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Article

Effects of Chinese Text Size on the In-Vehicle Text Legibility and Driver Distraction: A Simulator Study

by
Qi Zhong
,
Rong Han
*,
Jiaye Chen
and
Chunfa Sha
Experience and Service Design Team, School of Arts, Jiangsu University, Zhenjiang 212013, China
*
Author to whom correspondence should be addressed.
Appl. Sci. 2025, 15(16), 8874; https://doi.org/10.3390/app15168874
Submission received: 27 June 2025 / Revised: 6 August 2025 / Accepted: 11 August 2025 / Published: 12 August 2025
(This article belongs to the Special Issue Human–Vehicle Interactions)
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Abstract

The rising popularity of in-vehicle information systems (IVIS) in China highlights the significance of Chinese character displays. A key design factor for text-rich in-vehicle human–machine interfaces (HMI) is Chinese text size (CTS). However, the impact of CTS on text legibility and driver distraction has not been extensively explored. The present study launches a simulator experiment and adopts several one-way repeated-measure analyses of variance to identify the optimal CTS that maximizes text legibility while minimizing driver distraction. The findings indicate that both text legibility and driver distraction improved progressively as the CTS increased, reaching a specific size of seven millimeters, at which they approached asymptotes. Subjective measures were more sensitive than objective measures. The analysis showed no significant impact of CTS on task completion time, number of errors, total glance duration, mean speed, or lane position variation. However, larger CTS led to more frequent, shorter glances, whereas smaller CTS resulted in fewer, longer glances. CTS below seven millimeters was associated with lower subjective preference and a higher perceived workload. Therefore, it is recommended that a CTS of seven millimeters or larger be used to promote the design of driver-friendly in-vehicle HMI, control IVIS-related distractions, and enhance road safety in China.

1. Introduction

In recent years, the sales of in-vehicle information systems (IVIS) have experienced exponential growth. According to Statista [1], global shipments of IVIS are projected to exceed 70 billion USD by 2027. With the explicit prohibition of mobile phone use while driving in most countries [2], alongside the increasing integration of mobile technology in IVISs [3], concerns about IVIS-related distractions have become widespread [4]. Driver distraction is increasingly recognized as a significant contributor to motor vehicle injuries and fatalities. Using IVIS while driving can be seen as a form of epidemic and harmful distracted driving behavior, as it diverts attention from the primary task of driving to secondary tasks related to IVIS. These distractions can involve visual, auditory, manual, cognitive, and temporal demands, often requiring a combination of these factors simultaneously. Numerous studies, including self-reports [5,6], official reports [7,8], roadside observations [9,10], simulations [11,12], on-road assessments [13,14], and naturalistic driving research [15,16], consistently confirm the negative impact of IVIS-related distractions on traffic behavior and road safety. These effects include longer operation times, excessive off-road glances, increased driving workload, prolonged reaction times, deteriorating driving performance, and heightened probabilities of near-crashes, actual crashes, and traffic congestion. Unfortunately, as noted by Parnell et al., there is currently no clear legislation addressing IVIS-related distractions, unlike that for mobile phone use [17,18,19]. Therefore, designing a driver-friendly IVIS to reduce or mitigate driver distraction is crucial and has become a significant concern for automobile manufacturers worldwide [20].
China’s automobile industry has experienced significant quality improvements and rapid development over the past decade. According to China’s Ministry of Public Security [21], by the end of September 2023, the number of motor vehicles in the country reached 430 million. China is anticipated to become the third-largest market for IVIS, following North America and Europe [22]. The growing popularity and profitability of IVIS services in China underscore the importance of Chinese character displays in vehicles. As features like navigation, email, and messaging are integrated into automobiles, the amount of text-rich information presented to drivers has dramatically increased [23]. Consequently, text legibility—the clarity with which individual characters can be understood or recognized—has become increasingly important. Chinese text size (CTS) is a crucial aspect of automotive human–machine interface (HMI) design because it directly affects both text legibility and driver distraction [24,25,26]. However, to the best of our knowledge, CTS can vary significantly in the market, and there are currently no established design guidelines for in-vehicle HMI in China [25,26]. Finding the appropriate CTS is essential for creating driver-friendly in-vehicle HMI, minimizing IVIS-related distractions, and enhancing road safety and public health. Therefore, investigating the impact of CTS on in-vehicle text legibility and driver distraction is a pressing task of practical importance.

2. The Related Work and Research Gaps

2.1. CTS on Visual Display Terminals (VDTs)

As previously mentioned, whether it is in English or Chinese, text size plays a crucial role in text legibility. Several studies have investigated the legibility of CTS on different screen-based VDTs, including mobile phones [27,28], computers [29,30], and tablets [31,32]. In general, the aforementioned screen-based VDTs have similar task scenarios and all operate in single-task and non-critical safety contexts. In terms of both subjective and objective text legibility, text sizes that are too small or too large typically lead to reduced reading speed, lower accuracy, and less favorable subjective evaluations, such as perceptions of legibility and overall preference. According to Kingery and Furuta [33], on the one hand, the reduced performance associated with smaller text sizes may be due to a lack of clarity in the internal patterns of words. On the other hand, the poor performance linked to larger text sizes likely stems from the fact that less ‘meaningful information’ can be perceived in a single eye fixation.

