Characteristics Of Traffic Accidents Research Articles

ANALYSIS OF BLACK SPOTS ON JL. RAYA KAKAP KUBU RAYA DISTRICT WITH Z-SCORE METHOD

Kubu Raya is a district in West Kalimantan Province. It is directly adjacent to Pontianak City, the province's capital. This condition increases mobility and vehicle traffic, resulting in a relatively high accident rate.Traffic accident data came from the Kubu Raya Regency Police Station, and field observations obtained data on road condition and completeness. The analysis methods used are weighting, Z-Score, and CUSUM (Cumulative Summary).The number of accidents in Jalan Raya Kakap during 2020 - 2022 amounted to 26 incidents. The characteristics of traffic accidents on Jalan Raya Kakap for three years (2020 - 2022) are that victims with minor injuries are more than victims of death and serious injuries, namely seven victims in 2020, 8 victims in 2021, and 18 victims in 2022. STA points 0 - 1 have the highest number of accidents during the 3-year period, which is 152 STA points. 2-3 by 129, and point STA. One black spot falls into the high accident vulnerability category: point STA. 0-1. Two black spots fall into the high accident vulnerability category: STA points. 2-3 and STA. 7-8. Four black spots fall into the medium category. Three black spots fall into the low category. Moreover, four points are categorized as not accident-prone.

Analysis of Determining the Location of Blackspots and Blacksites on the Bypass Road KM 19-27 Padang City using the Accident Equivalent Number and Upper Control Limit Method


 
 
 
 The Padang City Bypass Road KM 19-27 is a road section that has quite a heavy traffic volume, starting from the Lubuk Minturun intersection to the Flyover towards the Airport, so there is a high possibility of accidents occurring along this road section. This research uses secondary data obtained from the Unit Padang City Police Traffic Accident. The aim of this research is to determine the characteristics of traffic accidents and identify locations prone to accidents on the Padang City KM 19-27 Bypass road during the 2018-2022 period and to provide alternatives for preventing traffic accidents in the future. This type of research uses the Accident Equivalent Number (AEK) method and the Upper Control Limit (UCL) method. If the AEK value is greater than the UCL then it is categorized as an accident-prone location. The results of the analysis of the characteristics of traffic accident data for 2018-2022, the highest was at KM 20 with 16 incidents, based on time, namely 07.00-08.00 WIB, 10 incidents, based on victims, namely minor injuries (LR), 161 victims, and based on causal factors. The main cause of traffic accidents is the human factor. Blackspot location based on analysis using the AEK method with 5 years of data (2018-2022), namely at KM 20 with the highest total AEK value, namely 221. The blacksite location using the AEK method with UCL control limits on the Padang City Bypass road section KM 19-27 is KM 19, 20, 21, 22, 23, 24 and 25. Recommendations for handling traffic accidents on the Padang City Bypass KM 19-27 road, namely by providing education about driving safety, checking vehicles regularly, improving the physical condition of the road and prohibiting pedestrians from walking. at certain points that disrupt traffic.
 
 
 

CHARACTERISTICS OF TRAFFIC ACCIDENTS ON 4/2D ROAD TYPES ON THE SURABAYA - MOJOKERTO TOLL ROAD ( CASE STUDY: WARUGUNG - PENOMPO TOLL ROAD SECTION)

In developing road infrastructure, keeping pace with the transportation sector and the rapidly growing economy is vital. Inadequate road infrastructure conditions will cause problems on the road, namely traffic accidents and congestion, which results in a lack of driver comfort. PT Jasa Marga can undoubtedly find out the leading cause of the accident. This study aimed to determine the characteristics of traffic accidents on the 4/2d road type, precisely on the Surabaya - Mojokerto toll road on the Warugunung - Penompo toll road. The Surabaya–Mojokerto Toll Road or Sumo Toll Road is a 36.27-kilometer-long toll road that connects the City of Surabaya with the City of Mojokerto, East Java Province. This toll road is connected to the Kertosono-Mojokerto Toll Road to the west. The class of vehicles on this toll road, such as trucks and large-laden cars, can also be said to be one of the characteristics of traffic accidents. Location of accident-prone points (BlackSpot) on the Warugunung – Penompo toll road in 2021 on line A, namely at Km 3+000 – 4+000 of the Warugunung – Driyorejo section, because at that location there are road slopes and bends, so many motorists drive at high speed high and have to slow down when there is a descent and many riders do not anticipate it. In 2021, line B, namely at Km 5+000 - 6+000 on the Warugunung - penompo section, is not much different from line A.

