A Comprehensive Review: Multisensory and Cross-Cultural Approaches to Driver Emotion Modulation in Vehicle Systems
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Abstract
1. Introduction
- 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
- 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
- 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
3.2. Specific Findings
3.2.1. Driver Emotion and Behavior
3.2.2. Driver Emotion Modulation Based on Unisensory and Multisensory Inputs
3.2.3. 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 |
- Cultural Background Differences
- Influence of culture on driver emotion modulation
- Influence of human characteristics on driver emotion modulation
4. Discussion
4.1. Strengths of the Studies Reviewed in This Article
- 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
- 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
5. Conclusions
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
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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 | — |
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 |
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. |
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Zhang, J.; Raja Ghazilla, R.A.B.; Yap, H.J.; Gan, W.Y. A Comprehensive Review: Multisensory and Cross-Cultural Approaches to Driver Emotion Modulation in Vehicle Systems. Appl. Sci. 2024, 14, 6819. https://doi.org/10.3390/app14156819
Zhang J, Raja Ghazilla RAB, Yap HJ, Gan WY. A Comprehensive Review: Multisensory and Cross-Cultural Approaches to Driver Emotion Modulation in Vehicle Systems. Applied Sciences. 2024; 14(15):6819. https://doi.org/10.3390/app14156819
Chicago/Turabian StyleZhang, Jieshu, Raja Ariffin Bin Raja Ghazilla, Hwa Jen Yap, and Woun Yoong Gan. 2024. "A Comprehensive Review: Multisensory and Cross-Cultural Approaches to Driver Emotion Modulation in Vehicle Systems" Applied Sciences 14, no. 15: 6819. https://doi.org/10.3390/app14156819
APA StyleZhang, J., Raja Ghazilla, R. A. B., Yap, H. J., & Gan, W. Y. (2024). A Comprehensive Review: Multisensory and Cross-Cultural Approaches to Driver Emotion Modulation in Vehicle Systems. Applied Sciences, 14(15), 6819. https://doi.org/10.3390/app14156819