2.2. Text Size on IVIS

Essentially, the IVIS operates in a significantly different context from the previously mentioned VDTs. The optimal text sizes identified for non-driving environments may not be suitable for automobile use. Firstly, driving is a safety-critical activity, making the text-reading task a secondary activity; safe driving remains the primary focus [34]. Secondly, unlike the continuous reading experience in other settings, drivers typically read in-vehicle text information during brief, interrupted glances [35]. Thirdly, IVIS is usually installed in the center console, requiring drivers to read text that is ‘off-axis’, at an angle of around 15 degrees or more, and from potentially greater distances than those encountered in seated environments [36]. As a result, it is uncertain whether the text sizes deemed appropriate in sedentary, non-driving contexts will be practical in the dynamic driving environment.
Some researchers have conducted psychophysical experiments on how text size affects legibility under glance-like reading conditions. For instance, Dobres and their colleagues [37,38,39] thoroughly examine text size legibility. They found that even minor differences in on-screen typeface design can significantly influence the time a viewer glances at the device. Overall, larger text sizes proved more legible than smaller ones, after accounting for other factors such as stroke weight, contrast polarity, and ambient lighting. Fujikake et al. [40] reported subjective ratings of legibility for five different text sizes (2, 4, 6, 8, and 10 mm) in two viewing positions: directly in front of the participant and 30 degrees to the left. They discovered that text presented directly in front received significantly higher legibility ratings, with the largest text size of 10 mm deemed the most legible. However, it is important to note that reading was the primary task in this case. Similarly, Cai and Green [41] developed equations to predict optimal text sizes for in-vehicle displays, indicating that larger text sizes are necessary to accommodate increased target distance and decreased display brightness when viewing off-axis. However, these equations do not consider the complexities associated with a dual-task driving context, and none of the studies have examined the effects of text size on reading measures, off-road glance performance, and driving behavior.
To the best of our knowledge, few studies have investigated the effects of text size on legibility under driving conditions. For example, Reimer’s research group [42,43] compared two different typeface designs in a simulator study, featuring a capital letter height of four millimeters. The results indicated that the Humanist typeface was less visually demanding than the Square Grotesque typeface, as shown by shorter task times, reduced total off-road glance duration, and fewer off-road glances. Viita and Muir [44] established subjective levels of legibility for Chinese and English text in in-vehicle displays during a simulated driving experiment. The participants reported that the minimum comfortable text size for English matched the minimum criteria (four millimeters) outlined in Reimer’s study [42,43]. They also found that comfortable and acceptable character sizes for Chinese text displayed on IVIS are approximately 0.5 mm larger than those for English text, confirming that characters with higher density should be larger. However, the self-reported results of Viita and Muir [44] are subjective and have not been verified by other objective data (eye-tracking and driving performance). Crundall et al. [24] conducted a medium-fidelity simulator study to examine the impact of English text sizes (4, 5, 6.5, 8, and 9 mm) on visual demand, driving performance, and workload. Although there were no apparent decrements in driving performance associated with smaller text sizes, drivers extended their glance duration when the text size was reduced, as they attempted to process more information with each glance. Therefore, it is recommended that designers of in-vehicle HMI avoid using English text sizes of 6.5 mm or smaller. Similarly, Kim et al. [45] surveyed the legibility effects of Korean text size, suggesting that the minimum legible Korean text size is approximately 14 pt, about 4.94 mm. Chinese characters have a higher character density than Japanese, English, and Korean texts due to their more complex structures and directional strokes [46]. Consequently, recommendations for text sizes in Japanese, English, and Korean should differ from those in Chinese [24,42,43,44,45,46].
Only a limited number of studies have explored the impact of CTS on in-vehicle text legibility and driver distraction in dual-driving conditions. For example, Qian and Sun [25] conducted a rapid in-vehicle HMI visual distraction test with 30 participants. Their findings indicated that typeface choice could significantly affect the legibility of the in-vehicle text. Furthermore, they noted that differences in glancing behavior could not be significantly reduced when increasing the CTS from five to six millimeters. However, none of these studies have examined the effects of CTS on driving performance and workload. You et al. [26] also investigated CTS in the IVIS of intelligent vehicles. Their experiment involved 30 participants performing simulated in-vehicle secondary tasks. They found that text legibility improved and driver workload decreased as the CTS increased. They recommended a minimum CTS of 4.5 mm, with an optimal 6 mm or larger CTS. Nevertheless, there has been no investigation into the effects of CTS on off-road glancing behavior and driving performance.

2.3. The Present Research

To summarize, the reviewed literature indicates that several knowledge gaps still need to be addressed. Firstly, research on the legibility of CTS has primarily focused on mobile phones, computers, and tablets [27,28,29,30,31,32]. However, it remains unclear how drivers interact with CTS within IVIS while in a vehicle, where driver distraction should be a primary concern, in addition to issues of text legibility. Secondly, while studies have investigated the impact of text size in English, Japanese, and Korean on in-vehicle text legibility and driver distraction [24,37,38,39,40,41,42,43,44,45], fewer studies have examined CTS, which exhibits a higher intra-character density than these languages. Thirdly, there is a relative lack of empirical eye-tracking research on CTS legibility in dual-task driving scenarios [24,25,26,44], highlighting the need for further simulator studies that offer a safe, cost-effective, and repeatable environment [47,48]. To address these knowledge gaps, a simulated driving experiment has been initiated to explore the effects of CTS on in-vehicle text legibility and driver distraction.