Research on the Testing and Evaluation of Active Safety System for Turning Cars in Two wheeler Traffic Scenarios

China In-depth Traffic Accident Survey (CIDAS) shows that two wheeler has the highest accident fatality rate, more than 38%, which is far more than cars and pedestrians. In this paper, the characteristics of traffic accidents in China, the types of two wheeler, and traffic characteristics of two wheeler are taken into account. There are typical hazardous scenarios in the case of crossing, longitudinal, turning, mixed, etc. In the existing collision scenarios design of cars and two wheeler, the testing methods of crossing and longitudinal have been basically mature. Therefore, combining with the functional testing of the current automobile active safety system, to recurrent the traffic scenarios of two wheeler objectively, the active safety test and evaluation scenarios of turning cars under the two wheeler traffic scenarios are designed. Test paths, test speeds, and impact position are proposed. it complements the test scenarios for active safety function.

Analysis of the Characteristics of Motorcycle Road Traffic Accidents in Chongqing

Traffic accidents have become an important factor affecting human safety. Chongqing has a large number of motorcycles and corresponding traffic accidents. Analyzing and clarifying the characteristics of motorcycle traffic accidents in Chongqing has positive practical significance. This article selects a motorcycle case reported by an insurance company in 2021 and uses statistical software to analyze the characteristics of motorcycle road traffic accidents in Chongqing. Based on feature analysis, select a typical traffic accident, analyze the injury mechanism and protective measures, and study the prevention and treatment policies for road traffic accidents in Chongqing. The statistical results show that the proportion of motorcycle accidents in Chongqing is relatively high, and the number of accidents in suburban areas and counties is much greater than that in the main urban areas. At the same time, head impact on the windshield and ground is the main source of damage in motorcycle accidents.

Spatiotemporal Distribution and Evolution Characteristics of Water Traffic Accidents in Asia since the 21st Century

As an important mode of transportation for the global trade, waterborne transportation has become a priority option for import and export trade due to its large load capacity and relatively low cost. Meanwhile, shipping safety has been highly valued. By collecting technological water traffic accident data from the EM-DAT database, the spatiotemporal distribution and evolution characteristics were investigated in Asia since 2000. The methods of gravity center and standard deviation ellipse analysis were utilized to determine the spatial and data-related characteristics of water traffic accidents. Temporally, the results indicated that accidents occurred most frequently during the seasons of autumn and winter, leading to a significant number of casualties. Spatially, both South-eastern Asia and Southern Asia emerged as regions with a high frequency of water traffic accidents, particularly along the borders of Singapore, Malaysia, Indonesia, and the Bay of Bengal region. In addition, the Daniel trend test and R/S analysis were conducted to demonstrate the evolution trend of accidents across various regions and seasons. The present study provides guidance for improving marine shipping safety, emergency resource management, and relevant policy formulation.

Analysis of primary-party traffic accident rates per driver in Japan from 1995 to 2015: Do older drivers cause more accidents?

Studies on the age and generation characteristics of traffic accidents primarily focus on the tendency of deaths and severe injuries, whereas the faults or drivers who caused the accidents are not considered. Using license holders as a parameter for measuring accident risk when evaluating the number of primary-party accidents is challenging because it includes those who possess licenses but do not drive. In previous studies, the age characteristics in traffic accidents were evaluated based on different age groups and generational characteristics. Therefore, a Bayesian age–period–cohort analysis was performed in this study to isolate the effects of age, period, and generation on the number of traffic crashes. This approach can identify the gender/age of the driver, who may be the primary contributor to an accident, as well as the risk of traffic accidents in younger and older drivers. The results show that 1) age imposes a more significant effect than the duration and cohort. In the case of single-vehicle accidents, 2) the effect of age was significantly more prominent for males over 80 years old and females over 70 years old.

