The effects of transportation noises such as road traffic noise (RTN), railway noise and aircraft noise on humans have long been recognized, and the relationships between noise exposure and human responses have been investigated [1
]. Out of these transportation noises, the road traffic noise generated by vehicles was one of the major sources. Many studies have revealed that RTN induces adverse effects on human responses such as annoyance [3
], sleep disturbance [14
], and other non-auditory reactions [23
]. Of course, among the RTN, the noise of travelling vehicles is dominant, and it comprises honking sounds as well. Several countries face noise problems caused by horn use. A report on the RTN in urban areas of Vietnam, for example, showed frequent horn honking as a major factor of RTN [28
]. A report on the RTN at urban rotaries in India found that heavy vehicles and their honking more significantly affected the equivalent continuous A-weighted sound pressure level (LAeq
) than other vehicle types did [29
]. Another study in India also revealed that frequent honking increased from 2 to 5 dB in LAeq
]. According to research on the RTN in Iran, the model estimating LAeq
using factors including traffic flow, vehicle speed, and horn noise indicated that the honking frequency contributed to the increasing LAeq
and maximum noise level value (LAmax
The situations in which drivers should use horns are stated in the traffic regulations of various countries. Road Traffic Act in Japan [32
], for instance, states that a vehicle horn should be used only in an emergency or in dangerous locations where there is a sign allowing horn use, such as on a blind curve. However, there are many situations in which a horn is used other than those mentioned above. Although this is not a serious problem in Japan, such horn use evokes negative reactions from pedestrians and residents.
Horns were originally installed in vehicles for safety. Horn sounds are therefore designed with high sound pressure levels to alert drivers of danger in noisy environments. However, vehicle interior and exterior noises are quieter than they used to be when standards stating the acoustic characteristics of horn sounds were established. Horn sounds should therefore fulfil functions even if they have lower sound pressure levels. Concerning the current sound pressure level of a horn sound, the Automobile Standard Harmony World Forum in 2014 proposed regulations on the acoustic characteristics of horn sounds [33
] in which the upper limit of the sound pressure level was maintained while the lower limit was reduced. Such a revision of the regulations will not mitigate noise problems relating to honking because horn sounds with high sound pressure levels will still be generated on roads. As long as the current horn system is used, in which the horn sound is emitted outside a vehicle at a sound level loud enough to be heard by drivers inside their vehicles, the noise problem will not be improved by the acoustic design of a horn. Therefore, the control of horn use is supposed to be more effective to drastically improve the noise problem of horn use. To reduce the RTN, including horn sounds in urban areas of Indonesia, the ridesharing or car-pooling policy to reduce the number of vehicles, and the similar policy for motorcycles and the prohibition of vehicle horn use, were examined for actual measurement results of the RTN [34
]. Through the combined application of these programs, the maximum reduction in LAeq,10min
was estimated to be 3.9 dB. The result revealed that the prohibition of horn use was not so effective.
In controlling driver horn use, it is necessary to identify the factors affecting driver horn use. Various intrinsic and extrinsic factors are assumed to influence driver horn use. Driver horn use is considered an indicator of driver aggression [35
]. In Scandinavia, the use of horns is generally regarded as a manifestation of driver aggression, whereas the threshold for horn use is lower and not necessarily regarded as such in Southern Europe [36
]. Fujii has proposed a socio-psychological model representing driver traffic behaviors [37
]. In this model, a certain traffic behavior is assumed to be caused by behavioral intention, which is related to psychological factors such as personal norm and moral obligation. From these studies, driver horn use can be considered one of the traffic behaviors and is influenced by the intrinsic (psychological) factors of the driver. A study conducted in South Korea investigated the relationship between driver awareness of their horn use and the manner of its use [38
]. It was suggested that drivers who do not normally use horns are reluctant to use them, and that they sound a short horn when necessary to warn other drivers of danger or for the purpose of alerting them.
Furthermore, another study conducted in Japan reported that the honking patterns of horn use were related to location and traffic volume [39
]. The results suggested that driver horn use is influenced by extrinsic factors (i.e., situations). Based on these findings, we assumed a similar behavioral model in which intrinsic and extrinsic factors influence behavioral intentions and induce specific traffic behaviors, including the use of a horn. To address the horn noise issue, a comprehensive understanding of the intrinsic and extrinsic factors that lead drivers to use their horns is needed.
