towards the AEB system and had the intention to continue using it.
This attitude positively impacts on the use of this AEB system where it is likely to try to influence other drivers in the future. This is because advanced technologies are usually supported to greatly reduce the frequency and severity of road accidents. In order to encourage more car drivers to use this system, the government and also automotive manufacturers must cooperate and give full support in future planning. Provide awareness to the car drivers about the importance of the AEB system for the safety.
In conclusion, the AEB system functions as a vehicle safety technology. Adopting new innovation technologies in vehicles such as the AEB system for the drivers will positively impact during driving the vehicles. The technology can assist the driver from the crash and help them use the maximum capacity for the vehicle brake and avoid road accidents.
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ACKNOWLEDGMENT
This research provided no specific grant from any funding agency in the public, commercial, or not for profit sectors.
REFERENCES
Anwar, K., Kassim, A., Hashim, H. H., & Ilyas, R. (2017). Advancement in Vehicle Safety in Malaysia from Planning to Implementation. Asian Transport Studies, 4(4), 704–714.
Babbie, E. (2007). The Practice of Social Eesearch (11th ed.). Belmont, CA: Thompson Wadsworth.
Baharuddin, M. I., Khamis, N. K., Kassim, K. A. A., & Mansor, M. R. A. (2019). Autonomous Emergency Brake (AEB) for Pedestrian for ASEAN NCAP Safety Rating Consideration: A Review. Journal of the Society of Automotive Engineers Malaysia, 3(1), 63–73.
Bhattacherjee, A. (2001). Understanding Information Systems Continuance: An Expectation- Confirmation Mode. MIS Quarterly: Management Information Systems, 25, 351–370.
Cavana, R. Y., Delahaye, B. L., & Sekaran, U. (2000). Applied Research: Qualitative and Quantitative Methods. Sydney: John Wiley & Sons Inc.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly: Management Information Systems, 13(3), 319–339.
Duan, J., Li, R., Hou, L., Wang, W., Li, G., Li, S. E., Cheng, B., & Gao, H. (2017). Driver Braking Behavior Analysis to Improve Autonomous Emergency Braking Systems in Typical Chinese Vehicle-Bicycle Conflicts. Accident Analysis and Prevention, 108(August), 74–82.
Hair, J., Money, A., Page, M. & Samuouel, P. (2007). Research Methods for Business. Chichester, West Sussex: John Wiley & Sons Inc.
Hamid, U. Z. A., Zakuan, F. R. A., Zulkepli, K. A., Azmi, M. Z., Zamzuri, H., Rahman, M. A. A., &
Zakaria, M. A. (2017). Autonomous Emergency Braking System with Potential Field Risk Assessment for Frontal Collision Mitigation. Proceedings - 2017 IEEE Conference on Systems, Process and Control, ICSPC 2017, 2018-Janua(December), 71–76.
Ishanuddin, N.M. et al. (2021). Design and Implementation Content Validity Study: Development of an Instrument for Measuring Consumers’ Perception of Automatic Emergency Braking (AEB). In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2021.
Lecture Notes in Networks and Systems, vol 270. Springer, Cham.
Ishanuddin, N.M. et al. (2021). Consumers’ Perception of Automatic Emergency Braking (AEB):
Theoretical Model and Construct Development. Journal of the Society of Automotive Engineers Malaysia, 5(2): 205-222.
Kassim, K. A. A., Arokiasamy, L., Isa, M. H. M., & Osman, I. (2016). Automotive Consumerism towards Car Safety in Malaysia. Procedia - Social and Behavioral Sciences, 219, 424–430.
https://doi.org/10.1016/j.sbspro.2016.05.065
Kim, B. J., & Lee, S. B. (2020). A Study on the Evaluation Method of Autonomous Emergency Vehicle Braking for Pedestrians Test Using Monocular Cameras. Applied Sciences (Switzerland), 10(13), 1–15.
Chang, C. C. (2013). Exploring the Determinants of E-Learning Systems Continuance Intention in Academic Libraries. Library Management, 34(1), 40–55.
38
Koglbauer, I., Holzinger, J., Eichberger, A., & Lex, C. (2018). Autonomous Emergency Braking Systems Adapted to Snowy Road Conditions Improve Drivers’ Perceived Safety and Trust.
Traffic Injury Prevention, 19(3), 332–337.
Mantle‐Bromley, C. (1995). Positive Attitudes and Realistic Beliefs: Links to Proficiency. The Modern Language Journal, 79(3), 372–386.
Ministry of Transport. (2019). Transport Statistics Malaysia 2018.
https://www.mot.gov.my/en/Statistik Tahunan Pengangkutan/Transport Statistics Malaysia 2018.pdf
Mokhtar, N. H., Hamzah, L., Mamat, H. C., Nor, M. K. M., & Munir, F. A. (2019). Priority Factor Influencing Public Interest in Owning Vehicle with AEB System. Journal of the Society of Automotive Engineers Malaysia, 3(2), 139–147.
Morosan, C. (2012). Theoretical and Empirical Considerations of Guests Perceptions of Biometric Systems in Hotels: Extending the Technology Acceptance Model. Journal of Hospitality &
Tourism Research, 36(1), 52-84.
Nabavi, A., Taghavi-Fard, M. T., Hanafizadeh, P., & Taghva, M. R. (2016). Information Technology Continuance Intention: A Systematic Literature Review. International Journal of E-Business Research (IJEBR), 12(1), 58-95.