Development of a Road Protection Value Model as an Indicator for National Road Safety Performance Assessment from the Perspective of Drivers of Four or More Wheeled Motorized Vehicles

This paper introduces the model of Star Rating Scores (SRS) or Road Protector Scores (RPS) for Indonesian National Roads from the perspective of motorized vehicle drivers with four or more wheels, which are explored from the characteristics of traffic accidents along Indonesia's national roads. This SRS model takes into account 2 different main parameters and 4 main parameters that are the same as the main parameters of the SRS International Road Assessment Program (iRAP) and a total of 51 road attributes. The two main parameters that differ from the SRS iRAP model are the parameters for front-rear crashes and fore-side crashes when turning around. While the 4 parameters are the same as front-side collision accidents at property access, single accidents leaving the road body, front-to-front collision accidents, and accidents at intersections. In the early stages, the National Road SRS model was designed using 51 road attributes. After analysis using the Importance and Performance Analysis (IPA) method, 43 road attributes were successfully formulated for the SRS National Road model, consisting of 30 likelihood factor attributes, 10 severity factor attributes, 2 external traffic influence factor attributes, and 1 factor attribute operational speed. In addition, it is proven that the SRS National Road model is significantly different from the SRS iRAP model. The three main parameters of the National Road SRS model, namely the front-rear hit accident parameter, the front-side hit accident parameter when turning around, and the front-side hit accident parameter at property access are significantly different from the parameters of the SRS iRAP model.

Characteristics analysis of intercontinental sea accidents using weighted association rule mining: Evidence from the Mediterranean Sea and Black Sea

With the continuous growth of international trade and the number of ships, the pressure on marine safety is increasing. To strengthen the efficiency and pertinence of accident prevention and control measures, in-depth research on the characteristics of marine traffic accidents is of great significance. This study uses a Weighted Association Rule Mining (WARM) approach to investigate the association between marine traffic accidents characteristics. The Mediterranean Sea and Black Sea play a crucial role in global maritime transportation. The marine traffic accidents in the Mediterranean Sea and Black Sea region from 2006 to 2020 are collected from the Lloyd's List Intelligence (LLI) database. Then, WARM is applied to obtain the characteristics of marine traffic accidents. The findings show that Flag of Convenience (FOC) vessels in the Mediterranean have a lower accident rate than non-FOC vessels do. Moreover, the results reveal a strong relationship between accidents and the age, gross tonnage, and ship type. Older general cargo ships with a gross tonnage between 500 and 3000 tons are more prone to accidents. This research provides insights for authorities to develop targeted measures for preventing specific types of accidents and enhancing marine safety.

Division and Analysis of Accident-Prone Areas near Highway Ramps Based on Spatial Autocorrelation

This study focuses on identifying accident-prone areas and analyzing the factors contributing to the distribution of traffic accidents near highway ramps. A combined method of kernel density estimation, spatial autocorrelation analysis, and multivariate logistic regression analysis helped to identify accident hotspots. Through data collection and analysis, the clustering characteristics of traffic accidents in the diversion and merging areas were identified. Four levels of accident-prone areas were divided according to the accident rates. The factors influencing the spatial distribution of accidents were analyzed. The results showed that traffic accidents in the diversion area were concentrated near the exit, but the accidents in merging areas had a wider range of distribution. The analysis of this phenomenon was conducted using the multinomial logit model results. The important factors of different accident-prone areas were clarified. The temperature, the accident lane, weather conditions, and the time of day had significant impacts on the spatial distribution of traffic accidents. The study’s findings provide an important decision-making basis for highway accident prevention management.

Analysis of accident characteristics and accident-prone areas in Sleman Regency, Yogyakarta (Case study: Kaliurang Road Section Km 3.5 – Km 10)

This study aims to identify accident-prone locations on the Kaliurang road km 3.5 – km 10 Sleman Regency, D.I.Yogyakarta Province to find steps to reduce accidents in these accident-prone areas. The initial data is traffic accident data for 2020 – March 2022 which is then analyzed to determine the characteristics of traffic accidents on the Kaliurang km 3.5 – km 10 road segment classified by type of collision, type of vehicle, and material loss. Determination of the location of accident-prone areas based on ranking using the Equivalent Accident Number (EAN). A total material loss of Rp. 86,300,000.00 for the last two years and three months. The location of the accident-prone area is the Kaliurang kilometer 8 road with an EAN value of 203. The results of the analysis are interpreted that the better the handling related to complementary buildings and road facilities, the more likely it is to reduce the number of accidents in the accident-prone area.

Risk Assessment of Traffic Accidents Involving Young Adult Drivers by Identification of Subjective and Objective Factors

Young drivers represent the most vulnerable age group at risk of participating in traffic accidents. In order to reduce the occurrence of traffic accidents involving young drivers, various models for assessing the risk of accidents have been studied. Inexperience, lack of driving skills and risky behaviour in traffic are the main characteristics of traffic accidents involving young adult drivers. On the contrary, traffic accidents involving older adult drivers are characterised by reduced visual and cognitive stimuli and reduced mobility. Based on the data about traffic accidents from the available databases relevant for road traffic safety in the Republic of Kosovo over a four-year period, the road characteristics that caused the majority of traffic accidents involving young adult drivers and the subjective and objective factors that affected the occurrence of traffic accidents the most have been defined. To conclude the research, a correlation has been defined between objective and subjective factors that increase the risk of traffic accidents, as well as the frequency of single safety factors (human, vehicle, road and environment) in traffic accidents involving young adult drivers.