The main purposes of the present study were to find the extrinsic factors of driver horn use, such as the behavior of other drivers and the traffic environment, and to propose the countermeasure to reduce driver horn use. Although the actual road conditions and situations surrounding drivers are complicated and change continuously, the relationship between the occurrence of horn use and the traffic environment was investigated. As a case study, measurements and recordings of horn use and the current circumstances of traffic were conducted at urban intersections in Taiwan [40
]. We found traffic features at intersections and relationships between the extrinsic factors, such as traffic count and traffic signals, and driver use of horns. A microscopic analysis was then conducted to examine the quantitative parameters of the traffic environment related to driver horn use [41
]. As a further study, this paper analyzes the effects of vehicle horn use and the traffic environment on the acoustic environment around intersections, i.e., LAeq
at the measured point at intersections. Furthermore, based on the results obtained, countermeasures to improve the acoustic environment and to reduce drivers’ use of their horns will be discussed. To approach these points, important data on the vehicular environment [40
] are restated in this paper.
4.1. Relationship between Traffic Volume and Horn Honking
The macroscopic analysis using the traffic counts were firstly carried out [40
]. Correlation analysis between the total traffic volume and the frequency of horn use was examined at each intersection on each day of measurement. On weekdays, there was no significant correlation at any surveyed site (Intersection 1: r
= 0.16, Intersection 2: r
= 0.28, and Intersection 3: r
= 0.02). On the weekend, significant correlations were obtained at two sites (Intersection 1: r
= 0.72, p
< 0.01; Intersection 2: r
= 0.57, not significant; and Intersection 3: r
= 0.90, p
presents the coefficient of correlation between the traffic volume of each vehicle type and the frequency of horn use. The results show significant correlations between the standard-sized vehicle traffic volume and the frequency of horn use on the weekend at all intersections and on the weekday at Intersection 2. The traffic volume of motorcycles significantly correlated with the frequency of horn use only at Intersection 3 (r
= 0.90, p
< 0.01). On weekdays, however, there was no relationship other than that for standard-sized vehicles at Intersection 2.
shows scatter diagrams of the total traffic volume and the frequency of horn use during the measured 10 min in each hourly time zone, where the numbers next to data points represent time zones from 7:00 to 19:00. The frequency of horn use approximately increased as the total traffic volume increased at all surveyed sites. Such tendencies become clearer when removing the data for rush hours on weekdays (i.e., 8:00 and 17:00 or 18:00), in particular, at Intersections 1 and 3. As mentioned above, a high traffic volume during rush hours is supposed to relate to a high volume of motorcycles. The correlation between the total traffic volume and the frequency of horn use was analyzed using the data for weekdays and weekends with the data for rush hours eliminated (i.e., data for 9 h on a weekday and 12 h during the day on a weekend). Significant relationships were obtained for Intersections 1 and 3 (Intersection 1: r
= 0.71, p
< 0.01; Intersection 2: r
= 0.35, not significant; and Intersection 3: r
= 0.77, p
To investigate the effect of the characteristics of the intersections on horn use, the relationship between the total traffic volume per lane at each intersection (i.e., the total traffic volume during the recorded 10 min of each hourly time zone was divided by the number of lanes entering the intersection) and the frequency of horn use was examined. Figure 5
shows scatter diagrams for the total traffic volume per lane and the frequency of horn use during the recorded 10 min in each hourly time zone. The result for the total measurement time, including rush hours, is displayed in Figure 5
a, while the result obtained when removing the data for rush hours on weekdays is displayed in Figure 5
b. These figures in Figure 5
show positive relationships between the frequency of horn use and the traffic volume per lane. Both relationships were statistically significant (Figure 5
= 0.63, p
< 0.01; and Figure 5
= 0.74, p
< 0.01). However, the linear relationship of the result for which the data of rush hours were eliminated in Figure 5
b was clearer than that for the total measurement time.
