*3.1. Drivers' Faults Analysis*

The analysis of the available accident data for both rural and suburban roadway segments for the years 2014–2018 is shown in Table 1 below. The analysis revealed that three of the drivers' faults listed in Table 1 were responsible for almost 73% of all reported crashes. Lane departure (25.95%), distracted driving (24.19%), and tailgating (22.79%) were the top driver faults causing crashes. In fourth and fifth places came traffic rules violation (9.6%) and wrong-way driving (8.21%). The remaining driver faults, listed in Table 1, were responsible for less than 10% of reported crashes. Moreover, the analysis of the severity of crashes showed that the most frequently occurring driver's faults (lane departure and distracted driving) were the causes of crashes with the highest severity. These driver faults were responsible for almost 81% of the total reported fatalities, 77% of severe injuries, 63% of moderate injuries, 67% of slight injuries, and almost 46% of property damage only (PDO) crashes. Reckless driving was ranked as the third major fault causing fatalities with almost 7%, and control loss and traffic rules violation were also responsible for nearly 7% of reported fatalities.


**Table 1.** Percentage and severity of crashes based on drivers' faults.

#### *3.2. Distracted Driving Analysis*

As stated earlier, distracted driving was found to be the second highest ranking drivers' fault responsible for crashes on rural and suburban roads, and it was the second most hazardous cause of fatalities and injuries. Available records show that the number of crashes with distracted driving listed as the driver's fault is 2472, which represents 24.19% of all crashes. Distracted driving as a driver's fault was responsible for 22.7% of fatalities, 22.7% of severe injuries, 21.6% of moderate injuries, 24.4% of slight injuries, and 22.4% of PDO crashes. The characteristics of these crashes are discussed based on statistics acquired from the available data. Differences between crashes on rural and suburban roads caused by distracted driving were investigated based on three different factors: human- and time-related factors, presented in Table 2; road- and environment-related factors, presented in Table 3; and crash-type- and vehicle-related factors, shown in Table 4. Among the 2472 crashes with distracted driving listed as the driver's fault, 910 (36.8%) occurred in suburban areas and 1562 (63.8%) took place in rural areas. The severity of crashes in rural and suburban roads is presented in Figure 1. Distracted driving in rural areas seemed to be more fatal, whereas that on suburban roads led to more severe injuries.

**Table 2.** Distracted driving crashes on rural and suburban roadways according to human- and time-related factors.


**Figure 1.** Severity of crashes with distracted driving listed as driver's fault on rural and suburban roads.


**Table 3.** Distracted driving crashes according to road- and environment-related factors.

**Table 4.** Distracted driving crashes according to crash-type- and vehicle-related factors.


Table 2 shows the characteristics of crashes caused by distracted driving as the drivers' fault according to human- and time-related factors. According to the table, males were responsible for almost two-thirds of the crashes on both rural and suburban roadways. The differences in crash percentages between rural and suburban areas for males and females indicate that females were more distracted on rural roadways than males were, who appeared to be more distracted on suburban roadways where driving tasks are more demanding. Table 2 shows that drivers in the age group of 25–39 years were responsible for 64.2% of crashes, while drivers in the age group of 40–54 years caused only 22.7% of distracted driving crashes on both rural and suburban roadways. The percentages of crashes between age groups for rural and suburban areas show no major difference, except a slight increase in percentage in suburban areas for drivers of the age group 40–54.

The analysis in Table 2 shows that the majority of crashes (96%) occurred on "no holiday" days. The percentages of crashes between "holiday" and "no holiday" show no major differences between rural and suburban roadways. Distracted driving crashes during weekdays are almost three times more frequent than those that occur on weekends. Unlike suburban roadways, rural roadways seem to have slightly more distracted driving crashes during weekdays, although suburban roads show more crashes during weekends. Table 2 also shows that around 69% of distracted driving crashes occurred at midday and evening on both rural and suburban roadways. Morning and night-time crashes caused by distracted driving seem to be slightly more common on suburban roadways. Meanwhile, rural roadways show a higher percentage of crashes due to distracted driving around midday.

