A Comprehensive Review: Multisensory and Cross-Cultural Approaches to Driver Emotion Modulation in Vehicle Systems

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Featured Application: This study will focus on enhancing vehicle design by integrating advanced multisensory and culturally adaptive emotion modulation systems to meet the diverse needs of drivers globally and improve overall driving safety.

Abstract

Road accidents are caused by multiple factors. Aggressive driving and traffic violations account for 74% of road traffic accidents. In total, 92% of fatalities occur in low- and middle-income countries. Drivers’ emotions significantly influence driving performance, making emotional modulation critical during vehicle interaction. With the rise of smart vehicles, in-vehicle affective computing and human-centered design have gained importance. This review analyzes 802 studies related to driver emotional regulation, focusing on 74 studies regarding sensory stimuli and cultural contexts. The results show that single-sensory methods dominate, yet multisensory approaches using auditory and visual elements are more effective. Most studies overlook cultural factors, particularly the differences in East–West cultural values, indicating a need to tailor modulation methods based on cultural preferences. Designs must emphasize adaptability and cultural consistency. This review aims to analyze driver emotional modulation thoroughly, providing key insights for developing vehicle systems that meet the diverse emotional and cultural needs of global drivers. Future research should focus on creating multisensory emotional modulation systems that offer positive reinforcement without causing excessive relaxation or aggression, accommodating subtle cultural and individual differences, thus enhancing the safety of autonomous driving.

1. Introduction

The World Health Organization reports 1.25 million deaths globally from vehicle accidents every year. In total, 92% of global road traffic fatalities occur in low- and middle-income countries, despite these nations accounting for roughly 60% of the world’s vehicles. Road traffic accidents result in a loss of approximately 3% of gross domestic product for most countries. According to the Global Status Report on Road Safety 2023 [1], there are significant variations in mortality rates from road traffic incidents across different regions. Among the World Health Organization’s six regions (the African region, European region, Americas, Eastern Mediterranean, South East Asia, and Western Pacific region), four regions have seen a decline in fatalities among vehicle occupants, whereas the Eastern Mediterranean region has experienced an 11% increase in deaths, and the European region has remained unchanged.

Previous research indicates that one cause of vehicle accidents is aggressive driving behavior [2]. Studies show that anger negatively impacts driving ability and encourages hazardous actions such as traffic violations, lane changes, high speeds, and crashes. Moreover, aggressive driving and traffic offenses contribute to 74% of traffic accidents [3]. The European Commission is promoting the shift from Industry 4.0 to human-centered Industry 5.0, and advancements in sensor technologies now make emotional interactions feasible within autonomous vehicles [4,5,6]. There is an increasing number of emotion recognition sensors being integrated into vehicles [7]. In-vehicle affective interaction can perceive and understand human behavior, and implement corresponding strategies to reduce the occurrence of accidents [5,8]. Advancements in artificial intelligence and in-vehicle sensors are driving efforts in affective computing and shaping human-centered design as the future of autonomous vehicles [9,10,11]. The rapid development of in-vehicle sensor technologies means in-vehicle emotional systems can effectively address the psychological and behavioral aspects of occupants, ensuring road safety [12,13].

According to previous studies on the relationship between drivers’ emotions and driving performance, reference [14] indicated that negative emotions in drivers can adversely affect overall driving performance. Therefore, many scholars have approached driver emotion modulation through human senses. For example, some scholars consider the use of interactions involving light with subliminal cues as a positive way to regulate drivers’ emotions [15]. Other scholars measure changes in aggressive driving behavior through the demand on the sensory channels involved (visual, auditory, and olfactory senses) [16,17]. Simultaneously, some studies have suggested that emotions evoked by music can accelerate speed, whereas anger induced by visual stimuli tends to decrease speed [18,19]. Ref. [20] found that cold temperatures and psychological stress elevate driving risks. Ref. [21] also mention that olfactory factors can influence driving performance. Due to the rapid changes in driving scenarios, some studies highlight that multisensory driver emotion modulation is more effective [22]. Human-centered design, key to ergonomics, simplifies complex driving environments and enhances interactions and responses to psychological, emotional, and social driving challenges [23].

Human-centered in-vehicle interaction also significantly focuses on the cross-cultural characteristics of user groups. Cross-cultural adaptation in vehicles facilitates understanding human cultures and emotional driving styles, aiding in the development of emotional driving strategies to regulate drivers’ emotions [11]. According to [24], age, gender, and cultural and regional differences affect driver behaviors. Research indicates that to ensure the driver sample accurately represents the overall driver population of a specific region or country, the selection process must include drivers of varying ages, genders, and driving experience [25]. Furthermore, integrating the theory presented in [26], we can attribute drivers’ emotional responses to cultural value differences associated with their geographical regions, such as the collectivist tendencies observed in Asian countries. This literature aids our understanding of emotional modulation patterns and strategies within diverse cultural contexts. Different cultural values and traffic environments affect driving styles, and emotional changes can also affect driver behaviors [27]. Hence, there is a definite link between driver behaviors and cross-cultural factors that influence driver aggression.

Previous studies have focused on driver emotion recognition, identifying emotions through physiological measurements [28,29,30,31,32,33,34,35,36]. Algorithms such as K-nearest neighbors, deep neural networks, and convolutional neural networks have achieved accuracy rates exceeding 90%. However, few studies have approached this topic from a human-centered perspective, examining drivers’ senses, behaviors, and emotion modulation, as well as their interaction modes with vehicles. Moreover, few studies have explored driver emotion modulation methods and their effectiveness from a cross-cultural perspective. To summarize the findings of existing studies, we analyzed driver behavior and driver emotion modulation from a human-centered perspective by conducting a review of the scientific literature. The three specific objectives of this review are as follows:

• Correlate the evidence on drivers’ emotions and behaviors during the driving process: Analyze driving behaviors under various emotional states. Assess the impact of different emotional conditions and driving behaviors on the risk of road accidents.
• Examine the impact of driver emotion modulation methods on drivers’ emotions based on unisensory and multisensory inputs: Evaluate the effects of single-sensory stimuli, such as auditory and visual inputs, on drivers’ emotional regulation. Use psychological questionnaires, physiological metrics, or neural activity as assessment tools. Assess the outcomes of multisensory stimuli, specifically the combination of auditory and visual elements, on emotional regulation. Compare the differences between single-sensory and multisensory approaches. Analyze emotional state variations using pre- and post-intervention measurements.
• Identify driver emotion modulation from a cross-cultural adaptation perspective: Examine the effectiveness of emotional regulation methods across diverse cultural contexts. Analyze whether emotional regulation strategies, such as cognitive reappraisal, emotional expression, and sensory input, require adaptation in various cultural settings. Employ experimental findings and statistical analyses as evaluative criteria.

