In traffic psychology, HP refers to subjective assessment of the degree of harm caused by traffic accidents, which can affect drivers’ behavioral decisions (Deery, 1999; for example, evaluating dangerous behaviors such as running red lights.). A driver’s perception of danger is affected by driving experience and age. For example, driving experience can improve a driver’s ability to perceive danger (Deery, 1999; Rosenbloom et al., 2008). In addition, some studies believe that negative emotions such as fear and anger can also affect drivers’ perception of danger (Lu et al., 2013).

Some studies have found an antithetical relationship between perceived hazards and dangerous driving behavior. In other words, the stronger the driver’s HP ability is, the less likely he will engage in dangerous driving behavior (Machin and Sankey, 2008; Mills et al., 2008). Besides, the researcher (Ma et al., 2010) further suggested that risk perception may not directly affect drivers’ driving behavior. For example, the researchers used risk perception scales to measure participants’ attitudes toward traffic accidents (for example, how much you care about a traffic accident which might hurt others) and found that perception of danger has an indirect effect on speeding behavior. Moreover, HP moderated the relationship between age, and dangerous driving (Rhodes and Pivik, 2011). In simpler terms, HP is more suitable for predicting dangerous driving in older adults than in young adults.

To sum up, dangerous driving behaviors can be effectively reduced by improving drivers’ danger perception ability, thus improving road driving safety. Therefore, the relationship between HP, affective states, and age needs further study.

Driving emotion (Steinhauser et al., 2018; Kadoya et al., 2021b) is crucial in traffic safety, which can cause dangerous driving behaviors by influencing drivers’ cognition, attention, judgment, and behavior (Steinhauser et al., 2018; Kadoya et al., 2021a). For example, for some drivers who take driving for pleasure, driving itself can be enjoyable and generate positive emotions during driving (Sheller, 2004). Studies have shown that driving in positive emotions, such as letting the guard down and playing with friends, can lead to dangerous driving behavior (Møller and Gregersen, 2008). However, there are opposing views that positive emotions have been found to promote more flexible, creative thinking and action, thus may enhance creativity associated with perceived danger (Isen, 1987; Lyubomirsky et al., 2005).

However, positive emotions are rarely used in road traffic environments and are considered unable to effectively awaken drivers’ awareness of vigilance (Lewis et al., 2007). To keep drivers on high alert in road traffic safety, negative emotions dominated by fear, tension, and worry are often used (Lewis et al., 2008). Obviously, it is important to use negative emotions on the traffic road. Despite this, some studies (Elliott, 2003) suggest that the use of negative emotions should be cautious, because the arousal of fear is stimulating and inhibiting, which may lead to defects in coping mechanisms in road traffic safety. Many studies have found that fear produces adverse reactions (Schoenbachler and Whittler, 1996; Witte et al., 1998; Orit Taubman Ben-Ari and Mikulincer, 2000). This kind of adverse reaction shows that in order to cope with the unpleasant feelings caused by the prompt information, they defensively ignore the prompt information, but do not control or eliminate the potential threat implied in the message. In addition, some people in fear may perceive the prompt as a self-challenge, reducing the perceived level of danger while the actual level of danger remains the same, leading to dangerous driving behavior. Therefore, scholars suggest that negative emotions such as fear should be carefully used in road traffic safety, and other types of emotions should be considered (Wundersitz et al., 2010). Whereas, when people are in a negative emotional state, they may process information more carefully (Schwarz et al., 1991). If warning signals intend to convey information about safety or danger, then negative emotions may promote the cognitive process of danger perception. As a result, it’s not clear which emotions are better for driving.

In addition, there seems to be a gender gap in positive emotions among young drivers: Young male drivers are more enjoy driving than young female drivers, according to a study of driving attitudes (Harré et al., 1996), and male drivers are more affected by positive emotions, which may explain why they are more likely to drive dangerously (Rhodes and Pivik, 2011).

If drivers’ danger perception ability is affected by emotions and age, then road traffic signs should be designed to eliminate and avoid the influence of these factors when conveying potential threat information. The effect of emotion and on the perceived danger of warning messages is unclear. Therefore, it is necessary to further study how young drivers perceive and process warning messages in different emotional states.