3. Materials and Methods

3.1. Participant

The convenience sampling method was adopted. Thirty-five drivers (18 females and 17 males) with no prior experience in similar experiments were anonymously recruited to participate in this simulator study. The recruitment targeted drivers were aged 18 to 60 years (mean age: 34.1, standard deviation: 7.2) to account for the decline in visual acuity as people age. In order to achieve the experimental purpose safely and accurately, all participants held valid Chinese driving licenses and had at least one year of driving experience (range: 1 to 20 years, mean: 8.5 years, standard deviation: 6.1 years). Those with visual acuity that was not normal or not correctly compensated were excluded from the study. Additional requirements included being in reasonably good health, having adequate sleep, and being comfortable speaking and reading Chinese. Participants with major illnesses requiring hospitalization in the past six months and those diagnosed with Parkinson’s disease or other neurological disorders were also excluded due to potential impacts on fine motor control. All participants signed written informed consent before taking part in the simulated driving experiment. The School of Arts, Jiangsu University’s Ethics Committee approved the study (Approval Number: 2024-11-003).

3.2. Design

This study was designed as a 6 × 1 within-subject repeated measures experiment, with CTS as the independent variable. The CTS levels ranged from 4 mm to 9 mm, specifically: 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, and 9 mm. Additionally, a baseline condition was included where no text was presented. Current international standards for HMI displays specify that the character height for a particular font should be measured as the distance from the baseline to the cap height of the font, using the capital “H” as a reference [9]. The minimum CTS of 4 mm is based on findings by Viita and Muir [44], which suggest that 4 mm is the smallest comfortable text size for English on IVIS. The maximum CTS of 9 mm was determined from research by Crundall et al. [24], where this size ensured that the text covered the entire display area. The CTS of 6 mm was chosen because it aligns closely with the recommended size indicated by You et al. [26]. The 5 mm CTS was included because research by Qian and Sun demonstrated that increasing the size from 5 mm to 6 mm resulted in only marginal differences in glancing behavior [25]. The median sizes of 7 mm and 8 mm were selected as they are approximately midway between the other sizes.
The dependent variables in this study encompass two dimensions: text legibility and driver distraction indicators. Specifically, the metrics of text legibility include task completion time, number of errors, subjective preference, and NASA-TLX, a workload rating scale. The metrics of driver distraction include mean speed, lane position variation, total glance duration, number of glances, mean glance duration, and the number of glances exceeding 2 s (s). Detailed definitions, measurements, and correlations with text readability and driver distraction are presented in Table 1.

3.3. Task

The primary task in the simulated driving study involved lane-keeping at speeds between 40 and 60 km/h, following China’s urban road speed limits [49,50,51]. The secondary task required participants to search for specific characters within pseudo-text passages—random strings of Chinese characters—simulating a quick browse on an IVIS to locate a target character. Using pseudo-text allows for consistent stimulation for each condition and helps eliminate individual differences in semantic comprehension [24]. To ensure data reliability, participants had to search through three passages for each experimental condition, resulting in 18 trials (6 levels × 3 trials). A counterbalanced design was employed to distribute these 18 trials evenly across participants. Additionally, 30 s baseline driving tasks, during which no text was presented, were conducted at random times, which provided a basis for comparison of driving performance measures between single-task and dual-task scenarios.

3.4. Stimulus

Six different passages of Chinese pseudo-text were created, each featuring a distinct text size defined by capital letter heights of 4 mm, 5 mm, 6 mm, 7 mm, 8 mm, and 9 mm. An example of a pseudo-text passage is illustrated in Figure 1, which was programmed using PHP 8.1 and displayed on a 10.1-inch HUAWEI tablet with a resolution of 1920 × 1200 pixels (Huawei, Shenzhen, China). Aside from the varying text sizes, all other factors impacting text legibility were controlled in this study. Following the previous literature, the pseudo-texts were composed of the 3500 most frequently used Chinese characters [57], with stroke counts ranging from 4 to 17 [27]. Each pseudo-text passage consistently displayed 50 characters, arranged in five lines of 10 characters each [31]. The typeface used was Hei style, formatted in single-spacing and shown in positive polarity, with the blocks of pseudo-text center-justified [38,42].
Each passage contained the target character appearing two, three, or four times. Participants were not informed about the number of target characters to avoid any anticipatory behavior, and their positions were randomized [24]. The character located in the upper left corner of the interface was the one participants needed to identify. Participants pressed the ‘+’ button each time they identified a target character, which was highlighted in red. The ‘→’ button was used to indicate the completion of a trial. A program that randomized the order of the 18 tasks managed the automated presentation of stimuli. The intervals between the end of one task and the prompt for the next task varied randomly between 20 and 40 s.