2. Methods

2.1. Information Retrieval Tactics and Eligibility Criteria

A flow chart of the literature review is shown in Figure 1, consistent with the recommendations of the European Commission (Research and Artificial Intelligence—Digital Strategy) [37]. We collected relevant articles for this review based on the following:

• Articles were published after 2018, with most published within the past five years, and some found from the list of references in the relevant literature.
• Articles were selected by conducting literature searches in Web of Science, Scopus, and Google Scholar.
• The following keywords were used for the literature search: “driver emotion modulation”, “driver emotion regulation”, “driver behavior”, “driver style”, “driver safety”, “driver emotion”, and “cross-cultural impact on driving emotion”.
• The search strategies were compiled and the literature search was conducted using the Boolean operators “AND” and “OR”, such that “driver emotion” AND “modulation” OR “cross-cultural impact” were used in the search engine.
• The findings from the literature search were examined. The Web of Science database returned 380 articles, while the Scopus databases returned 460 articles.
• Articles obtained from the Web of Science and Scopus databases were combined. Articles were collected using CiteSpace-6.3.1 software, which eliminates irrelevant references and duplicates. The number of articles was reduced from 840 to 802.

2.2. Data Analysis

We conducted two types of data analysis: (1) overall findings and (2) specific findings. Each type is described below.

• Analysis of overall findings: The data trends from the 802 articles were visualized using CiteSpace software. The procedure for data analysis is described below. First, we keyed the full records in plain-text format into CiteSpace software. Next, we set the parameters, including time slicing, year span (from 2018 to 2023), and years per slice (1 year) for country and keyword analyses. We then employed the CiteSpace software and obtained the networks and data, obtaining the countries and keywords. We also obtained the data of grants used to cluster the keywords and countries. Finally, we conducted keyword co-occurrence analysis and presented the visualization results. We set a g-index of 20 (k = 20) to ensure the selected literature demonstrated significant citation impact while controlling for node numbers to exclude irrelevant articles. A higher g-index indicates greater influence of the literature within the citation network. However, a higher g-index increases the number of nodes, indicating more irrelevant literature [38]. We excluded articles with low citations, minor influence, and limited clustering relevance, allowing for a focused analysis of works that make substantial contributions to the field. The number of articles selected after screening of the most relevant articles and keywords was 277.
• Analysis of specific findings: These 277 articles were then assessed by two reviewers to identify the articles with the most relevant themes along with supplementary content from Google Scholar. The articles were reviewed by two independent reviewers who are not co-authors of this manuscript to avoid any potential bias. The reviewers are experts in automotive technology studies. At this stage, each result was reviewed, and the search results were refined by retaining articles related to driver behavior and emotion regulation, cross-cultural adaptation, and sensory input in driver emotion modulation. The criteria for excluding articles included the following: relevance to the research questions and objectives; methodological rigor and quality of the data; and a high impact factor of the journals to ensure credibility. Each full text was evaluated based on the exclusion criteria shown in Figure 1. It was ensured that the selected literature not only had a high impact in terms of citations, but was also closely related to our research topic. The remaining articles after peer review were categorized as follows: (1) driver emotion and behavior (13 articles), driver emotion modulation based on unisensory and multisensory inputs (34 articles), and cross-cultural impact on drivers’ emotions (27 articles).

3. Results

3.1. Overall Findings

There is an increasing trend in the number of publications related to driver emotion modulation or driver emotion regulation from 2018 to 2023, as shown in Figure 2. We analyzed 802 articles obtained from the Web of Science and Scopus databases using CiteSpace software. Based on the findings, most of the relevant studies are from China, the United States, Germany, and India, as shown in Figure 3. The United States (n = 147) has the highest number of publications, followed by China (n = 127), Germany (n = 107), and India (n = 63). This indicates an increasing trend in research programs in China and the United States. In contrast, the number of relevant studies in Germany was highest in 2018, followed by a decline.

The results of the keyword co-occurrence analysis are shown in Figure 4. There is a gradual increasing trend for the combination of the “driver emotion” and “artificial intelligence” keywords. From a temporal perspective, the dark red color represents a time closer to the present, indicating that research on drivers’ emotions gradually shifted from driver behavior in 2018 to emotion regulation in 2020. Research became more prevalent from 2019 to 2020, gradually focusing on in-vehicle emotion regulation. In 2022, there was an increase in the number of studies pertaining to the integration of artificial intelligence for in-vehicle monitoring. After keyword clustering, there are six clusters: (1) user experience, (2) driver distraction, (3) emotional intelligence, (4) driver emotion regulation, (5) in-vehicle frustration, and (6) autonomous vehicles.

The six key clusters can be organized into three distinct groups, each emphasizing different aspects of the driving experience and their impact on emotion modulation. The first group, drivers’ emotional and behavioral factors, focuses on emotional intelligence and driver emotion regulation, emphasizing the importance of managing emotions for behavioral decision-making and composure under stress, which directly affects driving safety. The second group, driver emotion modulation based on human sensory perception, includes user experience and driver distraction. This group analyzes how interaction with the vehicle through sensory inputs impacts drivers’ emotional states and attentiveness. A well-designed user experience reduces stress and the potential for accidents. The third group, driver emotion modulation related to cross-cultural backgrounds and driver personality, addresses in-vehicle frustration and the impact of autonomous vehicles. It considers how personal and cultural differences affect drivers’ emotional responses and interactions with autonomous technologies. This is essential for creating adaptable systems for diverse global populations, thereby enhancing both user experience and safety.

3.2. Specific Findings

By integrating the literature found using CiteSpace with some extended terms, we summarized the relevant studies in detail. The studies were organized into three categories: (1) drivers’ emotional and behavioral factors, (2) driver emotion modulation based on human sensory perception, and (3) driver emotion modulation related to cross-cultural backgrounds and driver personality. We also discuss the key factors of human-centered emotion modulation for smart vehicle drivers. The summary includes the effects of different emotional factors on driver behaviors, the application of intelligent sensors in recognizing human emotions, and the effectiveness of human-centered emotion modulation.

3.2.1. Driver Emotion and Behavior

Here, we summarize 13 studies related to the types of emotions experienced by drivers, the behavioral factors of drivers, associated risks factors, and cultural and human factors, as shown in

Table 1. Summary of studies related to driver emotion and behavior.

Reference	Driver Emotion(s)	Driver Behavior(s)	Road Accident Factor	Cultural Factor	Human Factor
[39]	anger and pleasure; surprise and fear	risky driving behaviors; opposite	driving style and sensory seeking	SN	—
[40]	anger, anxiety, and frustration	aggressive driving	distress tolerance ↓	—	PC
[7]	anger and anxiety	steering wheel angle increasing	driving pressure ↑	—	PC
[41]	angry and fear	anxiety driving	arrival-blocking	—	EI
[42]	anxiety	aggressive driving, continuous honks	road rage	—	PC
[43]	anger	high speed; short following distance and aggressive behavior	risk-taking driving ↑	SN	—
[44]	negative emotion, contempt	aggressive driving	speeding ↑	—	—
[45]	negative emotion	deceleration increase	conservative driving decision	SN	—
[18]	negative emotion	increasing speed	distracted attention	—	—
[46]	anger and frustration	aggressive driving	deliberate infringements	—	—
[47]	—	driving attention	risky driving attitude	SN	EI
[48]	negative emotion	weaving in and out of lanes	reckless behavior	SN	—
[49]	—	driving attention	risky driving	SN	—

Note: EI: emotional intelligence; SN: social norm; PC: personal characteristic; ↓: decrease; ↑: increase.