The characteristics of crashes caused by distracted driving as the drivers' fault according to road- and environment-related factors are shown in Table 3. More than 98% of these crashes took place on tangent sections on both rural and suburban roads. A higher percentage of crashes caused by distracted driving on two-way divided roads took place on suburban roads, whereas a higher percentage of crashes were seen on one-way and twoway undivided rural roads. The analysis shows that the majority of crashes (87.62%) took place at "no junction" roadway sections in both rural and suburban areas. The percentage of "at junction" crashes was slightly higher on suburban roads.

Table 3 shows that the majority of distracted driving crashes occurred on level grades, under dry surface conditions, in clear weather, and on two-lane roads for both rural and suburban areas. Rural roads witnessed more crashes at level grades, while suburban roadways saw more crashes on descending sections. No major difference was noticed in terms of the surface condition between urban and suburban areas. A higher percentage of crashes with distracted driving was noticed on two-lane rural roadways, while a higher percentage of crashes was seen on three-lane suburban roads. Suburban roads witnessed more crashes with distracted driving noted as the driver's fault during clear weather and daylight hours, whereas more crashes were seen on rural roadways when lighting conditions were dark.

The characteristics of crashes caused by distracted driving as the driver's fault according to crash-type- and vehicle-related factors are shown in Table 4. Collision, with a percentage of 83.62%, was the most often occurring crash type in both rural and suburban areas. Crash types caused by distracted driving seem to occur in different percentages in rural and suburban roadway sections. Collision and run-off-road (ROR) crashes occurred in higher percentages on rural roads, whereas more pedestrian crashes were seen on suburban road sections. Crashes that involved more than one vehicle were seen in higher percentages in suburban road sections.

Distracted driving crashes that occurred at speeds of 40–80 km/h were the most observed among all speed categories. The highest percentage of crashes on suburban roads occurred at speeds of 40–80 km/h, while for rural roads, the highest percentage of crashes occurred at speeds of 60–100 km/h. Crashes at speeds of higher than 100 km/h seemed to occur on rural roads only. Rural roads witnessed a higher percentage of crashes caused by distracted driving involving automobiles, medium vehicles, and tractor vehicles. On the other hand, crashes on suburban roads involved more light and heavy vehicles.

After comparing the differences between crashes resulting from distracted driving on rural and suburban roads based on crash percentages, a statistical analysis was conducted to assess whether these differences are statistically significant. Table 5 shows the results of the independent samples *t*-test for rural and suburban roadways. Six variables were found to be statistically significant: at junction, road grade, number of lanes, weather condition, crash type, and number of vehicles involved. For these variables with statistically significant differences, the effect size was calculated using Eta square and classified using Cohen's [31] guidelines, where 0.01 = small effect, 0.06 = moderate effect, and 0.14 = large effect. From the foregoing, and as shown in the table below, the six variables with statistically significant differences ended up having only a small effect. This indicates that the reported differences do not have a strong effect.


**Table 5.** Independent samples *t*-test: rural vs. suburban roadways.

Moreover, the independent samples test was also conducted to explore whether differences exist between genders in terms of distracted driving. The results shown in Table 6 below indicate that differences only exist under three conditions, namely road surface conditions, weather conditions, and lighting conditions. However, the effect size calculations revealed that the differences were very small, as reflected by the fact that no values crossed Cohen's [31] guideline classifications for a small effect size (0.01).

**Table 6.** Independent sample *t*-test: males vs. females.


#### **4. Discussion**

The driver fault analysis conducted in this study proves the significant influence of distraction on driver performance and the great losses resulting from it. The analysis revealed that distracted driving was responsible for causing nearly one-fourth of the reported crashes included in this study. Moreover, the analysis of the severity of crashes showed that distracted driving was responsible for 22.7% of all reported fatalities, 22.7% of severe injuries, and 22.4% of PDO crashes. These results are in line with previous findings [6–11] indicating that human error was responsible for a very high percentage of crashes, and distraction had a significant influence on road crashes. These results also prove that humans continue to have limited capability to perform more than two tasks in parallel, as reported by Pashler [3].