3.5. Apparatus

The snapshot of the experimental apparatus is shown in Figure 2. The experiments were conducted in a fixed-base simulator at the Vehicle Ergonomics Laboratory of Southwest Jiaotong University. The simulator included vehicle models, an accelerator, a brake, clutch pedals, seats, and steering wheels. A 1.5 m wide by 1.0 m high LCD screen displayed the traffic environment ahead. Following guidelines from the NHTSA for distraction testing [58], a simulated urban road was created, featuring a two-way, six-lane layout that was straight, 3.5 m wide per lane, and 5 km long, without gradients or horizontal curves. The roadside infrastructure included traffic signs, buildings, streetlights, and landscaping, all developed using SimCreator 2.0 and SimVista 2.0 software. Occasional directional road signs and slip roads were also included to enhance authenticity.
A custom Java application was integrated with the V4.4 software for STISIM Drive to monitor the vehicle’s speed and lane position. Since actual reading while driving generally occurs in low-demand traffic situations, the simulator had no vehicles in the middle lane and a low-density traffic flow on both sides of the carriageway.
An iPad Air 2 (10.1-inch, Apple, Cupertino, CA, USA) was positioned on a chair 50 mm high and angled 30° to the right of the steering wheel to simulate IVIS [49,50,51]. A GoPro Hero 12 Black high-definition action camera (GoPro, San Mateo, CA, USA) was mounted beside the IVIS screen, providing a 180° view to capture the participants’ task performance.
The Tobii Glasses 3.0 eye tracker system (Tobii, Stockholm, Sweden) was employed to collect binocular gaze data at a frequency of 50 Hertz. This system creates a gaze cursor overlaid onto a video scene recorded from the participant’s point of view, offering a real-time video record of their focus throughout the experiment. The Tobii Pro Lab 3.0 software analyzed the participants’ off-road glance behavior.

3.6. Procedure

The single test lasts about 30 min and mainly includes the following four stages: preparation, practice, formal, and questionnaire. Each participant completed the experiment, accompanied by an experimenter and an assistant. The whole experiment took place from 10 to 24 November 2024.

3.6.1. Preparation Stage

Upon arrival, participants’ basic sociodemographics were collected and examined based on the qualification criteria, including gender, age, driving habits, and driving experience. A research associate then verbally informed them about the study’s aim, procedures, tasks, potential benefits and risks, and the assurance of anonymity and confidentiality. Finally, participants were required to sign the written informed consent to further participate in the experiment.

3.6.2. Practice Stage

Participants, wearing well-calibrated Tobii Glasses 3 eye trackers, underwent brief training sessions to familiarize themselves with the simulator and assess their simulator-related symptoms. A research associate then manually initiated a series of practice trials and further explained the tasks as necessary. Participants were presented with at least three examples to ensure they understood the tasks. Participants were instructed to balance driving safety while attempting to complete the tasks, just as they would when driving a real car. Safety remained the top priority while we encouraged them to do their best. Those who met all the criteria then proceeded to the formal session. Before this, they were given a brief rest period, during which the eye tracker was recalibrated accurately.

3.6.3. Formal Stage

In the main experiment, participants were instructed to stay in the middle lane while driving at 40 to 60 km/h. They were tasked with performing character-search tasks using a pseudo-text passage. Participants were required to read each passage from the top left to the bottom right and identify the presence of a target character, ensuring consistency across all character-search conditions to avoid potential discrepancies. Instead of counting each occurrence of the target character mentally or rereading the pseudo-text to confirm their responses, which would be a distraction, participants were instructed to press the ‘+’ button whenever they detected the target character. After pressing the ‘→’ button, the screen would go black, and the subsequent trial would begin after a 30 s interval. Additionally, 30 s baseline tasks were administered at random intervals during each condition. Throughout the experiment, participants received explicit instructions to remain in the middle lane, pay attention to the road ahead, avoid aggressive driving behaviors, and drive deliberately slowly to enhance their ability to read the pseudo-text efficiently.

3.6.4. Questionnaire Stage

Participants were instructed to complete the paper-based NASA-TLX scale honestly after each condition. At the end of the experiment, their subjective preferences were recorded on a paper-based 10-point Likert scale. The Simulator Sickness Questionnaire indicated that none of the participants experienced simulator sickness. In detail, the dimensions, measurement items, and reliability of the simplified Simulator Sickness Questionnaire can be seen in Table A1, Appendix A. The result of reliability represented by the Cronbach’s coefficient (α = 0.887) meets the requirements. After this was confirmed, each participant received a movie ticket or a 50 CNY phone bill voucher as reimbursement for their participation.