The linear relationship between the traffic volume and the frequency of horn use would suggest that horn use should be frequent during rush hours, but in fact, horn use was not as frequent. The results suggest that the situations in which drivers need to use their horn are unlikely to occur during rush hours.
Furthermore, scattered data for each intersection are distributed within a certain range of the traffic volume in Figure 5
b. The results for Intersection 2 (indicated by triangles) are distributed at large numbers of horn use and high traffic volumes. Conversely, the results for Intersection 3 (indicated by crosses) are oppositely distributed in the figure. This suggests that the characteristics of the intersections, such as locations in the city, connections with roads, and the number of lanes, affect horn use.
4.2. Horn Honking during Traffic Signal Cycles
The situations in which horn sounds were generated during the traffic signal cycle were analyzed [41
]. Table 6
shows the frequencies of horn use, which were observed during each green light phase for all measured time periods (the total duration of each green light phase during a 10 min × 12 h period). The horn honking was generally more frequent on weekdays than on weekends. At Intersection 1, drivers used their horns more frequently in phases I and II. At Intersection 2, they used horns more frequently in phases other than phase II. At Intersection 3, horns were used more frequently in phases II and III than in other phases.
The duration of the green lights varied by phase, date of measurement, and intersection (Table 2
). Therefore, the duration of horn sounds counting was equalized to 10 min periods. The frequency of horn use during the 10 min periods was estimated from the frequency of horn use within 1 s span measures that were averaged in each of the four green light phases throughout all measured time periods and measurement days (a 10 min × 12 h × 2 day period), as shown in Figure 6
. Table 7
gives the estimated frequencies of horn use. At Intersection 1, the frequency of horn use is high in phases I and II. At Intersection 2, horn use frequency is higher in phases other than phase I. The overall frequency of vehicle horn use at Intersection 3 was low, but relatively high in phases I and IV compared to other phases.
During the green light phases, where the estimated frequency of horn use was higher, left-turn traffic was allowed, as was straight traffic, as shown in Figure 2
. Video data analysis revealed many instances where vehicles entering the intersection to make a left turn during a green light phase began honking their horns. Therefore, we examined in detail the causes of horn use in green light phases when left turns were possible.
4.3. Analysis of Causes of Horn Use in Green Light Phases When Left Turns Were Possible
To explore measures to reduce horn honking, we conducted a microscopic analysis of how drivers use their horns [41
]. Video data were analyzed in detail for instances where horns were used during signal phases allowing left turns (specifically, phase II at Intersections 1 and 2 and phase IV at Intersection 3). First, we categorized the situations in which vehicle horns were used into four types: (1
) cutting in line, (2
) slowness, (3
) sudden stops, and (4
) stopping state. Situation (1
) is a circumstance in which a driver of a car who interrupted the line to make a left turn was honked at by the driver of another car. Situation (2
) refers to a circumstance where a driver of a car driving slowly was honked at by another driver. Situation (3
) is a circumstance in which a driver had to stop suddenly because the vehicle in front of them stopped, and they used their horn. Situation (4
) refers to a circumstance in which a driver honked at another car that remained stopped at the stop line even though he/she could turn left after the green light turned on. Table 8
shows the number of these situations in which drivers used their horns during the above phases of the entire measurement period. Excluding the situation where the cause of horn use was unclear (situation (5
)), horn use was frequently found in situation (4
) (stopping state situations) at each intersection.
Next, regarding situation (4
), the duration from when the light turned green until the car in front of the stop line started moving (the start delay time) was measured using video data, and then the start delay times were compared between when a horn was used and when a horn was not used. Intersection 1 had two lanes for left turns. Therefore, the same analysis was performed in each lane at this intersection. Table 9
presents the mean start delay times with and without horn use at each intersection. The mean start delay times were over 4 s when horn use occurred, but only about 2 s when horn use did not occur. T-test results revealed significant differences of the mean start delay times. The results suggest that delayed departure of the vehicle in front is one of the major causes of driver horn use at intersections.