Another issue worth paying attention to is whether age differences exist in people’s processing and response to information under different emotional states. Young drivers (15 to 25 years old) drive unsafe more often than older age groups, research has also found that young drivers’ driving performance is linked to cognition (Di Meco et al., 2021). The elderly have a higher emotional happiness index and less negative emotional experience than young people (Mikels et al., 2005; Reed and Carstensen, 2012; Gronchi et al., 2018). In the process of processing emotional information, the elderly pay more attention to positive emotional information than negative emotional information, that is, the “positive effect” of the elderly. This is also true in memory research (Mather and Carstensen, 2003; Comblain et al., 2005; Spaniol et al., 2008; Scheibe and Carstensen, 2010).

Two models of cognitive-affective aging: social-emotional selectivity theory (Carstensen et al., 1999; Mikels et al., 2005) and dynamic integration theory (Labouvie-Vief, 2003, 2005, 2009; Labouvie-Vief et al., 2009) explain the positive effects.

On the one hand, SST is a life-span development theory related to motivation (Mather and Carstensen, 2003), assuming that goal selection follows adulthood. SST proposes a choice of goals throughout adulthood. Some goals involve preparing for the future, such as accumulating knowledge and meeting new friends; Other goals are related to satisfying the present life, such as enjoying intimacy and pursuing emotional satisfaction. While these goals are important over the course of life, SST places great emphasis on the negative correlation between age and future time horizons. Young people tend to perceive that the future is vast, prioritizing preparation for the future, spending more time and energy building social networks and increasing knowledge reserves to cope with an uncertain future; older adults seek to meet the emotional satisfaction of the present when they perceive the limited time in the future (Sims et al., 2015). However, when the elderly are getting older or perceive that time in the future is limited, the pursuit of emotional satisfaction takes precedence over other goals (Sims et al., 2015). The positive effect theory of SST extension theory proposes that the larger the age span of the two study groups, the easier the positive effect will be detected (Charles and Hong, 2015).

On the other hand, DIT suggests that this is an automatic process of cognitive decline due to aging (Labouvie-Vief, 2003). This theory suggests that older adults have difficulty managing cognitive-affective complexity due to the limitations of age-related cognitive resources. The theory believe that positive information is easier than negative information, and older people use fewer cognitive resources to process positive information. The elderly face the decline of cognitive resources and thus compensate for the processing of information in a simple, positive way, that is, the automatic processing of positive emotional information. Automatic processing of positive emotional information is an adaptive attentional mechanism (Labouvie-Vief, 2009), when it is associated with negative emotions such as pain and threat, it automatically preserves cognitive processing by eliminating emotional stimuli. Therefore, the positive effect of emotion processing on the elderly is minimal automatic emotion processing. The above studies showed that older people prefer positive emotional processing, while younger people do not have this preference or prefer negative emotional processing (Kennedy et al., 2004).

Both SST and DIT explain differences in emotional processing in the elderly. Positive information processing stabilized or improved with age, while negative information processing decreased with age (Carstensen et al., 1999; Labouvie-Vief, 2003). While the role of attention in each theory may lead to different assumptions. SST believes that the positive effect depends on the later attention process, which is passively controlled, while DIT believes that the positive effect depends on the early attention process, which is processed automatically.

Studies have shown that increased attention to negative material among young people leads to age-related differences in the direction of attention (Charles et al., 2003; Ready et al., 2007; Shamaskin et al., 2010). And the elderly showed a stimulative effect of attention on positive (as opposed to negative) information (Isaacowitz et al., 2006; Mather and Knight, 2006).

In conclusion, young drivers and old drivers prefer different emotional information (positive or negative), however, different emotional stimuli will guide older drivers and young drivers to judge and make decisions differently (Taubman-Ben-Ari, 2012). What is more, the influence of emotion on HP of young and old drivers is still unclear. Therefore, it is necessary to further study the influence and effect of emotion on different driving groups.