4. Results

Five participants were excluded due to missing eye-tracking data. As a result, the analytical sample consisted of 540 measurement samples (30 participants × 6 tasks × 3 replicates). Data processing and analysis were conducted using IBM SPSS software version 29.0. Firstly, all outliers were identified and removed, and the remaining data were averaged to reduce measurement errors across each condition. Secondly, the verification of residual normality was performed, and two measures (the number of glances and the number of glances over 2 s) underwent a square root transformation to support the normality hypothesis. Thirdly, several one-way repeated measures analyses of variance (R-ANOVA) were performed to investigate the effect of the cognitive demand on text legibility and indicators of driver distraction. The degrees of freedom were adjusted using the Greenhouse–Geisser correction due to Mauchly’s test indicating a violation of the sphericity assumption. When appropriate, the Least Significant Difference (LSD) post hoc test was employed to control for potential Type I errors. The effect size was measured using partial eta squared (ηp2), and statistical significance was defined as p < 0.05.

4.1. Text Legibility

In the analysis of pseudo-text legibility across six conditions of CTS, the results from the one-way R-ANOVA (shown in Figure 3, Figure 4 and Figure 5) indicated no significant effect on task completion time [F(5, 145) = 14.56, ηp2 = 0.07, p = 0.082], as illustrated in Figure 3, or the number of errors [F(5, 145) = 15.96, ηp2 = 0.06, p = 0.090], as illustrated in Figure 4. However, a significant difference was observed in the subjective preference scores [F(5, 145) = 65.57, ηp2 = 0.58, p < 0.001], as illustrated in Figure 5. The subsequent LSD post hoc analysis revealed that participants’ subjective preferences increased steadily with higher CTS levels.
The dimensions, measurement items, and reliability of the NASA-TLX scale are seen in Table A2, Appendix A. The result of reliability represented by the Cronbach’s coefficient (α = 0.865) meets the requirements. Furthermore, a significant difference in the overall scores of NASA-TLX [F(5, 145) = 38.13, ηp2 = 0.33, p < 0.01] was confirmed, as illustrated in Figure 6, suggesting that the overall perceived workload of the participants decreased as CTS increased little by little. More specifically, a series of one-way R-ANOVAs was conducted for the six subscales’ scores of NASA-TLX. The results presented in Figure 7 show that the trend of the changes in the scores of half of the sub-scales was consistent with the overall score of NASA-TLX. That is, as the CTS gradually increased, the subscales’ scores of the mental demand, performance, and effort also decreased. However, three subscales demonstrated insignificant effects: ‘physical demand’ [F(5, 145) = 16.11, ηp2 = 0.09, p = 0.060], ‘temporal demand’ [F(5, 145) = 18.45, ηp2 = 0.10, p = 0.055], and ‘frustration’ [F(5, 145) = 14.73, ηp2 = 0.08, p = 0.066].

4.2. Driver Distraction

Regarding driving performance, the results presented in Figure 8 indicate a significant difference in mean speed [F(6, 174) = 27.48, ηp2 = 0.16, p < 0.05]. The LSD post hoc analysis revealed that participants drove the fastest in the baseline condition, with no significant differences found among the six dual-task driving conditions. Additionally, Figure 9 shows a significant difference in lane position variation [F(6, 174) = 60.33, ηp2 = 0.54, p < 0.001]. The LSD post hoc results indicate that the baseline condition had the least lane position variation, while the standard deviation of lane position increased with the rise in CTS. However, there were no significant differences among the six dual-task conditions.
In terms of off-road glance behavior, the one-way R-ANOVA results found no significant difference in total glance time [F(5, 145) = 11.96, ηp2 = 0.07, p = 0.073], as illustrated in Figure 10. However, there were significant differences in the number of glances [F(4.68, 121.96) = 44.41, ηp2 = 0.38, p < 0.01], as illustrated in Figure 11, and mean glance duration [F(4, 100) = 42.62, ηp2 = 0.36, p < 0.01], as illustrated in Figure 12. The subsequent LSD post hoc analysis showed that the number of glances increased with CTS, while the mean glance duration decreased as CTS increased. Specifically, the CTS conditions of 7 mm, 8 mm, and 9 mm resulted in the highest frequency of off-road glances and the shortest mean glance duration. Finally, the results of the one-way R-ANOVA shown in Figure 13 indicate that the impact of CTS was significant for the number of glances lasting over 2 s [F(5.45, 124.88) = 55.03, ηp2 = 0.50, p < 0.001]. The highest counts occurred in the CTS (4 mm) and CTS (5 mm) conditions, while the lowest counts were observed in the CTS (7 mm), CTS (8 mm), and CTS (9 mm) conditions. The CTS (6 mm) condition fell in between.

5. Discussion

This simulator study investigated how CTS affects in-vehicle text legibility and driver distraction. It was found that both text legibility and driver distraction improved progressively as the CTS increased, reaching optimal performance at a size of 7 mm, where improvements began to plateau. Therefore, after comprehensive consideration, a CTS of 7 mm or larger is recommended.