.

Based on the literature search, it can be deduced that the majority of studies focus on anger within the category of negative emotions (n = 11, 85%). Reference [39] mentioned that pleasure can also lead to dangerous driving behaviors. Meanwhile, ref. [46] pointed out that the anger resulting from frustration and threats increases the frequency of intentional driving infringements. Two of the studies (n = 2, 15%) [47,49] did not specify the emotions researched but included aspects of personality and attitudes.

Causes of traffic accidents: Several studies [18,42,43] mentioned that aggressive driving behavior, such as continuous honking and speeding, significantly increases the risk of road accidents. Risk-taking driving behaviors like high speed, short following distances, and deliberate infringements are often associated with aggressive driving styles. Also, refs. [7,40] reported that anxiety while driving can lead to behaviors that block arrival and increase the driving pressure. Reduced distress tolerance can contribute to aggressive driving, raising the likelihood of accidents. Additionally, refs. [18,46] indicated that distracted attention, indicated by increased speed or weaving in and out of lanes, leads to reckless behavior and heightens the risk of accidents. Risky driving attitudes, such as taking unnecessary risks and not paying attention to road conditions, can result in dangerous driving situations. Reference [45] mentioned that sensory seeking behaviors and increased steering wheel angles can elevate driving pressure, making it more challenging to maintain control and increasing accident risks.

Driver behavior: The literature indicates that negative emotions enhance risky behaviors and deteriorate driving performance (n = 10, 77%). Although anger can lead to aggressive driving behaviors, it does not increase the frequency of errors. Anger driven by threats, contempt, and frustration particularly increases the frequency of intentional violations (n = 4, 31%) [7,39,44,46]. From 2018 to 2024, there was increasing emphasis on how human emotional intelligence and personal characteristics influence drivers’ emotions, highlighting the importance of human factors (n = 5, 35.71%) [7,40,41,42,47].

Impact of personal characteristics on emotions and driving behavior: A literature survey by Steinhauser and Leist [18] found that conservative thinking leads to more traffic accidents. This study suggests that conservative decisions, influenced by negative emotions, do not necessarily result in safer driving behaviors. Additionally, sensory input can also affect the level of anger and thus influence driver behavior [48]. For example, music-induced anger can cause drivers to speed up, while visual input can cause drivers to slow down because it distracts them. Shamoa-Nir [42] emphasized the importance of emotional intelligence in driving across different cultural settings, highlighting the association between anger, aggressiveness, and risky driving behaviors. Anxiety can reduce driving performance and promote caution, while sadness and depression, especially when accompanied by rumination, can diminish driving performance due to self-focus.

A number of studies (n = 6, 42.85%) [39,43,45,47,48,49] indicate that cultural background, especially social norms, is a significant factor influencing driver behaviors. Although [45], who conducted their study in China, do not explicitly state how culture influences driver behaviors, they suggest that cultural factors impact driver behaviors, and particularly, describe how emotional responses can vary and affect driving safety. One study in Bangkok, Thailand, by [43], posits that culture influences driver behaviors, such as attitudes toward traffic safety and social norms, which might impact driver behaviors.

Since the emotional state of drivers has been identified as a factor contributing to driving risks, it is essential to modulate drivers’ emotions. At present, some sensors have been developed for intelligent vehicles to identify drivers’ emotions through affective computing. Using a human-centered approach to effectively modulate drivers’ emotions, driving safety can be improved [50].

3.2.2. Driver Emotion Modulation Based on Unisensory and Multisensory Inputs

With the proliferation of intelligent sensors, there is an increasing number of studies related to the use of sensors for emotion recognition. However, to promote driving safety, integrating artificial intelligence with human intervention is still essential [51]. We reviewed 34 articles on driver emotion modulation based on unisensory and multisensory inputs, as summarized in

Table 2. Summary of studies related to driver emotion modulation based on unisensory and multisensory inputs.