The analysis of distracted driving on rural and suburban roads was performed based on three different groups of factors: human- and time-related factors, road- and environment-related factors, and crash-type- and vehicle-related factors. Distracted driving in rural areas seemed to be more fatal, whereas suburban roads witnessed more severe injuries. The higher frequency of fatalities on rural roads could be attributed to the fact that traffic on rural roads runs at higher speeds, resulting in more severe and fatal crashes. This finding is in line with those of Eberhardt et al. [21], Kmet et al. [22], and Gonzalez et al. [23], who indicated that fatality rates in rural areas are higher than those in urban locations.

The analysis of distracted driving based on human factors revealed that males were responsible for almost two-thirds of the crashes on both rural and suburban roadways. This percentage is reasonable considering that the number of licensed male drivers in Jordan is almost twice that of licensed female drivers [23]. The differences between genders in terms of distracted driving were investigated using an independent samples *t*-test. Statistically significant differences with a small effect size were found between male and female drivers under three conditions, namely road surface conditions, weather conditions, and lighting conditions. As reported by Young et al. [13], distractions and road and environmental factors are expected to make the driving task more demanding, thus leading to impaired driving performance.

Differences were noted between drivers' age groups in that younger age groups were causing crashes due to distracted driving almost three times more often than older groups. This finding is in line with that of Regan et al. [12], who suggested that older and/or more experienced drivers are more skillful at conducting multiple activities while driving, unlike younger and/or less experienced drivers. The slight difference in percentages of crashes between age groups for rural and suburban areas can be attributed to the more demanding driving tasks on suburban roads due to higher traffic volumes and extra accessing maneuvers.

Road aggressiveness is one important human factor that was not included in the crash records. Alonso et al. [19] indicated that drivers who tend to have several accidents give less importance to elements that can affect the driving task. The number and types of traffic violations (accident history) of drivers can be used to indicate the road aggressiveness factor. Therefore, the availability of the driver's accident record in the crash report can be very helpful in studying driving behaviors and can contribute to a better understanding of driver distraction for reducing road crashes.

The study of the effect of time-related factors on distracted driving showed that the majority of crashes occur on "no holiday" days and during weekdays, which can be attributed to the higher exposure to risky situations resulting from higher traffic volumes that occur on roads on regular working days. Rural roadways showed a slightly higher occurrence of distracted driving crashes during weekdays, although suburban roads showed more crashes during weekends. Morning and night-time crashes were slightly more frequent on suburban roadways; this could be due to the higher traffic volumes on suburban roadways during these times. Meanwhile, rural roadways showed a higher percentage of crashes due to distracted driving at midday; this could also be attributed to the active movement of traffic on rural roads during this time.

Young et al. [13] indicated that distraction on different areas and road types may vary. Weather, traffic, and road conditions influence the demandingness of the driving task. Therefore, the characteristics of crashes caused by distracted driving according to road- and environment-related factors were investigated. The result of the independent samples *t*-test revealed that four variables were statistically significant with a small effect size: at junction, road grade, number of lanes, and weather condition. The percentage of at-junction crashes was slightly higher on suburban roads, which could be attributed to the higher demandingness level of the driving task due to higher traffic volumes. The majority of distracted driving crashes were seen on level grades, under dry surface conditions, in clear weather, and on two-lane roads for both rural and suburban areas. Suburban roads witnessed more crashes with distracted driving as the drivers' fault during clear weather and daylight times, whereas more crashes were recorded on rural roadways when the lighting conditions were dark. This is consistent with Stutts et al. [32], who found that those who were distracted at the time of their crashes were less likely to be traveling on multi-lane roadways and were less likely to have crashed at an intersection or other road junction.

Casado-Sanz et al. [25] suggested using the physical severance index in future research, which considers the distribution of urban land as a relationship between the difference in the built areas on both sides of the road and the total built area. Territorial variables (built environment and physical severance) can affect the occurrence of accidents. Since the available data provide the coordinates of crashes, it might be possible to consider such territorial variables in future studies.