5.1. Text Legibility and Driver Distraction Improved Gradually as the CTS Increased

Two subjective measures of text legibility (subjective preference and NASA-TLX) indicated that text legibility gradually improved as the character size (CTS) increased. This finding supports the studies conducted by Crundall et al. [24], Viita and Muir [44], and Kim et al. [45]. In other words, beyond just Korean and English, the observation that larger text can subjectively enhance legibility is also evident in Chinese. Furthermore, this finding extends the previous conclusions drawn from research involving mobile phones [27,28], computers [29,30], and tablets [31,32]. Specifically, a larger CTS resulted in better pseudo-text reading performance in a stationary, non-driving context (where reading is a primary task). It yielded similar results in a dynamic driving context (where reading is a secondary task and safe driving is the main priority).
From an objective standpoint, no evidence suggests that the total time taken and the visual demands of the pseudo-text reading task change with varying CTS, contrasting with earlier research conducted in non-driving contexts [27,28,29,30,31,32]. Previous studies indicated that a medium CTS is most effective, while both too small and too large CTS can hinder reading efficiency. An excessively small CTS can lead to poor perception of character patterns, while an overly large CTS can limit the amount of information processed in a single glance [30]. The safety-critical nature of driving largely influences this outcome. Crundall et al. [24] noted that, in addition to text size, the total task time and glance duration are also influenced by the demands of driving safety during dual-task situations. In this regard, when controlling for other factors, variations in CTS do not significantly affect the total time or visual resources allocated to text stimuli, as these do not exceed a threshold that would compromise the driver’s safety.
Although the overall duration of off-road glances did not show significant differences, the distribution of these glances revealed notable variations. Larger text sizes were associated with more frequent, shorter glances, while smaller text sizes resulted in fewer but longer glances. This finding aligns with the research conducted by Crundall et al. [24], which suggests that smaller text leads to processing more information during each off-road glance. Similarly, as noted by Yen et al. [30], smaller text on desktop computers produced longer fixation durations and fewer individual fixations compared to larger text. Our study extends this finding from non-driving contexts to driving scenarios. In order to quickly scan pseudo-text while driving, participants did not exhibit unique adaptive glance behaviors [11,12]; instead, they employed the same eye movement patterns typically observed during sedentary reading tasks. Under regular circumstances, this approach might offer advantages, as it could be more efficient to process visual information through fewer, longer glances. However, lengthy off-road glances are known to negatively impact driving performance in driving contexts.
In contrast, drivers who read smaller CTS on in-vehicle HMI did not experience a decline in reading performance or mean speed; however, they did show greater variation in lane position, which poses a safety concern. This result only partially aligns with the findings of Crundall et al. [24], who indicated that reading pseudo-text on IVIS with varying CTS does not significantly impact reading performance or driving performance, including mean speed and lane position variation. Interestingly, the mean speed during dual-task conditions was lower than the baseline condition, which is generally interpreted as a self-regulating driving strategy [59]. However, no significant differences were observed across all dual-task driving conditions. We hypothesize that factors such as driving speed, traffic flow, and roadway alignment, along with the characteristics of the simulation, might cause these drivers to feel overly confident about their driving abilities, leading them to avoid taking necessary compensatory actions [49,50,51]. Moreover, the results also indicate that the subscale scores of physical demand, temporal demand, and frustration on the NASA-TLX showed no significant differences among the five CTS conditions. Multiple resource theory may help explain the observed lane position variability. Wickens [60] reported that competition for visual resources existed between reading and driving tasks. Although total glance time was similar across each CTS condition, the smaller character types resulted in longer mean glance durations and more off-road glances exceeding 2 s. This unwanted visual distraction, coupled with the insufficient compensation for mean speed, contributed to the variations in lane position.

5.2. The Recommended CTS for IVIS Is Seven Millimeters or Larger

Based on the principles proposed by Crundall et al. [24], Kim et al. [45], and Zhong et al. [51], the ideal CTS is the smallest size that ensures maximum text legibility while minimizing driver distraction. Specifically speaking, for this research, a CTS of 7 mm was identified as optimal, as larger sizes did not result in significant improvements in text legibility or reduced driver distraction. In comparison, this recommendation value exceeds the appropriate CTS for mobile phones [27,28], computers [29,30], and tablets [31,32], further highlighting the complexity of safety-critical driving scenarios. In other words, this once again proves indicating that reading text on handheld cellphones or smartphones while driving is a more distracting activity compared to browsing text on IVIS while behind the steering wheel [34]. Furthermore, the recommended minimum CTS of 7 mm is slightly larger than the minimum suggested sizes for English text (6.5 mm) [24] and Korean text (14 pt, approximately 4.94 mm) for IVIS [45], which is reasonable because Chinese characters, consisting of more strokes and structures, have a higher character density than English and Korean [42,45]. The optimal CTS (7 mm) obtained in this study is also greater than the minimum acceptable size of the English text (4 mm) and the Chinese text (4.5 mm), indicating the limitations of the subjective readability assessment method used in the study of Viitaa & Muir [44]. Therefore, when evaluating the design of the in-vehicle HMIs, it is beneficial to supplement with eye-tracking data and driving performance data.