Reference	Sensory Input(s)	Driver Emotion(s)	Driving Performance	Measurement	Effectiveness of Driver Emotion Modulation	Cultural Factors	Human Factors
[52]	haptic, vocal	calmness	DP ↓	BR, HR	reduced drivers’ breathing rate and level of arousal; safety and driving performance were not impaired; drivers preferred haptic stimulation over voice	—	cognition
[53]	haptic	stress	PR ↓	BR, HR, PR	haptic breathing guidance could increase both the rate and intensity of breathing as well as heart rate; all participants (except two) stated that haptic breathing guidance intervention was safe, provided that it was not delivered in inappropriate scenarios	attitudes	individual differences
[54]	haptic	stress	DP ↓	SCR, HR, BR, ET	haptic guidance could effectively regulate breathing rate, increasing comfort; however, haptic guidance was not useful in complex maneuvers	—	behavior
[55]	visual	negative, positive, calmness	LE ↑	speed	pleasant images degraded longitudinal control to the greatest extent	—	individual differences
[56]	visual	negative, positive	DP ↓	speed	intersection type and position influenced drivers’ emotional states	—	behavior
[57]	visual	negative	DP ↓	PR	both blue and orange lighting enhanced lane maintenance for drivers	—	behavior
[58]	visual	negative	DP ↓	EEG	cool hues had better regulation quality than warm hues for color attributes; positive expression had better outcomes than negative expression for expression attributes	diverse user interactions	behavior
[11]	visual, vocal, temperature	negative	DP ↓	PR	unexpected sounds generally had a negative effect; ambient lighting could be alarming or distracting, but also calming, depending on its brightness, position, and personal familiarity with it; empathetic voice interaction proved effective in enhancing driver focus and providing empathy during negative emotional states	culturally sensitive design	individual differences
[59]	visual, vocal	negative	DP ↓	gesture	audio feedback was great; feedback was great; distraction came from “dislikes” on the road	—	individual differences
[15]	visual, vocal	negative	DP ↓	strategies	the following factors influenced the positive emotions of the participants: (1) ambient lighting (28.3%), (2) visual notification (20%), empathetic assistant (15%)	—	cognition
[60]	vocal	negative	DP ↓	PR	participants in the reappraisal-down condition had better driving behaviors and reported less negative emotions	—	cognition
[61]	vocal	negative	PR ↓	PR	voice assistant, navigating the driver through complex menus	—	behavior
[62]	vocal	negative	DP ↓	PR, behavior	self-selected music encouraged aggression; sad music boosted heart rates	—	cognition
[63]	vocal	negative	DP ↓	HR	music with specific tempos or familiarity significantly improved driving performance	—	behavior
[64]	vocal	negative	DP ↓	ER	self-selected music resulted in less frustration	—	individual differences
[65]	vocal	negative, positive	DP ↓	scale	music had a positive effect, whereby it increased drivers’ caution	—	behavior
[66]	vocal	negative	PR ↓	scale	low-activation music could reduce systolic reactivity	—	behavior
[67]	vocal	stress	trust ↓	scale	submissive voice increased emotion regulation	—	behavior
[68]	vocal	negative	DP ↓	EEG	automatic adjustment of music in response to drivers’ mood could reduce traffic accidents	—	—
[69]	vocal	negative	DP ↓	ER	positive comments were more effective in reducing drivers’ anger state and perceived workload, and in improving driving performance	—	behavior
[70]	vocal	negative	DP ↓	PR	angry speech improved reaction times	—	cognition
[71]	vocal	negative	DP ↓	scale	warnings associated with the environment worked best	—	behavior
[17]	vocal	stress	DP ↓	scale	conscious audio interventions increased the number of driving mistakes; audio interventions need to be tailored according to driver’s personality	—	personality
[72]	vocal	negative	DP ↓	behavior	personalized speech can curb angry behavior and lower driving risks	—	cognition
[29]	vocal	negative	DP ↓	EEG	music or reports could affect negative emotions	—	cognition
[73]	vocal	negative, positive	DP ↓	behavior, PR	customized personal music was more effective in regulating emotions	cultural background	personality
[74]	vocal	negative	DP ↓	scale	noise levels increased; annoyance linearly increased; 55 dB(A) was the best environmental noise level for cognitive efficiency in cognitive tasks	—	cognition
[75]	cooling	negative	DP ↓	scale	85% of drivers liked cooling, which they all believed reduced fatigue, and 91% preferred it during monotonous driving	—	behavior
[76]	olfactory	negative	DP ↓	scale	rose scent relaxed drivers; peppermint increased alertness but caused more lane deviations; unpleasant scents led to more collisions	—	—
[77]	olfactory	negative	DP ↓	visual	peppermint scent was effective in alerting drivers to drowsy driving	—	behavior
[78]	olfactory, visual	negative	DP ↓	LE, speed	olfactory notifications resulted in significantly slower driving	—	cognition
[79]	olfactory	negative	DP ↓	scale	olfactory notifications were less distracting and more effective than visual ones	—	behavior
[80]	olfactory	negative	DP ↓	ECG, PPG, RESP	agarwood had the best effect, followed by sweet orange, with lavender being the least effective	—	cognition
[81]	reappraisal	negative	DP ↓	scale	drivers with fewer offenses habitually adopted more adaptive driving styles and emotion modulation strategies	—	individual differences

Note: DP: driving performance; PR: physiological response; LE: lane excursion; BR: breathing rate; HR: heart rate; ER: error rate; SCR: skin conductance response; ET: eye tracking; ↓: decrease; ↑: increase.

. The analysis was performed from various viewpoints, including sensory aspects, emotional factors, driving performance, the effects of driver emotion modulation, cultural factors, and human factors.

From a sensory perspective, the primary modalities explored in driver emotion modulation include haptic (n = 3, 9%), vocal (n = 21, 62%), visual (n = 8, 24%), temperature (n = 2, 6%), and olfactory (n = 5, 14%) stimulation. Among these studies, several studies focus on unisensory methods (n = 29, 85%), and a few examine multisensory methods (n = 5, 15%). Voice modulation used speech and music. Visual adjustments utilized images or ambient lighting. In addition, some studies incorporated cognitive methods for emotion modulation.

From an emotional standpoint, most studies focus on modulating negative emotions (n = 29, 6%), while some scholars [17,52,53,55,56,65,67] mention that positive emotions and stress also require modulation because it can increase arousal due to increased speed. Consistent with previous analyses, the influenced behaviors include driving performance (n = 29, 85%), such as improved speed control, decreased driving errors and lane excursions [55], and improved driving performance resulting from physiological changes [53,66].

Haptic assistance: Ref. [59] demonstrated that driver emotion modulation generally reduces stress and aggressive driving behaviors among drivers. From a tactile perspective, refs. [52,53] found that haptic feedback not only effectively reduces stress, but is also preferred by drivers. Notably, ref. [54] mentioned that haptic feedback can increase both the rate and intensity of breathing, as well as heart rate; most participants considered the haptic breathing guidance intervention safe, provided it was not used in inappropriate scenarios.

Visual assistance: From a visual viewpoint, refs. [56,57,58,59] reported that exposure to pleasant images and colors, such as cool blue and warm orange, leads to slower mean driving speeds, whereas unpleasant images correlate with a higher frequency of lane excursions. Refs. [11,15,82] confirmed that positive expressions yielded better outcomes than negative ones in terms of expression attributes. Additionally, ref. [59] found that distractions were primarily caused by ‘dislikes’ encountered on the road and that ambient lighting also played a role.

From an auditory perspective, the modulation effects are twofold, involving speech and music. Empirical evidence suggests that strategies using voices and empathetic assistants are most effective in improving negative emotional states [15,59,61,72]. Compared with a dominant voice, a submissive voice tends to better influence driving modes and trust [60,67]. Positive comments can also reduce a driver’s state of anger, thereby enhancing driving performance [69,71]. Conversely, angry speech tends to increase reaction times, likely by activating the right frontoparietal networks and reducing activity in the left frontal area [17,70]. In addition, studies have shown that music, especially self-selected music, can potentially mitigate anger [62,63,66,68]. Low-activation music reduces systolic reactivity and influences cardiovascular responses, moderating the cardiovascular correlates of negative moods [29,73]. Ref. [74] also demonstrated that selecting the optimal decibel level in the car can effectively reduce drivers’ negative emotions.

From an olfactory standpoint, olfactory notifications are less distracting and more helpful than visual ones, with scents like rose and peppermint improving drivers’ mood and behavior [76,77]. Conversely, ref. [78] reported that unpleasant scents can worsen driving performance, while clean air has a neutral effect. Ref. [79] also indicated that olfactory cues were more effective than visual ones. Furthermore, ref. [80] examined the effects of three olfactory stimulants (lavender, sweet orange, and agarwood) on negative emotions. Their results indicate that agarwood has the best regulatory effect on negative emotions, followed by sweet orange, with lavender being the least effective.

From a temperature viewpoint, comfort levels are partially dependent on the duration of cooling. Ref. [75] mentioned that longer cooling duration has been shown to effectively reduce passive fatigue, as evidenced by changes in physiological measures such as heart rate variability and skin temperature. However, ref. [11] summarized that cooling can also result in a subjective reduction in feelings of fatigue, which may lead drivers to prefer more stimulating driving experiences.