4.4. Noise Level in Situations with and without Honking
A previous study employed the noise prediction model to estimate the effects of honking on the acoustic environment [44
]. However, in the present study, a single-point measurement was conducted because it was considered that such a simple measurement would be sufficient to approximately determine the impact of horn use on the acoustic environment near intersections (or the difference between when the horn use occurred and when it did not occur) without using noise maps or other prediction methods.
To determine the impact of horn use on the acoustic environment around intersections, we calculated the equivalent continuous A-weighted sound pressure level (LAeq,10min
) and the maximum noise level (LAmax
) of the RTN, both with and without the use of horns, by vehicles. Data management software (RION AS-60) was employed to calculate the LAeq,10min
without the use of horns. The data for horn sounds were removed from the initial data, and then both acoustic indices were recalculated. Figure 7
displays the variations in total traffic volume and LAeq,10min
during the measurement time for each intersection and each measurement day. The similar results for LAmax
are displayed in Figure 8
Significant relationships between LAeq,10min and total traffic volume were found for all measurements, except one weekday at Intersection 1 (Intersection 1: rweekday = −0.05, not significant; rweekend = 0.81, p < 0.01; Intersection 2: rweekday = 0.87, p < 0.01; rweekend = 0.76, p < 0.01; and Intersection 3: rweekday = 0.62, p < 0.05; rweekend = 0.85, p < 0.01). Although the values of LAeq,10min when the noise level data of honking were removed were very similar to those when such data were not removed, LAmax sometimes decreased when the noise level data of honking were removed in situations when LAeq,10min values were relatively low.
4.5. Relationship between Noise Level and the Traffic Environment
To clarify the effects of vehicle horn use and traffic environment on the acoustic environment around intersections, multiple regression analysis was performed with LAeq,10min as the dependent variable and the honking frequencies, as well as the traffic environmental factors, such as the traffic volumes of the three vehicle types, total number of entry lanes, and total number of exiting lanes in each intersection, as the independent variables.
As a result, an index of multicollinearity suggested that the variable “total number of entry lanes” was correlated with the other variables. Therefore, this variable was excluded from the independent variables and an analysis was conducted using five variables. Table 10
presents the obtained result. According to this table, the variable “traffic volume of motorcycles” was statistically significant (p
< 0.001). The result reveals that LAeq,10min
increases with the traffic volume of motorcycles. Neither the traffic count of standard-sized vehicles nor their horn use appears to have any effect on the acoustic environments of intersections.
A similar analysis was conducted for LAmax
. The dependent variable was LAmax
and the independent variables were the honking frequencies and the traffic environmental factors mentioned above. As a result, because multicollinearity problems also arose in this analysis, the variable “total number of entry lanes” was excluded. Table 11
shows that the significant variable is the “honking frequency” only and suggests that LAmax
increases with the frequency of honking.
Our measurements and recordings of horn use and current circumstances of traffic at three intersections in Taipei city, Taiwan suggested that LAmax significantly increased with frequency of honking, although no effect of horn honking on LAeq was found. In terms of LAeq, driver horn use did not affect the acoustic environment at the surveyed sites. Here, reducing the amount of small motorcycle traffic would be most effective. However, horn sounds are audible when noise levels are relatively low. Therefore, reducing the use of deafening horn sounds could be effective for improving the acoustic environment around intersections.
The present study indicates the relationship between standard-sized vehicle traffic volume and frequency of horn use. The results also suggest that the characteristics of the intersections, such as connections with roads and number of lanes, were related to horn use. An analysis of honking frequency during traffic signal cycles showed that honking was more frequently observed during the green light phases allowing left turns than in other phases. Video data analysis regarding the instances of honking during such green light phases appeared to show that horn use was frequently found in “stopping state” situations in which a vehicle at a stop line did not immediately start moving after a green light was turned on to allow a left turn, inducing another driver’s horn use. In such situations, the mean start delay times when drivers used their horns were significantly longer than those when they did not. To prevent vehicle start delays and reduce driver horn use, measures to direct the attention of stopped drivers to traffic signals would be necessary.
If the next-generation mobility (e.g., self-driving vehicles) is widely introduced into society and traffic conditions improve, the current horn system may no longer be needed. However, until such a dream is realized, the current system will be maintained. This study is expected to provide useful information for such current situations.