At present, studies on dangerous driving mainly focus on young drivers and adult drivers, but as China continues to enter an aging society, there are more and more older drivers. Therefore, We need to further explore the HP ability of young and old drivers in different emotional states. Therefore, this study explores the following questions:

In this study, we used the method of listening to music while recalling imagination (Kuhbandner and Zehetleitner, 2011; Larson et al., 2013; van Steenbergen et al., 2014) to wake up the emotions of the participants. The Self-Assessment Manikin (SAM; Morris, 1995) questionnaire was used to assess their emotional valence (EV) and emotional arousal (EA), and evaluated their emotional state at that time from these two dimensions. A five-point scale questionnaire (Kalsher et al., 1995) was adopted to ask the participants to score the HP of 22 traffic warning signs. We hypothesized that emotions have a significant impact on drivers’ HP, and drivers’ HP is higher under negative emotions; the influence of age and emotion on HP is interactive, young people have higher HP under negative emotion, while old people have higher HP under positive emotion.

We designed a 3 (emotion: Negative, Neutral, and Positive) × 2 (age: young group, old group) mixed experimental design. Emotion and age are independent variables, the former is a within-participants variable and the latter is a between-participants factor. The dependent variable was the self-assessment of the HP of traffic warning signs. The framework for experimental design is shown in Figure 1.

We recruited 14 young drivers with an age range of 21 to 24 (M = 22.21, SD = 1.05) and 13 older drivers with an age range of 50 to 60 (M = 54.08, SD = 2.72). There were nine men and five women among the younger drivers, and twelve men and one woman among the older drivers. The young drivers are undergraduate students from Ningbo University. The older drivers are didi ‘s express drivers (Non-professional driver), as long as they meet the application requirements (age: 22–60; Driver’s license C2 or above for express; Driving experience more than 1 year; and Drivers with a total mileage of less than 100,000 km) can apply through Didi’s express drivers. These drivers usually pick up customers on the way home and earn part of the fee, which does not have the same positive feelings toward customers as professional drivers.

In order to control the driver’s driving experience at a similar level, we first measure the driver’s driving activity level (driving age, weekly driving frequency, driving mileage, and the number of traffic accidents) through questionnaires. Drivers with driving experience of more than 1 year and less than 2 years, driving frequency of three times or more per week, total mileage of 10,000 or so, and no traffic accidents were selected and invited as participants to participate in the experiment, so as to avoid the influence of driving experience as the intervention variable. The gender composition of the two groups was not deliberately controlled, but the result of random invitations. All participants had normal or corrected visual acuity and were not color blind.

According to the mixed experimental design, we randomly divided participants into three (Negative, Neutral, and Positive) emotion groups, repeatedly arousing three different emotional states over different time periods. Each participant completed the experimental tasks measured by the questionnaire in three different emotional states.

G* Power (Faul et al., 2007) was used for prior power analysis. Under the conditions of standard effect size f is 0.4 (large), significance level of 5% and power of 80%, the total sample size required was 64. Therefore, the minimum sample size of young (old) drivers should be 11.

To exclude the influence of incomprehensibility on the participants’ self-assessment of perceived hazard. We measured the understanding of Chinese road traffic warning signs stipulated in Road Traffic Signs and Lines (GB5768) and selected the signs with an understandable level of 70% as experimental materials for the questionnaire. In order to avoid and reduce the weariness caused by too many questions in the traffic warning sign comprehension experiment, we randomly selected one of the signs with opposite directions but the same meaning. For example, “turn left” or “turn right” were randomly selected as test signs in the traffic sign comprehension experiment, as shown in Figure 2. Participants would see one of the signs and fill in its meaning in the experiment. This preliminary screening method can not only avoid subjective exclusion but also reduce the number of questions to a certain extent.

Finally we selected 43 triangular warning signs (as shown in Figure 3) from the 77 road traffic warning signs stipulated in Road Traffic Signs and Lines (GB5768) as the test signs of the experiment.

Remove the text message of the 43 signs, and only the logo image was retained and printed in color on A4 white paper. Each page had 6 signs with a size of 2 cm × 2 cm. At the top of the questionnaire, we used a description of the “Yield pedestrian” sign as a reference.

We invited 10 people (including inexperienced, novice, and skilled drivers) to participate in the traffic warning signs comprehension experiment. The participants ranged from 21 to 45 years old (M = 25.4, SD = 6.98). All participants had normal or corrected visual acuity, were not color blind, did not participated in similar experiments recently.