5.3. Strengths, Limitations, and Future Study

Recently, how to alleviate driver distraction caused by in-vehicle technologies has been a research hotspot. As far as we know, this research is the first simulator study to comprehensively investigate the impact of CTS on in-vehicle text legibility and driver distraction. The findings have practical implications for designing driver-friendly in-vehicle HMI, preventing IVIS-related distraction, and reducing road injuries in China.
However, several limitations should be considered when interpreting these findings, as they reflect the broader research potential opened up by the study’s findings. Firstly, the experiment was conducted in a low-level fidelity driving simulator. The CTS used may not directly apply to actual in-vehicle HMI designs without further testing in on-road or naturalistic driving scenarios. Secondly, the driving environment settings are too simple; more challenging traffic conditions, such as complex traffic flow, curved roads, and nighttime driving, need to be further considered. Thirdly, it is necessary to explicitly point out that these findings may only be apply to the selected participant pools for this study. Therefore, caution is warranted when generalizing these findings to the whole population. Fourthly, since this study primarily focused on the text size, future research that uses visual acuity tests to consider the effect of age on drivers is necessary. Fifthly, this study focuses solely on the CTS and does not consider other design factors of Chinese characters or Arabic numerals, which greatly restricts the practical relevance and applicability of the findings to real-world IVIS design. Future research could explore additional characteristics, such as text length, stroke width, character complexity, line spacing, and contrast polarity, to further enhance in-vehicle text legibility and reduce driver distraction.

6. Conclusions

The ongoing increase in car ownership in China and the rising popularity of text-rich in-vehicle HMI prompted us to conduct a driving simulation study. This study aimed to investigate the effects of CTS on text legibility within vehicles and driver distraction. Our findings yielded several important conclusions.
  • The in-vehicle text legibility and driver distraction issue progressively improved as the CTS increased, reaching a level of seven millimeters, where both factors approached their maximum effectiveness. Therefore, we recommend using a CTS of seven millimeters or larger for displaying in-vehicle text information.
  • Subjective measures were more sensitive than objective measures. There were no significant differences in average speed and lane position variation; a CTS smaller than seven millimeters led to lower subjective preferences and a higher perceived workload among drivers.
  • Although no significant effect of CTS was observed on task completion time or total glance duration, there were notable differences in glance distribution. Larger CTS resulted in more frequent, shorter glances, while smaller CTS led to fewer, longer glances.
These findings enhance the current understanding of how CTS affects in-vehicle text legibility and driver distraction, which contributes to in-vehicle HMI design in China. It supports the development of driver-friendly IVIS to prevent distraction-related injuries and promote road safety in the country.

Author Contributions

Conceptualization, Q.Z.; data curation, C.S.; formal analysis, Q.Z.; funding acquisition, R.H. and J.C.; methodology, Q.Z.; project administration, R.H. and J.C.; resources, C.S.; software, J.C. and C.S.; supervision, R.H.; validation, J.C. and C.S.; visualization, C.S.; writing—original draft, Q.Z.; writing—review and editing, Q.Z. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Key Research Base of Philosophy and Social Sciences in Sichuan Province (GYSJ2025-19), Youth Project of Jiangsu Provincial Social Science Foundation (23YSC013), General Project of Humanities and Social Sciences Research of the Ministry of Education of China (23YJC760010), and the General Project of Art Studies, National Social Science Foundation of China (21BG110).

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Ethics Committee of the School of Arts at Jiangsu University in China on 10 November 2024. (approval number: 2024-11-003), with which both authors were formerly affiliated.

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study. Written informed consent has been obtained from the patient(s) to publish this paper.

Data Availability Statement

The original contributions presented in the study are included in the article; further inquiries can be directed to the corresponding author upon reasonable request.

Acknowledgments

The authors would like to thank all the participants and the two research assistants for their efforts and dedication in this simulator experiment. In addition, we would like to express our gratitude to the Vehicle Ergonomics Laboratory of the School of Design at Southwest Jiaotong University for their technical support.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
IVISIn-Vehicle Information Systems
HMIHuman–Machine Interfaces
CTSChinese Text Size

Appendix A

Table A1. The dimensions, measurement items, and Cronbach’s coefficient of the simplified Simulator Sickness Questionnaire.
Table A1. The dimensions, measurement items, and Cronbach’s coefficient of the simplified Simulator Sickness Questionnaire.
DimensionsMeasurement ItemsCronbach’s
Coefficient
NauseaOverall feeling of stomach discomfort0.887
OculomotorOverall feeling of oculomotor discomfort
DisorientationOverall feeling of disorientation
Table A2. The dimensions, measurement items, and Cronbach’s coefficient of the NASA-TLX.
Table A2. The dimensions, measurement items, and Cronbach’s coefficient of the NASA-TLX.
DimensionsMeasurement ItemsCronbach’s
Coefficient
Mental DemandHow much mental activity was required (e.g., thinking, decision making, calculating, memorizing, and searching)? Was the task easy or difficult for you mentally? Simple or complex?0.865
Physical DemandHow much physical activity was required (e.g., pushing, pulling, turning, and controlling movements)? Was the task easy or difficult for you physically? Slow or fast-paced? Effortless or strenuous?
Temporal DemandHow hurried or rushed was the pace of the task? Was the pace slow and leisurely, or rapid and hectic?
PerformanceHow successful were you in accomplishing your goal? How satisfied were you with your performance in accomplishing the task goals?
EffortHow hard did you have to work (mentally and physically) to accomplish your level of performance?
FrustrationHow insecure, discouraged, irritated, stressed, and annoyed were you during the task?