Most of the included studies do not mention how cultural factors influence the emotion modulation process, with only a few articles highlighting the need for culturally sensitive design (n = 4, 12%) [11,53,73,82]. From a human factor perspective, several studies have pointed out that individual differences affect driving style and, thus, the effectiveness of driver emotion regulation [11,53,55,59,64,81]. Moreover, studies indicate that sensory-based driver emotion modulation can alter human cognition, influencing modulation outcomes [4,52,62,74,80]. Meanwhile, refs. [71,75,77,79] observed that that physiological differences resulting from emotion regulation can also affect driver behavior.

Based on the literature survey, it is evident that individual differences play a vital role in emotion modulation strategies for drivers. It is worth noting that human cognition can effectively reduce negative emotions and enhance driving performance. This suggests the potential benefits of improving physiological sensing to enhance in-vehicle user experience. Hence, there is a serious need to strengthen communication between humans and in-vehicle systems and to better manage attention allocation while driving.

3.2.3. Cross-Cultural Impact on Drivers’ Emotions

We reviewed 27 articles on the cross-cultural impact on drivers’ emotions, as summarized in Table 3, drawing insights from the perspectives of drivers from various cultural backgrounds. Most participants are young adults, with 10 of the studies (37.03%) involving college students. The participants hail from China (n = 12, 44.44%), the United States of America (n = 13, 48.14%), Germany (n = 2, 7.4%), Malaysia (n = 1, 3.7%), Japan (n = 4, 14.81%), and India (n = 4, 14.81%). Hence, this review contrasts the cross-cultural impact on drivers’ emotions between Asian and European participants. In addition, multicultural countries like Singapore (n = 2, 7.4%) and Malaysia (n = 3, 11.11%) are also included, emphasizing the diversity in cultural backgrounds among the study populations. The results are divided into 5 regions based on cultural context: Asia and the Middle East, Europe, America, Oceania, and others.

Most of the studies related to the cross-cultural impact on drivers’ emotions originate from the field of social science (n = 16, 59.26%), with a smaller proportion directly related to driving (n = 11, 40.74%). Two studies [8,11] also highlight the need to consider cultural attitudes in the use of technology while driving. This is an area for future exploration, emphasizing the importance of culturally sensitive design in autonomous driving technologies and driver assistance systems [83,84].

Table 3. Summary of studies related to cross-cultural impact on drivers’ emotions.

Reference	Participants	Number of Participants	Description of Participants	Method	Findings of Driver Emotion Modulation	Human Factor(s)
[85]	students	560	Netherlands and China	visual	Chinese participants perceived smaller differences between intended and unintended emotions	visual
[86]	students	416	46 European Americans, 33 Asian Americans, 91 Japanese, 160 Indians, and 80 Hispanics	reappraisal	cultural differences emerged for nearly all discrete emotions	physiological
[87]	students	80	40 from UK, 40 East Asians	reappraisal	UK drivers were more capable of regulating negative emotions elicited by social exclusion	physiological
[88]	general population samples	1735	593, 602, and 540 participants recruited from China, Italy, and Spain, respectively	reappraisal, expressive	acceptance and reappraisal were predictive of higher well-being; rumination and suppression were predictive of lower well-being	physiological
[89]	students	765	334 Chinese, 431 Germans	reappraisal	Collectivistic and individualistic differences in cognitive reappraisal led to fewer behavioral problems	physiological
[90]	students	103	64 females, 39 males	reappraisal	there was a curvilinear relationship between cultural dissimilarity and individual performance	physiological
[91]	young adults	84	40 Asian Americans, 44 Caucasian Americans	reappraisal	Asian American participants had fewer fixations on emotionally salient areas	physiological
[92]	students	86	48 East Asians, 38 Western Europeans	reappraisal	the East Asian populations could regulate emotions more effectively through specific strategies, especially under stress	physiological
[93]	adults	72	29 Japanese adults, 43 from United Kingdom	social norms	Japanese participants had greater difficulty with emotional self-awareness and emotional intensity differentiation	physiological
[94]	Chinese–English bilinguals	41	United States of America	visual, auditory	Western participants were more distracted by visuals, and Eastern ones by sounds	visual, vocal
[95]	younger adults	36	20 Japanese, 16 Dutch	visual, auditory	Japanese participants were more attuned to vocal processing in the multisensory perception of emotion than Dutch participants	visual, vocal
[96]	workers	511	231 Chinese, 280 Americans	cultural experiences	expression of emotions was more direct in the United States	physiological
[97]	students	>400	Chinese and American	cultural experiences	Chinese men reported relatively low levels of emotion; American women reported relatively high levels of emotion	—
[98]	students	85	46 students from a university in the United States of America, 39 students from two universities in India	cultural experiences	the students from India adapted more to situations; the students from the United States of America perceived situations as more influential on their emotions	—
[99]	native speakers	30	China, United States of America, and Singapore	visual, auditory	Chinese participants showed greater auditory modality bias, while American participants showed greater visual modality bias	visual, vocal
[100]	adults	108	51 and 57 participants recruited from India and United States of America, respectively	reappraisal	participants from India were more prone to using cognitive reappraisal for high-intensity negative stimuli compared with participants from the United States of America	physiological
[101]	adults aged 40 years	102	Chinese, German, and English	cultural experiences	improved usability and accessibility	visual
[102]	drivers (over 18 years)	620	Australia and China	cultural experiences	Chinese drivers preferred symbols over words	visual
[103]	younger drivers	—	China, United States of America, Australia, and New Zealand	cultural experiences	better emotional regulation	visual
[104]	drivers (aged 20–60 years)	70	South Korea and Canada	cultural experiences	differences in ethical decision-making in the face of dilemmas	physiological
[105]	drivers	561	Italian, Argentine, Romanian, Chinese, Malaysian, Dutch, and Belgian participants	social norms	driving style assessment could influence driver emotion modulation	physiological, driving style
[106]	drivers	823	287, 329, and 207 participants recruited from Israel, Turkey, and United States of America, respectively	behavior	emotion modulation difficulties influenced forgiveness and driving styles differently across cultures	driving style
[107]	drivers	187	92 participants recruited from United Kingdom (21 males, 71 females), 95 participants recruited from Malaysia (33 males, 62 females)	visual	visual search of the environment while driving influences information processing and situational awareness	visual, driving style
[108]	drivers	118	32 Chinese, 35 Indians, 44 Americans, 7 participants recruited from other countries	cultural experiences	higher-context cultures exhibited greater trust and preference	physiological
[24]	drivers	30	Malaysia	cultural experiences	social/cultural factors led to more frequent and aggressive steering in local drivers compared to foreign ones	behavioral
[109]	road users	500	187 Singaporeans, 313 Malaysians	social norms	higher traffic risk perception and willingness	physiological
[27]	drivers	—	participants recruited from Egypt, United Kingdom, India, China, Japan, and the United States of America	social norms	the level of aggression or patience in driving could be influenced by societal attitudes toward traffic rules and interpersonal interactions on the road	physiological

Note: —: the numbers are not mentioned.