Nastjuk, I., Herrenkind, B., Marrone, M., Brendel, A. B., & Kolbe, L. M. (2020). What Drives the Acceptance of Autonomous Driving? An Investigation of Acceptance Factors From An End- User’s Perspective. Technological Forecasting and Social Change, 161(July), 120319.
https://doi.org/10.1016/j.techfore.2020.120319
Newstead, S., & Budd, L. (2020). The Potential Benefits of Autonomous Emergency Braking Systems in Australia (Issue September).
NCAP, A. (2017). ASEAN NCAP : http://www.aseancap.org/v2/wp-content/uploads/2018/04/ASEAN- NCAP_Towards-Autonomous-Seminar-Proc_2017.pdf
Osswald, S., Wurhofer, D., Trösterer, S., Beck, E., & Tscheligi, M. (2012). Predicting Information Technology Usage in the Car: Towards A Car Technology Acceptance Model. AutomotiveUI 2012 - 4th International Conference on Automotive User Interfaces and Interactive Vehicular Applications, In-Cooperation with ACM SIGCHI - Proceedings, January, 51–58.
https://doi.org/10.1145/2390256.2390264
Park, E. (2020). User acceptance of smart wearable devices: An Expectation-Confirmation Model
Approach. Telematics and Informatics, 47(November 2019).
https://doi.org/10.1016/j.tele.2019.101318
Payre, W., & Diels, C. (2020). I Want to Brake Free: The Effect of Connected Vehicle Features on Driver Behaviour, Usability and Acceptance. Applied Ergonomics, 82(June 2019), 102932.
Peter, J. P., & Olson, J. C. (2010). Consumer Behavior & Marketing Strategy (Ninth Edit). New York:
McGraw Hill. http://dinhtienminh.net/wp-content/uploads/2019/01/Peter-P-Olson-J-2010- Consumer-Behavior-9th-edn-McGraw-Hill-Full.pdf
Rahi, S., Ghani, M. A., & Alnaser, F. M. I. (2017). Predicting Customer’s Intentions to Use Internet Banking: The Role of Technology Acceptance Model (TAM) in E-Banking. Management Science Letters, 7(11), 513–524. https://doi.org/10.5267/j.msl.2017.8.004
Rahman, M. M., Lesch, M. F., Horrey, W. J., & Strawderman, L. (2017). Assessing the Utility of TAM, TPB, and UTAUT for Advanced Driver Assistance Systems. Accident Analysis and Prevention, 108(November), 361–373. https://doi.org/10.1016/j.aap.2017.09.011
39
Rani, M. F. H., Bakar, S. A., Hashim, M. S. M., Harun, A., & Razlan, Z. M. (2019). Calculating the Brake-Application Time of AEB System by Considering Maximum Deceleration Rate during a Primary Accident in Penang Urban Road. 3(3), 320–332.
Rouibah, K., Abbas, H., & Rouibah, S. (2011). Factors Affecting Camera Mobile Phone Adoption Before E-Shopping in the Arab World. Technology in Society, 33(3-4), 271-283.
Sharma, S., Flores, A., Hobbs, C., Stafford, J., & Fischmeister, S. (2019). Safety and Security Analysis of AEB for L4 Autonomous Vehicle Using STPA. OpenAccess Series in Informatics, 68(5), 1–5.
Song, Z., Cao, L., & Chou, C. (2020). Development of Test Equipment for Pedestrian-. 2018, 1–24.
Stave, C., & Strand, N. (2015). Drivers knowledge and learning of advanced driver assistance systems.
ITS World Congress 2015, Paper Number ITS-1338, October, 5–9.
Syafiq, M., & Mohamed, S. (2017). Original Article Malaysian Drivers Perception Towards Advanced Driver Assistance Systems ( Adas ). 2(2), 15–20.
Tan, H., Zhao, F., Hao, H., Liu, Z., Amer, A. A., & Babiker, H. (2020). Automatic Emergency Braking (AEB) System Impact on Fatality and Injury Reduction in China. International Journal of Environmental Research and Public Health, 17(3).
Voinea, G. D., Postelnicu, C. C., Duguleana, M., Mogan, G. L., & Socianu, R. (2020). Driving Performance and Technology Acceptance Evaluation in Real Traffic of a Smartphone-Based Driver Assistance System. International Journal of Environmental Research and Public Health, 17(19), 1–20. https://doi.org/10.3390/ijerph17197098
Weng, F., Yang, R. J., Ho, H. J., & Su, H. M. (2018). A TAM-Based Study of the Attitude Towards Use Intention of Multimedia Among School Teachers. Applied System Innovation, 1(3), 1–9.
https://doi.org/10.3390/asi1030036
Wu, J. H., Shen, W. S., Lin, L. M., Greenes, R. A., & Bates, D. W. (2008). Testing the Technology Acceptance Model for Evaluating Healthcare Professionals’ Intention to Use An Adverse Event Reporting System. International Journal for Quality in Health Care, 20(2), 123–129.
https://doi.org/10.1093/intqhc/mzm074
Yousafzai, S. Y., Foxall, G. R., & Pallister, J. G. (2007). Technology Acceptance: A Meta-Analysis of the TAM: Part 1. Journal of Modelling in Management, 2(3), 251–280.
