Road accidents can have severe consequences, leading to injuries, fatalities, and significant socio-economic impacts. In the United Kingdom, a comprehensive dataset capturing detailed information about road accidents is available. This article aims to delve into this dataset, uncover insightful trends, and shed light on road safety in the UK. Through a thorough examination of the data, we can gain a deeper understanding of the factors contributing to accidents, identify patterns, and explore potential implications for enhancing road safety.
Overview of the UK Accident Dataset:
The dataset used in this analysis was obtained from the Kaggle website. It comprises various key metrics and provides valuable insights into road accidents in the UK. This section will provide an overview of the dataset, including a discussion on accident statistics such as the number of accidents, injuries, and fatalities over the years. Additionally, trends and patterns in accidents will be analysed, considering factors such as time of day, day of the week, and seasonal variations. Furthermore, the distribution of accidents across different regions of the UK will be investigated.
Key Metrics and Trends:
This section will focus on analyzing the total number of accidents recorded in the UK from 2005 to 2014, excluding the year 2008, as it was not included in the dataset. The total number of accidents during this period amounts to 1,504,150. The diagram below illustrates the distribution of accidents that occurred throughout these years.
Figure 1: Distribution of accidents by year
From the above diagram, it can be observed that the year 2005 marks the beginning of the dataset and has the highest recorded accident rate, with a total of 198,735 accidents. The diagram further demonstrates a downward horizontal slope from 2005 to 2011, indicating a decrease in the accident rate. However, in 2012, the rate experienced a significant surge, reaching 179,715 accidents, before dropping to a low of 138,660 accidents in 2013. The accident rate then increased once again in 2014.
Additionally, the distribution of accidents across the four quarters of each year from 2005 to 2014 will be visualized to explore any seasonality patterns. The following diagram provides a detailed overview of the correlation between accidents and the quarterly divisions.
Figure 2: Correlation between accidents and quarters of the year
From the aforementioned diagram, each year is represented by a unique color divided into four segments, corresponding to Q1, Q2, Q3, and Q4. Each segment shares the same color as the year it represents. Analyzing the visualization, it becomes apparent that the fourth quarter (Q4) of each year consistently exhibits the highest recorded accident rate, except for the year 2010, where the highest quarterly rate was observed in Q3, followed by Q4.
Additionally, I would like to discuss the accident rate in relation to the days of the week to determine which week experiences the highest occurrence of accidents. The diagram provided below illustrates the weekly distribution of accidents
Figure 3: Weekly distribution of accidents
Upon analyzing the diagram, it becomes evident that day 6 exhibits the highest accident rate, with a total of 247,137 recorded incidents. Following closely is day 5, which documented 226,411 accident victims. A careful examination of the graph reveals that the horizontal trend of accidents ascends from left to right, starting from day 1 (Sunday) and culminating in day 7 (Saturday). Notably, there is a steep incline between day 1, which recorded 164,972 accident victims, and day 2, which reported 213,718 incidents. The gradual increase in accidents continues horizontally across the days until day 5, which tallies 226,411 victims. However, day 6 experiences a sharp surge, reaching 247,137 accidents, followed by a notable decline on day 7, which recorded 201,416 incidents.
Based on our research, it is evident that day 6, which is Friday, has the highest accident rates.
Furthermore, the severity of accidents in the dataset is classified into three categories: severity 1, severity 2, and severity 3. Allow me to explain each severity level:
Fatal (Severity 1): This category encompasses accidents resulting in one or more fatalities within 30 days of the incident. It includes cases where individuals involved in the accident pass away at the scene or succumb to their injuries in a hospital or other medical facility.
Serious (Severity 2): Also referred to as severity 2, serious accidents involve injuries that are classified as severe but not fatal. These injuries typically require hospitalization or have significant consequences for the individuals involved. Examples of serious injuries include fractures, severe head injuries, spinal injuries, internal organ damage, or other injuries that significantly impact the person's life.
Slight (Severity 3): Severity 3 refers to relatively minor injuries that do not necessitate hospitalization or require only minimal medical treatment. Examples of slight injuries include cuts, bruises, sprains, and whiplash. Out of the total recorded accidents (1,504,150 incidents), we identified 19,441 accidents categorized as severity 1, 204,504 incidents classified as severity 2, and 1,208,205 cases labeled as severity 3.
Now, let's analyze; the distribution of accident severity across different hours of the day to identify the highest and lowest accident rates within each day. The following diagram displays the severity of accidents over time
Figure 4: Severity of accidents over time
In the above graph, the y-axis represents the cumulative sum of accidents, while the x-axis indicates the time of day when accidents occur. By observing the right side of the diagram, we can notice 24 squares with unique colors, each representing one hour of the day.
Regarding Severity 3 (slight accidents), we found that day 17 recorded the highest number of severity 3 accidents, reaching 114,835 incidents. It was followed by day 16 with a rate of 104,338 accidents, day 15 ranking third with 99,573 incidents, day 8 coming in fourth with 97,262 cases, and day 18 ranking fifth with 88,335 incidents. On the other hand, the hour with the least severity -3 accidents was hour 4, which recorded 6,396 incidents, followed by hour 3 with 8,260 accidents.