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Applsci 15 08874 g001
Figure 1. Example passage of Chinese pseudo-text. (a) The six types of CTS, (b) the Chinese pseudo-text interface.
Figure 1. Example passage of Chinese pseudo-text. (a) The six types of CTS, (b) the Chinese pseudo-text interface.
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Figure 2. The snapshot of the experimental apparatus. (a) Local view. (b) Global view.
Figure 2. The snapshot of the experimental apparatus. (a) Local view. (b) Global view.
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Figure 3. The result of the task completion time (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 3. The result of the task completion time (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 4. The result of the number of errors (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 4. The result of the number of errors (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 5. The result of the subjective preference (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 5. The result of the subjective preference (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 6. The result of the overall scores of NASA-TLX (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 6. The result of the overall scores of NASA-TLX (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 7. The result of the overall scores of NASA-TLX.
Figure 7. The result of the overall scores of NASA-TLX.
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Figure 8. The result of the mean speed (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 8. The result of the mean speed (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 9. The result of the lane position variation (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 9. The result of the lane position variation (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 10. The result of the total glance time (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 10. The result of the total glance time (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 11. The result of the number of glances (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 11. The result of the number of glances (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 12. The result of the mean glance duration (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 12. The result of the mean glance duration (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Figure 13. The result of the number of glances over two seconds (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
Figure 13. The result of the number of glances over two seconds (with standard error bars). The same alphabetic characters indicate no significant difference with α = 0.05.
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Table 1. Definitions, measurements, and correlations with text legibility and driver distraction.
Table 1. Definitions, measurements, and correlations with text legibility and driver distraction.
IndicatorsMetricsDefinitionsMeasurementsCorrelations
Text legibilityTask completion time (s)Task completion time is the duration from the pseudo-text appearing on the IVIS to when the participant finishes the corresponding reading task (searching for the target character) and presses the ‘next’ button [24,49,50,51,52,53,54,55,56].Post-video analysis−
Number of errors (n)The number of errors refers to the count of times the subject misidentified the target character during the task completion time [24,49,50,51,52,53,54,55,56].Post-video analysis−
Subjective preference (points)Subjective preference was obtained by asking participants to rate how desirable or valuable each of the five CTS conditions was for pseudo-text reading while driving, on a scale of 0 to 10 points [24,49,50,51,52,53,54,55,56].Paper-based Likert scale+
NASA-TLX (points)NASA-TLX is a subjective assessment tool that provides an overall workload score during dual-task and baseline conditions. It requires a weighted average of ratings (0–10 points) across six subscales: mental demand, physical demand, temporal demand, performance, effort, and frustration [24,49,50,51,52,53,54,55,56].Paper-based NASA-TLX scale−
Driver distractionMean speed (km/h)Mean speed refers to the average driving speed observed during both dual-task and baseline tasks [24,49,50,51,52,53,54,55,56].Simulator+
Lane position variation (mm)Lane position variation, also known as the standard deviation of lane position, refers to the degree of lateral position relative to the centerline during both dual-task and baseline conditions [24,49,50,51,52,53,54,55,56].Simulator−
Total glance duration (s)Total glance duration indicates the cumulative glance time spent on the area of interest (AOI), specifically the IVIS screen in this study, during each dual-task under varying CTS conditions [24,49,50,51,52,53,54,55,56].Tobii Pro Lab−
Number of glances (n)The number of glances refers to those entering the AOI during dual-task performance under each CTS condition [24,49,50,51,52,53,54,55,56].Tobii Pro Lab−
Mean glance duration (s)Mean glance duration is the average time each glance spends in the AOI during a dual-task under each CTS condition [24,49,50,51,52,53,54,55,56].Tobii Pro Lab−
Number of glances over 2 s (n)The number of glances lasting over 2 s refers to the mean duration of glances exceeding 2 s during dual-tasking under each CTS condition, which increases near-crash and crash risks by at least two times compared to baseline driving [24,49,50,51,52,53,54,55,56].Tobii Pro Lab−
Note: “−” denotes the negative correlation. “+” denotes the positive correlation.
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Zhong, Q.; Han, R.; Chen, J.; Sha, C. Effects of Chinese Text Size on the In-Vehicle Text Legibility and Driver Distraction: A Simulator Study. Appl. Sci. 2025, 15, 8874. https://doi.org/10.3390/app15168874

AMA Style

Zhong Q, Han R, Chen J, Sha C. Effects of Chinese Text Size on the In-Vehicle Text Legibility and Driver Distraction: A Simulator Study. Applied Sciences. 2025; 15(16):8874. https://doi.org/10.3390/app15168874

Chicago/Turabian Style

Zhong, Qi, Rong Han, Jiaye Chen, and Chunfa Sha. 2025. "Effects of Chinese Text Size on the In-Vehicle Text Legibility and Driver Distraction: A Simulator Study" Applied Sciences 15, no. 16: 8874. https://doi.org/10.3390/app15168874

APA Style

Zhong, Q., Han, R., Chen, J., & Sha, C. (2025). Effects of Chinese Text Size on the In-Vehicle Text Legibility and Driver Distraction: A Simulator Study. Applied Sciences, 15(16), 8874. https://doi.org/10.3390/app15168874

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