Table 3. Summary of studies related to cross-cultural impact on drivers’ emotions.

Reference	Participants	Number of Participants	Description of Participants	Method	Findings of Driver Emotion Modulation	Human Factor(s)
[85]	students	560	Netherlands and China	visual	Chinese participants perceived smaller differences between intended and unintended emotions	visual
[86]	students	416	46 European Americans, 33 Asian Americans, 91 Japanese, 160 Indians, and 80 Hispanics	reappraisal	cultural differences emerged for nearly all discrete emotions	physiological
[87]	students	80	40 from UK, 40 East Asians	reappraisal	UK drivers were more capable of regulating negative emotions elicited by social exclusion	physiological
[88]	general population samples	1735	593, 602, and 540 participants recruited from China, Italy, and Spain, respectively	reappraisal, expressive	acceptance and reappraisal were predictive of higher well-being; rumination and suppression were predictive of lower well-being	physiological
[89]	students	765	334 Chinese, 431 Germans	reappraisal	Collectivistic and individualistic differences in cognitive reappraisal led to fewer behavioral problems	physiological
[90]	students	103	64 females, 39 males	reappraisal	there was a curvilinear relationship between cultural dissimilarity and individual performance	physiological
[91]	young adults	84	40 Asian Americans, 44 Caucasian Americans	reappraisal	Asian American participants had fewer fixations on emotionally salient areas	physiological
[92]	students	86	48 East Asians, 38 Western Europeans	reappraisal	the East Asian populations could regulate emotions more effectively through specific strategies, especially under stress	physiological
[93]	adults	72	29 Japanese adults, 43 from United Kingdom	social norms	Japanese participants had greater difficulty with emotional self-awareness and emotional intensity differentiation	physiological
[94]	Chinese–English bilinguals	41	United States of America	visual, auditory	Western participants were more distracted by visuals, and Eastern ones by sounds	visual, vocal
[95]	younger adults	36	20 Japanese, 16 Dutch	visual, auditory	Japanese participants were more attuned to vocal processing in the multisensory perception of emotion than Dutch participants	visual, vocal
[96]	workers	511	231 Chinese, 280 Americans	cultural experiences	expression of emotions was more direct in the United States	physiological
[97]	students	>400	Chinese and American	cultural experiences	Chinese men reported relatively low levels of emotion; American women reported relatively high levels of emotion	—
[98]	students	85	46 students from a university in the United States of America, 39 students from two universities in India	cultural experiences	the students from India adapted more to situations; the students from the United States of America perceived situations as more influential on their emotions	—
[99]	native speakers	30	China, United States of America, and Singapore	visual, auditory	Chinese participants showed greater auditory modality bias, while American participants showed greater visual modality bias	visual, vocal
[100]	adults	108	51 and 57 participants recruited from India and United States of America, respectively	reappraisal	participants from India were more prone to using cognitive reappraisal for high-intensity negative stimuli compared with participants from the United States of America	physiological
[101]	adults aged 40 years	102	Chinese, German, and English	cultural experiences	improved usability and accessibility	visual
[102]	drivers (over 18 years)	620	Australia and China	cultural experiences	Chinese drivers preferred symbols over words	visual
[103]	younger drivers	—	China, United States of America, Australia, and New Zealand	cultural experiences	better emotional regulation	visual
[104]	drivers (aged 20–60 years)	70	South Korea and Canada	cultural experiences	differences in ethical decision-making in the face of dilemmas	physiological
[105]	drivers	561	Italian, Argentine, Romanian, Chinese, Malaysian, Dutch, and Belgian participants	social norms	driving style assessment could influence driver emotion modulation	physiological, driving style
[106]	drivers	823	287, 329, and 207 participants recruited from Israel, Turkey, and United States of America, respectively	behavior	emotion modulation difficulties influenced forgiveness and driving styles differently across cultures	driving style
[107]	drivers	187	92 participants recruited from United Kingdom (21 males, 71 females), 95 participants recruited from Malaysia (33 males, 62 females)	visual	visual search of the environment while driving influences information processing and situational awareness	visual, driving style
[108]	drivers	118	32 Chinese, 35 Indians, 44 Americans, 7 participants recruited from other countries	cultural experiences	higher-context cultures exhibited greater trust and preference	physiological
[24]	drivers	30	Malaysia	cultural experiences	social/cultural factors led to more frequent and aggressive steering in local drivers compared to foreign ones	behavioral
[109]	road users	500	187 Singaporeans, 313 Malaysians	social norms	higher traffic risk perception and willingness	physiological
[27]	drivers	—	participants recruited from Egypt, United Kingdom, India, China, Japan, and the United States of America	social norms	the level of aggression or patience in driving could be influenced by societal attitudes toward traffic rules and interpersonal interactions on the road	physiological

Note: —: the numbers are not mentioned.

• Cultural Background Differences

Research demonstrates that cultural differences impact the effectiveness of driver emotion regulation. Asia and the Middle East are predominantly collectivist, with strong emotional dependency and a preference for implicit, indirect communication [74,78,81,82]. In these high-context cultures, rich communication and content guidance are necessary for managing emotional changes [93]. Asians show a higher sensitivity to auditory cues and prefer symbols over text in emotion modulation processes [79,80,84]. Europeans, known for their high well-being and self-awareness, are found in studies [71,78] to prefer clear and explicit methods for emotion regulation, typical of individualistic and low-context cultures [72,73,74,76,78,87,91,95]. Westerners are effectively regulated by visual means and tend to focus on core content [79,80,84]. Furthermore, the extent of cultural exposure affects the effectiveness of emotion regulation among European Americans and Asian Americans [71,76,79], as shown in

Table 4. Summary of regional cultural differences and application direction.

Region	Cultural Background	Research Algorithms	Results and Application Directions
Asia, Middle East	more sensitive to sound; more reserved; dislike expressing; emotional dependence; high faith; good at serving others; collectivism; prefer symbols; focus more on context than on focal points; good at hiding emotions	machine learning; two-way ANOVA; multi-group structural equation modeling; Bayesian estimator; ANOVA; K-means	voice regulation should focus on context; flexibly adjust strategies according to emotional needs; regulate through visuals, using symbols more often; emotion recognition needs to be more accurate due to good emotion hiding.
Europe	high sense of well-being; individualistic tendency; high self-awareness; more sensitive to visuals; higher ratio of male drivers; focus on focal points	machine learning; two-way ANOVA; multi-group structural equation modeling; ANOVA	regulate through auditory means; multi-modal emotion regulation is better; use more direct expressions for voice regulation; focus more on focal objects in visual design; use abbreviations for concise and clear expression.
Americas	more sensitive to visuals; language with higher information speed and density; individualistic tendency; low-context expression, prefer clear and explicit communication	ANOVA; correlation analysis; K-means; Pearson’s correlation
Others	the amount and time of exposure to new cultures affect emotional perception	two-way ANOVA	different long-term orientation and educational levels yield different results; research cultural influence duration during design; pay attention to market guidance in different regions.