After simply informing participants of the purpose and process of the experiment, we asked them to write down their understanding meanings under the 43 traffic warning signs on the paper questionnaire as detailed as possible. The experiment lasted about 30 min.

To evaluate the fairness, two independent raters gave corresponding comprehension scores for the meaning description written by the participants according to the scoring criteria of the open questionnaire scale, as shown in Table 1. Cronbach’s alpha coefficient value of the scale was 0.96, indicating high reliability of the scale (Duarte and Rebelo, 2005).

Descriptive statistics of the comprehensible rate of 43 signs are shown in Table 2.

The understanding rates for all signs ranged from −40.0% (Sign 17 — split road) to 100% (Sign 1 — crossroads), with an overall mean (±standard deviation) of 60.0% (±25.83%) understanding rates for all signs. Ten signs had an understanding rate of greater than 85% as recommended by ANSI Z535.3, 2002, and 15 signs had an understanding rate of between 67 and 85% that is considered acceptable by ISO 3864-3, 2006 (a sign understanding rate of greater than 67%). Among them, the “low-lying road” sign, “high-protrusion road” sign, and “uneven road” sign have similar meanings, so the low-lying road sign with the highest understanding rate is retained. Although the understanding rate of the “Watch out for wild animals” sign reaches 80.0%, it is not common in daily traffic roads, so we removed it. After the sign comprehension test, we screened out 22 road traffic warning signs meeting the requirements, as shown in Figure 4.

The participants data were emotional state data from the SAM scale and self-rated HP data from the HP questionnaire. 6 questionnaire data from the young drivers and 3 questionnaire data from the old drivers were excluded from the analysis due to the significant difference in the EV of the participants before and after the experiment. We used SPSS 19.0 data analysis software to analyze the data of all participants.

One-way analysis of variance was used to compare the differences in EV and EA scores between different emotional groups, so as to judge whether the emotions of the subjects were successfully aroused.

In the emotion data before starting to fill out the HP questionnaire score (EV 1and EA1), emotion was significant for EV1 score [(F (2,69) = 247.54, p < 0.001)] and EA1 score [(F (2,69) = 9.40, p < 0.001)]. Post hoc Comparison analysis showed that the EV1 score of the negative emotion group (M = 2.08, SD = 1.06) was significantly lower (p < 0.001) than those of the neutral emotion group (M = 5.67, SD = 0.71), and also significantly lower (p < 0.001) than those of the positive emotion group (M = 7.38, SD = 0.71). The EV1 scores of participants in the neutral emotion group were significantly lower (p < 0.001) than those in the positive emotion group.

Similarly, the EA1 scores of the negative emotion group (M = 5.12, SD = 1.12) were significantly lower (p < 0.001) than those of the positive emotion group (M = 6.42, SD = 1.14), and also significantly lower (p < 0.001) than the neutral emotion group (M = 6.25, SD = 1.11). However, there was no significant difference in EAl score between neutral emotion group and positive emotion group (p > 0.05), indicating that all participants were in a state of high arousal. These results confirm that we successfully evoked the corresponding emotional states in each group of participants.

In the emotion data after filling out the HP questionnaire (EV2 and EA2), emotion had significant effect on the EV2 score [F (2,69) = 152.91, p < 0.001], and the post hoc analysis showed that the EV2 score of the negative emotion group (M = 2.63, SD = 1.01) was significantly lower (p < 0.001) than that of the neutral emotion group (M = 5.33, SD = 0.76), and also significantly lower (p < 0.001) than that of the positive emotion group (M = 7.13, SD = 0.90). The EV2 scores of participants in the neutral emotion group were significantly lower than those in the positive emotion group (p < 0.001). But the EA2 score [F (2,69) = 0.87, p > 0.05] was not significant. It showed that after the completion of the test task, although the arousal degree of the three groups was at a medium level, the participants still maintained the corresponding emotional state.