For Severity 2 (major accidents), we observed that day 17 also had the highest accident rate, with 17,589 incidents. Day 16 followed closely with 16,452 accidents, ranking second, and day 15 came in third with 15,566 incidents. Day 18 and Day 8 occupied the fourth and fifth positions, respectively. The hour with the lowest severity 2 accident rate remained 4, coinciding with the severity 3 data, recording 1,627 incidents. Hour 3 registered the second-lowest accident rate for both severity 3 and severity 2, with 2,127 incidents.
In terms of Severity 1 (fatal accidents), it is worth noting that the highest number of accidents occurred during hour 17, with a rate of 1,113. Hour 16 recorded 1,291 incidents, ranking second, while hour 13 claimed the third position with 1,004 incidents.
In summary, when examining the severity rates across different hours, it becomes apparent that hour 17 consistently ranks at the top in all severity categories. Hour 16 consistently follows as the second highest in all severity categories, and hour 15 secures the third position for both severity 3 and severity 2. Hour 18 and hour 8 alternate as the fourth and fifth positions, respectively, in terms of recorded accidents for severity 3 and severity 2.
We discuss the spread of the accident across the local authority highway road. Local authority highway roads are public roads controlled by the local authorities and most of the roads are routed to other regions or countries. Visualization will be carried out to see the top first pattern of road accident across the UK.
Figure 5: Accident by local authority highway
From the diagram above we see the first top accident rate in UK. We find out that E10000017 contain the most accident recorded with a rate of 36,650, followed by E10000012 which recorded 31,993 and E10000014 which recorded 27,675
Pedestrian UK accident
According to the analysis, the highest rate of accidents occurred in the "No Physical Segment," which recorded a total of 1,249,783 incidents. Following closely is the "Pedestrian Phase at Traffic Signal Junctions" segment, with a total of 98,150 accidents. The third segment, "Zebra Crossing," reported 39,054 accidents, while the "Central Refuge" segment came fourth with a total of 27,727 incidents.
Figure 6: Accident occurrence by segment
Based on the analysis conducted, it can be concluded that the presence of pedestrians appears to have a significant impact on reducing accidents. The data indicates that the segment without pedestrians, where the road is free of pedestrian activity, accounts for more than 70% of the accidents. Conversely, the segment with pedestrians shows a considerably lower rate of accidents. This finding highlights the effectiveness of pedestrian presence in mitigating accidents. When pedestrians are present, the occurrence of accidents decreases significantly. This suggests that pedestrians play a crucial role in enhancing road safety and reducing the likelihood of accidents. It is worth noting that this analysis underscores the importance of considering pedestrian-related factors when designing road safety interventions. Strategies that promote pedestrian-friendly infrastructure, such as crosswalks, pedestrian signals, and designated walkways, can contribute to further reducing accidents and enhancing overall road safety.
In summary, the data analysis strongly indicates that the inclusion of pedestrians in road environments has a positive impact on accident rates. By prioritizing pedestrian safety and implementing measures to accommodate and protect pedestrians, we can significantly improve road safety outcomes.
Contributing factors of accident
This chapter is going to discuss key factor that affect such as weather, speed, lighting condition of road, road surface condition.
Weather conditions in the UK can have a significant impact on road safety and contribute to an increased risk of accidents. Adverse weather such as rain, snow, fog, or strong winds can reduce visibility, create slippery road surfaces, and increase stopping distances, making driving more challenging. According to a study conducted by the UK Department for Transport, adverse weather conditions were a contributing factor in approximately 2,000 road accidents annually, resulting in over 250 deaths and 3,000 serious injuries.
Figure 7: Accidents by weather conditions
From the diagram above we find out that Fine with good winds recorded 18,355 accident, while fog and mist recorded 8190 accident case, while the unknown condition recorded the highest case which was 33,503, while snowing with high wind recorded 1,960 cases which is the smallest accident case, snowing with high wind 11,301 accident case was the lowest rate, while snowing without with wind recorded 11,301 cases while the unknown case recorded 28,422.
Weather conditions in the UK can have a significant impact on road safety and contribute to an increased risk of accidents. Adverse weather such as rain, snow, fog, or strong winds can reduce visibility, create slippery road surfaces, and increase stopping distances, making driving more challenging. According to a study conducted by the UK Department for Transport, adverse weather conditions were a contributing factor in approximately 2,000 road accidents annually, resulting in over 250 deaths and 3,000 serious injuries.
The UK road surface condition was analyzed and divided into seven segments, including single road carriage, dual road carriage, roundabout, one-way street, slip road, and the unknown.