.

The influence of cultural exposure on emotion modulation is evident in the following points. Different cultures exhibit distinct patterns in how emotions are perceived, expressed, and regulated. For instance, Asian cultures, including Japanese and Chinese, effectively regulate emotions more under stress using specific strategies and have a preference for auditory modalities [95,99]. Western cultures, represented by UK and US participants, are more visually oriented [85,94,107] and exhibit a more direct expression of emotions [96,97]. They also use cognitive reappraisal less frequently compared to participants from India when faced with high-intensity negative stimuli [86,98,107]. These differences in sensory processing and preferences influence behaviors, including driving, where the use of symbols versus words, and the interpretation of emotional cues, significantly affect driving behaviors [102].

• Influence of culture on driver emotion modulation

Research shows that emotion modulation across different cultures involves cognitive reappraisal and expressive suppression. Cognitive reappraisal is commonly used and associated with fewer behavioral problems [86,87,89,90,91]. Studies [88,90] show a strong association between cultural differences and individual performance, with cognitive reappraisal correlated with higher performance. East Asians, in particular, are more adaptable to emotion regulation [92]. Higher religiosity is also linked to increased rates of cognitive reassessment. Ref. [100] indicated that participants from India were more adept at emotionally regulating high-intensity negative stimuli.

Moreover, studies focusing on cultural influences on driver emotion modulation primarily concentrate on visual and auditory aspects [85,94,95,99,107]. Ref. [102] mentioned that even though there is not much direct emphasis on the sensory modulation of emotions, there is greater emphasis on human–machine interactions. This involves adapting interfaces and voice interactions to various cultures to monitor drivers’ emotions and lessen driving frustration. Ref. [101] highlighted the importance of culturally sensitive design in improving driver interaction and emotional well-being.

Meanwhile, several studies [103,106,108] have found that high-context cultures exhibit greater trust and preferences in their communication styles, which can influence broader behaviors in social and interactive settings. Also, some studies have demonstrated that cultural norms and social factors lead to differences in steering behavior, risk perception, and overall driving aggressiveness, highlighting the need for culturally sensitive approaches to driving education and policy-making [27,93,105,109]. It can be deduced that cultural backgrounds play a pivotal role in influencing how drivers emotionally respond to and regulate their feelings about autonomous technology.

• Influence of human characteristics on driver emotion modulation

Some studies on driver emotion modulation involve both sensory (n = 8, 30%) and psychological approaches (n = 19, 70%), with a significant emphasis on how culture influences individual personality traits and behaviors. Several studies have reported that drivers from different cultures exhibit unique preferences in driving styles, which require different design approaches to ensure effective emotional regulation during driving [105,106,107]. Ref. [24] reported that local drivers, influenced by cultural factors, exhibited more frequent and aggressive steering. In addition, it has been claimed that power distance, individualism versus collectivism, and long-term orientation are the cultural dimensions that influence drivers’ interactions [89]. Considering these cultural factors in design can enhance safety by reducing the need for behavioral adaptation. Also, refs. [27,93] mentioned that cultural diversity leads to different types of moral reasoning (e.g., moral altruists, moral nondeterminists, and moral deontologists), particularly for future autonomous vehicles, which influence drivers’ ethical decision-making processes. In this study, ref. [104] also showed that South Korea and Canada exhibit differences in ethical decision-making in the face of dilemmas. It is crucial to consider cultural diversity in order to create a moral, culture-specific emotion modulation framework in autonomous vehicles.

4. Discussion

We conducted this review with the goal of enhancing vehicle design by integrating advanced multisensory and culturally adaptive emotion modulation systems. We explored the primary emotions and perceptions associated with sensory inputs in driver emotion modulation. In addition, we examined the role of culture in driver emotion modulation. Moreover, we studied the methods and effects of driver emotion modulation within this field. We selected 802 articles to analyze their overall findings, providing insights into the effects of driver emotion modulation, as well as geographical distributions, sample sizes, and research trends. It is evident that a significant portion of driver emotion modulation methods involve the human senses. Although a considerable number of studies are from China and the United States of America, we also found significant geographic diversity in studies conducted in European and Asian countries. Studies in different countries also demonstrated cultural differences in driver emotion modulation. We selected 74 articles to analyze the specific findings, where 13, 34, and 27 articles were focused on driver emotion and behavior, driver emotion modulation based on unisensory and multisensory inputs, and cross-cultural impacts on drivers’ emotions. With the advancement of artificial intelligence, the primary focus of human–vehicle interaction has become emotional interaction [110].

The findings on multisensory driver emotion modulation suggest that vocal and visual modalities are more commonly used for modulation compared with haptic and olfactory modalities, as well as cooling methods. Empathetic voice strategies improve negative emotional states and trust in driving modes, while music can mitigate anger and influence cardiovascular responses linked with negative moods. Olfactory notifications are less distracting and more beneficial than visual ones, improving drivers’ mood and behavior. It is apparent that unimodal methods predominate the scientific literature, although some studies indicate that multimodal methods can enhance user experiences by transitioning vehicle functions from purely transportational to multisensory spaces [111]. Due to the potential ineffectiveness of unimodal approaches in driver emotion modulation, many have overlooked the importance of implementing emotion modulation strategies [22].

In the human-centered literature, there is an increasing focus on human factors. During our review process, we also discovered that an individual’s personality determines their driving style and influences the significance of sensory inputs in driver emotion modulation [5,112]. Ref. [113] show that drivers with higher EI exhibit less driving anger. By prioritizing human cognitive patterns in design, in-vehicle systems can become more intuitive and less distracting, enhancing emotion modulation and driving safety. According to [114], effective driver emotion modulation can provide a positive experience for users.

Furthermore, some studies address the impact of culture on drivers’ emotions, indicating that cultural differences can influence driving styles [115]. Studies have revealed that in Asia, due to a tendency toward collectivism, emotional dependence is stronger. Because emotional expression in Asia is more implicit, it indicates a need for more precise emotion recognition to assess and regulate drivers’ emotions. Asian culture requires more auditory modes for emotion regulation since they are more sensitive to sound and prefer symbols over text. In contrast, Western countries have a stronger inclination toward individualism and higher self-awareness. They prefer low-context, clear, and explicit verbal guidance for emotion modulation. They are more sensitive to visual input, prefer abbreviations for textual communication, and focus more on the core content rather than the context. There are national differences in driver emotion modulation. The amount and duration of exposure to new cultures also affect driver emotion modulation. Customizing interfaces and voice interactions according to different cultures is an effective method of modulation. Cultural backgrounds play a pivotal role in influencing how drivers emotionally respond to and regulate their feelings about autonomous technology. The lack of attention on cultural factors in driver emotion modulation in most studies indicates that there is a significant gap in the current understanding of how cultural attitudes toward technology influence driver behaviors. Thus, it is necessary to examine the need for culturally sensitive design [116] and how technologies used to modulate drivers’ emotions must be adaptable to diverse cultural norms and values [117].