The analysis of the crashes caused by distracted driving as the drivers' fault according to crash-type- and vehicle-related factors showed that collision was the most common crash type in both rural and suburban areas. The crash types and the number of vehicles involved were statistically significantly different between rural and suburban roads. Collision and run-off-road (ROR) crashes occurred in higher percentages on rural roads, whereas more pedestrian crashes were seen on suburban road sections. The high percentage of pedestrian crashes in suburban areas makes sense, as pedestrians are seen in urban and suburban areas more often and are only occasionally seen on rural roadways. Crashes that involved more than one vehicle were seen in higher percentages in suburban road sections, which could be explained by the existence of traffic-congested sections in suburban areas. The number of distracted driving crashes involving one vehicle was higher in rural areas due to less traffic and higher speeds.

As presented in the previous section, the highest percentages of crashes on suburban roads occurred at speeds of 40–80 km/h, while for rural roads, the highest percentages of crashes occurred at speeds of 60–100 km/h. Crashes at speeds of higher than 100 km/h seemed to occur on rural roads only. This is consistent with earlier findings by Thomason [24], who reported the same result about suburban roadways and rural highways. As for vehicle type, we noticed that both automobiles and light vehicles comprised more than 80% of vehicles involved in the reported crashes. Rural roads witnessed a higher percentage of crashes caused by distracted driving involving automobiles, medium vehicles, and tractor vehicles. A similar finding was reported by Stutts et al. [32], who indicated that distracted drivers were more likely to be driving during non-daylight hours and were more likely to be driving a pickup truck, van, or sport utility vehicles.

One of the major limitations of the present study is that the obtained data lack, in some respects, important details that, if they existed, would deliver more thorough and useful results about distraction. Therefore, it is recommended that accident reports be carefully designed to include all specific details, such as the type of distraction factor (visual, manual, cognitive, and auditory) that caused the driver's distraction. Providing such details in the crash report would help eliminate confusion caused by interrelated information and would deliver complete information that will be significantly helpful to this field of research. It is also suggested that crash reports should include information on the number of accidents that drivers were previously involved in. Having this factor available can help researchers

examine the effect of aggressive driving, as recommended by Alonso et al. [19], on all kinds of crashes, including distraction.

### **5. Conclusions**

The aim of this study was to highlight the risk of driver distraction, which is one of the major driver's faults, in causing traffic crashes that cost great losses of lives and resources. Most drivers' faults that cause crashes on rural and suburban roadways were identified. Crashes caused by distracted driving were examined, and the differences between crashes on rural and suburban roadways were investigated. Based on the findings of this study, the following can be concluded:

Comprising almost one-fourth of the reported crashes (24.19%), distracted driving was the second most frequent driver fault causing crashes on both rural and suburban roadways.


Considering the above-mentioned results, it is recommended that practitioners and policy-makers establish specialized programs and awareness campaigns intended to educate drivers on several factors that affect their driving abilities and emphasize and stimulate mindful driving with a sufficient cognitive and visual emphasis on driving initiatives and the traffic environment. It is also recommended that this same dataset be used in the future for model development to obtain a deeper understanding about factors that contribute to distracted driving and simulate the impact of distracted driving on the injury or crash severity of a given crash.

**Author Contributions:** Conceptualization, T.M.A.-R.; Methodology, T.M.A.-R. and A.A.U.; formal analysis, T.M.A.-R., A.A.U. and A.A.A.-O.; Investigation; T.M.A.-R.; resources, T.M.A.-R.; data curation, T.M.A.-R.; writing—original draft, T.M.A.-R., A.A.U. and A.A.A.-O.; writing—review and editing, T.M.A.-R., A.A.U. and A.A.A.-O., visualization, T.M.A.-R., A.A.U. and A.A.A.-O.;

supervision, T.M.A.-R.; project administration, T.M.A.-R. All authors have read and agreed to the published version of the manuscript.

**Funding:** This research did not receive any specific grant from any funding agencies.

**Data Availability Statement:** The data that support the findings of this study are not publicly available due to privacy/ethical restrictions, but they are available from the corresponding author upon reasonable request.

**Acknowledgments:** Thanks are due to the Jordan Traffic Institute officers for providing the traffic accident data that were used in this study.

**Conflicts of Interest:** The authors declare no conflict of interest.