Figure 8: Accidents by road surface condition
Among these segments, the data revealed that the single carriageway had the highest number of accident victims, with a total of 900,325 victims, accounting for 79.01% of all accidents. This indicates that the majority of accidents were associated with the carriageway category. The dual carriageway followed closely behind with a total of 115,173 accidents, constituting 10.11% of the total. Surprisingly, the segment with the lowest number of accidents was the unknown category, which indicates that the cause of the road surface condition was not known. Specifically, there were 6,839 accidents recorded in this segment, accounting for 0.59% of the total. However, this data does not provide useful information as it cannot be attributed to a specific road surface condition. Interestingly, the second-lowest segment recorded 6,893 accidents, representing a rate of 0.60%.
In a surprising revelation, it was found that the majority of accidents occurred within the speed range of 30MPH. Among all recorded accidents, the 30MPH range accounted for a total accident rate of 968,284, representing a significant percentage of 64.37%. This indicates that more than half of the accidents related to speed were associated with this particular range. In contrast, the 60MPH range recorded 238,244 accidents, constituting 15.8% of the total accidents and ranking as the second highest. Interestingly, the lowest accident rate was observed in the 10-15 MPH range, with no accidents reported. The diagram below shows accident rate involving speed.
Figure 9: Accidents by speed
Discovering patterns in the UK accident dataset
Time and week related:
According to our research findings, it has been observed that a significant number of accidents occur around 17:00, particularly on Fridays. This time coincides with the period when most people are returning from work, resulting in a high volume of vehicles on the road. Consequently, this increased traffic congestion can contribute to a greater risk of accidents. Additionally, the fact that individuals are returning from work implies that they may already be stressed or fatigued. This state of mind can further impair their ability to concentrate on the road, potentially leading to accidents. The combination of heavy traffic and stressed drivers creates a hazardous environment that increases the likelihood of accidents and subsequently leads to more victims. Friday holds particular significance in this context due to the emotional trauma associated with wanting to reach home on time. As the last workday of the week, many individuals have a strong desire to finish their work promptly and begin their weekend activities, including resting. This eagerness to leave work and the anticipation of leisure time may cause people to lose consciousness of their surroundings, including the road conditions. As a result, their decreased awareness and attentiveness can contribute to accidents occurring more frequently on Fridays.
In summary, the concentration of accidents around 17:00 and on Fridays can be attributed to a combination of factors, including high traffic volume, stressed drivers returning from work, and individuals' eagerness to reach home quickly. These factors collectively contribute to the increased risk of accidents during this time, resulting in a greater number of victims.
Speed-related Accidents:
Upon analyzing the data, it was observed that accidents are most prevalent at a speed of 30mph. This speed category had the highest frequency of accidents compared to other speed ranges. This finding suggests a correlation between accidents and vehicles operating at this particular speed.
Weather Conditions and Accidents:
Bright weather conditions were found to be associated with the highest number of accidents. Throughout the year, bright weather prevailed more frequently than other weather conditions, indicating that a larger number of vehicles were in motion during these conditions. Consequently, the higher vehicle density contributed to an increased accident rate.
Road Types and Accidents:
Accidents were found to be most common on single-carriage roads within the analyzed segment. The prevalence of accidents on this road type exceeded that of other road types. Given that more vehicles were observed on single-carriage roads, the higher traffic volume in these areas contributed to the elevated accident rate.
Deviation from Scientific Expectations:
The observed accident patterns do not align with conventional scientific expectations. Clear roads would typically be expected to have lower accident rates; however, the data showed an inverse relationship. This deviation suggests the presence of other contributing factors beyond mere road conditions. Similarly, the high accident rate at 30mph contradicts expectations that lower speeds would result in reduced accidents.
Recommendations
Based on the findings, we propose the following measures to minimize accidents:
Encourage Speed Limit Adherence: Increasing awareness about the risks associated with driving at 30mph and promoting adherence to speed limits can help mitigate accidents in this speed range.
Improve Road Safety Infrastructure: Enhancing safety measures, such as adding traffic lights, speed cameras, and warning signs on single-carriage roads, can help reduce accidents in areas with high traffic density.
Promote Alternative Transportation Options: The government should invest in promoting alternative transportation modes, such as public transportation, carpooling, and cycling, to reduce the overall number of vehicles on the road.
Public Awareness Campaigns: Launching public awareness campaigns on safe driving practices, weather-related precautions, and the importance of maintaining appropriate speeds can contribute to accident prevention.
Conclusion
The analysis revealed significant patterns in accident occurrence related to speed, weather conditions, and road types. These findings demonstrate that higher vehicle density at 30mph, bright weather conditions, and the prevalence of single-carriage roads contribute to increased accident rates. By implementing the recommended measures, the government can work towards minimizing accidents and enhancing overall road safety.
References
1.Road Accident (n.d). Insee. Retrieved May 19, 2023, from https://www.insee.fr/en/metadonnees/definition/c1116
2.Road Accident (United Kingdom)(UK) (n.d). Kaggle. Retrieved May 2, 2023, from https://www.kaggle.com/datasets/devansodariya/road-accident-united-kingdom-uk-dataset
3.Weather related road accidents in UK. Department of Transport.
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