In STEM I, we’re conducting a research project based on our own passions and ideas. This starts with a lot of background on your topic of interest. You then develop an idea for your project, and then develop an approach for collecting data!
This project focuses on how the tempo of music affects the speed at which a person drives in a car.
Many individuals listen to some form of audio entertainment while driving. Previous research has shown that different tones of music cause differences in how individuals drive a car. However, the tempo of the music has not been frequently considered, only the tone of the music. In this study, participants drove in a driving simulator to different speeds of music. An experiment was conducted in which a participant drove in the simulator with two different tempos of music. Participants did not participate in highway driving, as to keep the mean speed of the car consistent throughout the simulation. A random sample of speeds at different times in the simulation was collected from each condition, and the means of each sample were found. A two-sample t-test was used to compare the two means (fast music speeds > slow music speeds). Results from this experiment indicated a statistically significant difference in speeds between the two conditions (a= .05, p=2.22*10^-4). This suggests that individuals may tend to drive faster as the tempo of the music increases. This study seeks to investigate whether there is a relationship between the tempo of music and the overall speed of the car.
How does the tempo of music listened to in the car affect the behaviors of the driver in the car?
As the tempo of the music utilized increases, the speed of the car/heart rate will also increase.
Millions of Americans ride in cars every day (Ghojazadeh et. al., 2023). Many of these people also listen to music while riding or driving in a car. In past studies, music has been shown to have an affect on an individual's emotions, and one's emotions have shown to affect how one drives (Chepenik et. al., 2007). What if music, then directly affected one's ability to drive? For example, past research has shown that a driver is more likely to get into an accident while listening to fast-paced music (Pecher et. al., 2009). What if listening to certain types of music was causing individuals to get into car crashes, but this was not cited as the cause of the crash? Could identifying music as a medium that causes car crashes lead to less car crashes occuring, thus leading to safer roadways?
First participants were randomly split into one of three conditional groups. The participants had varying levels of driving experience (license, permit, neither), so they were randomly assigned to the conditional groups within these groups. After, participants came in one at a time and first drove in the simulator for 10 minutes to get used to how it worked. After participants drove in the simulator for 20 minutes to the type of music that they had been assignment to listen to. After all participants had driven in the simulator, I then collected speeds driven by each participant in the simulation and made lists for the speeds collected for each conditional group. After, I compared the three test groups using an ANOVA test.
After data was collected and then placed in Excel, an ANOVA test was used to find evidence of a difference in speeds between the three groups. This test yielded a p-value of .119, (α = 0.05) which does not suggest that there is a difference in speeds between the three groups. However, when looking at the graphs, the range of speeds differed with the type of music utilized with the group. In the Low BPM group (Figure 2), speeds ranged from 0 – 55 MPH. In the no music group (Figure 1) speeds ranged from 0-65 MPH, which is greater than that of the Low BPM group. In the High BPM group, speeds ranged from 0-70 MPH, which is greater than the ranges of speed exhibited by both other groups. While results from this study may not suggest that the speed that a driver drives at overall changes with the type of music they listen to, the graphs suggest that the driver may drive at more varied speeds as the tempo of music increases, since the range of speeds in this experiment increased as the tempo of music increased.
Limitations in this study included time constraints, scheduling conflicts, limited driver experience, technical issues, etc. There were a decent number of participants that signed up to participate in the study, but due to conflicts in participants’ and the researcher’s schedule, many participants were not able to partake in the study. Many drivers that participated in the study were inexperienced drivers and were allowed to drive in the simulator for about 10 minutes before data was collected to learn how to use the simulator properly. When testing began, an issue arose with certain buttons not working on the steering wheel of the simulator, which made it difficult to start the car in the program used to conduct the simulation. However, it was discovered that the keyboard could first be used to turn on the car in the program, and then control was switched over to the steering wheel for participants to use. Confounding variables that were recognized in this study included the age of participants, using music without lyrics, and driver experience. Participants in this study were all about the same age (16 or 17 years old). Music with lyrics were not used, as lyrics are another layer to a song. Drivers had varying levels of driving experience, so groups were stratified in order that each group had participants with varying levels of driving experience. An ANOVA test was conducted on the data, since the goal of the study was to determine if there was a significant difference between the means of car speeds between test groups. Since there were more than 2 test groups, an ANOVA test was utilized. Studies such as the ones conducted by Brodsky in 2002 and Groene and Barrett in 2012 focus on music as a distractor with various groups of people (Brodsky 2002) (Groene and Barrett, 2012). However, these studies do not focus directly on how the change in the tempo of music affects the speed of a car during a simulation.
Since this study was conducted in a simulation, it may be beneficial to also reproduce this study in a car as well, since it allows participants to put in a real-life environment instead of a simulated one. Also, this study aimed to address how music affected driving behaviors, while more research should be done to discover why these behaviors happen, as this can lead to more accurate recommendations that can help lower the amount of potential music-related car crashes. This includes looking at factors such as eeg readings, heart rate, galvanic skin response, etc. This study could also be expanded to multiple age groups, since testing was only done with teens in between the ages of 16 and 17. One other factor that could be looked at in the future in the music that was used. While this study used two different types of music (one for the Low BPM condition, one for the High BPM condition), the same music could be used for both conditions in the future, it simply could have been sped up or slowed down. This would keep the music used in the study consistent throughout. Also, testing should also be done with music with lyrics to see how this affects the behaviors of drivers as well.
This study aimed to discover how music affected the speed of a car while drivers listened to different types of music. This was accomplished by having three groups of drivers drive in a driving simulator with either Low BPM music, no music, or High BPM music. An ANOVA test was conducted on results, and although significant results were not found (*p = .119, α = .05), the graphs showed increasing variability in the data, hinting that more research must be done before reaching a definite conclusion. If future research leads to significant results, this could help to lower the amount of car crashes on the road, leading to safer roads for everyone.
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