4.1. Strengths of the Studies Reviewed in This Article

Based on this literature survey, we identified several strengths of the reviewed studies, which are listed as follows:

• The number of articles published on emotion modulation has been progressively increasing over the years, increasing from 80 in 2018 to 160 in 2023.
• A large number of participants were involved in the studies reviewed in this article, many of whom joined experiments that helped guide the research in the right direction.
• There is a special focus on the effects of driver emotion modulation on driving safety. Studies have shown that individual differences mean that drivers respond differently to sensory inputs, highlighting the importance of personalized approaches.
• Cultural backgrounds have been found to influence how drivers perceive and react to different sensory inputs. For example, the interpretation of colors in visual interfaces, the type of music considered soothing, or the acceptance of voice commands can vary widely across cultures.
• Human-centered approaches to driver emotion modulation are increasingly focused on enhancing user experience by aligning in-vehicle communication and attention management with drivers’ preferences and traits. Autonomous vehicles will increasingly use non-invasive technology to enhance safety and necessitate adaptable, culturally sensitive systems, as mentioned by [103].

4.2. Weaknesses of the Studies Reviewed in This Article

Despite the strengths of the studies reviewed in the literature, we also identified several weaknesses, which are listed as follows:

• Selection bias: The data for this review were sourced from two databases, Web of Science and Scopus. While these databases cover a broad range of content, they do not encompass all publications.
• Language bias: Limiting the review to studies published in certain languages (typically English) may overlook important research conducted in other languages, potentially skewing the results of the review.
• Geographic bias: The studies included in this review are primarily concentrated in specific countries in Asia and Europe (such as China, Japan, the USA, and the UK), which could narrow the scope of the research findings.
• Limited focus on emotion types: There is a predominant focus on unpleasant emotions, without correlating different categories of emotions with specific driving behaviors.
• Unisensory driver emotion modulation: Driver emotion modulation is often conducted based on a single sensory input, lacking effective emotion modulation strategies.
• Cultural studies from a social science perspective: The cross-cultural impact on drivers’ emotions is predominantly studied from a social science perspective, without considering driver emotion modulation from a multicultural viewpoint to address global cultural developments.
• Insufficient human-centered studies: There is a paucity of studies on individual differences in drivers’ emotional responses and sensory preferences, which are crucial for tailoring interventions.

4.3. Opportunity Analysis

• Develop integrated multisensory systems that combine visual, auditory, haptic, and olfactory modalities. Emphasize the use of empathetic voice strategies and music to alleviate negative emotions and enhance trust, while leveraging olfactory notifications to improve mood and behavior with minimal distraction.
• Transition vehicle environments from purely functional to multisensory spaces, incorporating a variety of sensory inputs to create a more engaging and emotionally supportive driving experience.
• Tailor emotion modulation interfaces to accommodate cultural preferences. For instance, in collectivist cultures like those in Asia, employ auditory cues and symbols more extensively, given this population’s higher sensitivity to sound and preference for symbolic communication.
• For individualistic Western cultures, design clear, low-context verbal guides and focus on focal visual elements. Utilize abbreviations and direct expressions to cater to their communication styles and visual sensitivity.
• Implement advanced emotion recognition systems that can accurately detect subtle emotional cues, especially in cultures where emotional expression is more restrained, such as in many Asian countries. This will enable more precise and effective emotion regulation interventions.
• Develop adaptive technologies that can modify their emotion modulation strategies based on the user’s cultural background. This includes customizing voice interactions, interface designs, and feedback mechanisms to align with diverse cultural norms and values.
• Examine the influence of cultural exposure on drivers’ emotions and incorporate this understanding into the design of emotion modulation systems. Recognize that drivers with significant exposure to new cultures may have different emotional responses and needs.

4.4. Threat Analysis

Developing reliable systems that accurately detect and modulate emotions is challenging due to the need to calibrate multisensory inputs to prevent passive fatigue or increases in risk-taking behaviors. Drivers might become overly dependent on emotion modulation systems, potentially leading to reduced self-awareness and self-regulation skills. This over-reliance could diminish a driver’s ability to manage their emotions independently, particularly in situations where technology fails or is unavailable. While tailoring systems to cultural preferences is beneficial, there is a risk of stereotyping or oversimplifying cultural traits. Incorrect assumptions about cultural behaviors and preferences can lead to ineffective or even counterproductive emotion modulation strategies. Current methods use natural language processing and olfactory delivery to regulate emotions in real time, but misinterpretations or malfunctions pose safety risks, underscoring areas for future exploration.

5. Conclusions

This comprehensive review has underscored the critical role of driver emotion modulation in enhancing driving performance and road safety. Through our analysis, we have identified key interactions between sensory inputs, cultural factors, and driver behaviors, significantly advancing the field of human-centered driver emotion modulation. Our study is one of the first to demonstrate the limitations of unisensory approaches, predominantly reliant on vocal or visual inputs, and to advocate for a multisensory integration strategy.

We have innovatively shown how multisensory inputs—combining auditory, visual, tactile, and olfactory senses—can more effectively regulate drivers’ emotions. For instance, our findings reveal that while traditional methods like speech and music influence driving behavior, integrating scents such as rose and peppermint can further enhance mood and performance. This multisensory approach not only fills a crucial gap in existing research but also sets a new direction for future investigations.

Moreover, our work distinctly highlights how individual characteristics and cultural backgrounds impact emotion modulation. We have conducted extensive studies across various cultures, revealing that regions such as Asia and the Middle East respond better to auditory and symbolic cues, whereas Western regions benefit from explicit and direct communication. These insights have led us to propose customizable emotion regulation systems that can be adapted according to cultural and individual needs, ensuring more effective and nuanced interventions.

Finally, we propose that by adopting an intelligent, human-centered approach, vehicles can be designed with culturally sensitive driver assistance systems based on human multisensory inputs. We need to develop an integrated multisensory system that combines visual, auditory, tactile, and olfactory modes and transition the vehicle environment from a purely functional space to a multisensory space, incorporating various sensory inputs to create a more engaging and emotionally supportive driving experience. We should also customize emotion regulation interfaces based on cultural preferences and develop adaptive technologies that can modify emotion regulation strategies according to the user’s cultural background. This includes customizing voice interactions, interface design, and feedback mechanisms to align with different cultural norms and values. Future studies can focus on developing multisensory driver emotion modulation systems that not only provide positive reinforcement without causing excessive relaxation or aggression, but also accommodate subtle cultural and individual differences in preferences for scents or tones, thereby enhancing autonomous driving safety through customized and adaptive interventions.