The effects of emotion and age on self-assessed HP were analyzed using two-factor repeated variance measures. The results of two-factor repeated variance measures shown below: Firstly, the main effect of emotion was significant [F (2,66) = 6.520, p = 0.003], which means that emotion had a significant effect on self-assessed HP. Further analysis showed that the negative emotion group (M = 3.20, SD = 0.10) perceived more harm (p = 0.002) than the neutral emotion group (M = 2.75, SD = 0.10), and the positive emotion group (M = 3.15, SD = 0.10) also perceived more harm (p = 0.005) than the neutral emotion group. In other words, in the neutral emotional state, the participants perceived the lowest perceived hazards. Results of paired comparison of emotions analysis are shown in Table 4.

The main effect of age was not significant, age had no significant effect on self-assessed HP, but the interaction effect of emotion and age was significant [F (2,66) = 9.18, p < 0.001]. Furthermore, simple effect analysis showed that the self-assessed HP of the young group was higher under negative emotion than under neutral emotion (p = 0.001) and positive emotion arousal (p = 0.002). In other words, the self-assessed HP of the young group was the highest under negative EA. For another, elderly group participants under the condition of positive emotion awaken was higher than in negative emotion awakened self-assessment HP (p = 0.008) and neutral emotion awaken self-assessment HP (p < 0.001). In other words, the older group participants had the highest HP in self-assessment under positive emotional conditions. Finally, when both groups were in positive EA, younger drivers perceived significantly fewer hazards than older drivers (p < 0.001). Results of simple effect analysis are shown in Table 5.

Emotion of the participants’ self-assessment HP research results show that emotion significantly influences participants’ self-assessment of HP. Further analysis found that the negative and positive emotion groups are perceived more harm than the neutral emotion group, in other words, participants had the lowest HP under neutral emotion. Emotion and gender of the participant’s self-assessment HP research results show that both the neutral and positive emotion groups perceived less harm than the negative emotion group. In other words, participants in the negative emotional group perceived the highest levels of HP. The results of both indicated that negative emotions increased participants’ self-assessed HP.

Excluding the effect of sign familiarity, this may be because negative emotions may encourage people to process information more carefully (Schwarz et al., 1991). If warning signals intend to convey information about safety or danger, then negative emotions may promote the cognitive process of perceived danger. When the drivers in negative emotional conditions saw these traffic warning signs, the negative emotional condition might encourage them to observe the information conveyed by the warning signs more carefully and focus most of their attention on the details of the related HP. This may explain why participants perceived the most danger under negative emotions.

Under the negative emotion arousal condition, the younger group perceived more harm than the older group, while under the positive emotion arousal condition, the older group perceived more harm than the younger group. This may be because young people have a negative bias in emotional selection while older people have a positive bias (Gronchi et al., 2018). When the young group was in the arousal state of positive emotions, they might avoid positive emotions and inhibit the processing of positive warning signs in the visual processing stage. However, when young people see these traffic warning signs in the state of negative EA, they will focus on the information of negative warning signs, thus generating attention and memory, and negative emotions may encourage people to be more careful in information processing (Schwarz et al., 1991), and focus most of the attention on the relevant HP details (Clore and Palmer, 2009).

The “positive warning sign” here refers to the fact that if a warning traffic sign is designed to convey positive emotions, this may potentially affect the young driver’s perception of danger. For example, a traffic warning sign used to convey the accident-prone road ahead is depicted as a warm home picture, rather than a serious impact and rear-end collision. This can be called a positive warning sign and may have a revelatory effect on the design and application of road traffic warning signs for older drivers.

Dynamic integration theory holds that emotions and cognition are related. According to this theory, positive information is more straightforward than negative information, and people will use fewer cognitive resources to process positive information. Compared with young people, older people will have reduced cognitive resources. The cognitive load capacity decreases and compensates for the preference of positive emotion processing and receiving information and evaluates external objects simply and positively, that is, automatic processing of positive emotion information (Labouvie-Vief, 2009). While positive emotions could influence people to think, feel, and act creatively (Lyubomirsky et al., 2005). When the elderly drivers were in a positive emotional state and saw these traffic warning signs, creativity associated with danger perception may be improved (Isen, 1987). This may reasonably explain why young drivers with negative emotions have higher HP of road traffic warning signs, while older drivers with positive emotions have higher HP of road traffic warning signs.