Characteristics of road traffic accident types and casualties in Guangzhou, China, from 2007 to 2020: A retrospective cohort study based on the general population

IntroductionThis study aimed to explore the trend and main influencing factors of road traffic accidents in Guangzhou, China, from 2007 to 2020 and to provide a reference and guidance for government decision-making. MethodsA retrospective cohort study was used to describe road traffic accidents in Guangzhou. According to the population types, all people with road traffic accidents were divided into migrant workers and the control population. We divided road users, administrative districts, motorcycle types and injury levels into subgroups to investigate the characteristics of road traffic accidents in Guangzhou. The road traffic accident data were derived from the Guangzhou Public Security Traffic Management Integrated System. ResultsThe incidence rate of road traffic accidents per 10,000 vehicles in Guangzhou decreased from 36.55 in 2007 to 10.07 in 2012, remained relatively stable at 9.47 in 2017, and finally rose to 11.12 in 2020. The injury rate showed the same trend as the incidence rate, while the mortality rate gradually decreased from 14.21 in 2007 to 5.19 in 2020. Vulnerable road users such as motorized two-to-three-wheeler drivers and migrant workers were casualties in more than 80% of the cases. The proportion of casualties involving mopeds and electric bicycles increased rapidly after 2018. Motor vehicle drivers frequently caused road traffic accidents and were most often uninjured. ConclusionRoad safety in Guangzhou has shown a clear trend of improvement, but casualties are uneven across administrative districts. More attention should be given to motorized two-to-three-wheelers, migrant workers, and road traffic violations by uninjured individuals.

Characteristics of Traffic Accidents Frequency on Connection Road Between 3 Cities in Riau - Indonesia

The main cause of road accidents in outside of cities is the driver's lack of awareness about road safety. Efforts to reduce these accidents can be done if the characteristics and causes are known. The purpose of this study was to determine the characteristics of road accidents in three areas in Riau province. Analysis used a descriptive quantitative analysis. This study was done to identify the characteristics of traffic accidents occurred from 2014 to 2019 on the connection road between 3 cities in Riau, namely in the Kuantan Singingi, Kampar and Rokan Hulu areas of Riau Province, Indonesia. The analysis used is descriptive quantitative analysis. The greater accidents were occurred in 2018, in which 192 cases. The least accidents were occurred in 2017, in which 115 cases, the month of June had the highest number of accidents since it was a month of school holidays. The percentage of total deaths on traffic accidents reached 60%. Meanwhile, 75.6% of traffic accident victims were injured, with the most accidents occurring on flat and straight roads. The types of vehicles that are often involved are motorcycle, which occur from 06.00 to 11.59 pm.

Analysis of speed limits credibility - Case studies for Batajnica and Nova Pazova

Complex and often contradictory aims in traffic engineering, primarily from the aspect of traffic efficiency and safety, have led to the need for speed management. One of the speed management measures is the speed limit. A poorly set speed limit can lead to negative consequences. A speed limit that is not in accordance with the driver's perception in relation to road and traffic characteristics is not considered credible. This paper examines the credibility of speed limits on two sections between the settlements of Batajnica and Nova Pazova. Through the paper methodology, the road characteristics of sections, speed (calculated speed, free speed, exploitation speed and limited speed) and traffic accidents were analysed. The credibility of the set speed limits in 2019 and 2020 was examined by analysing all the mentioned parameters. Recommendations were made based on the results of the research.

Exploration of road closure time characteristics of tunnel traffic accidents: A case study in Pennsylvania, USA

With the increase of roadway tunnels, tunnel traffic accidents are also increasing. Compared with open roadways, road closures caused by traffic accidents in the tunnel have greater influences on traffic operations, as tunnels are often the key junctions of the roadway network. With the traffic accident data of Pennsylvania from 1997 to 2020, this study is designed to identify the features and trends of road closure time due to tunnel traffic accidents. First, features of tunnel and non-tunnel traffic accidents are compared from the perspectives of accident consequences, environmental factors, risky driver behavior, and vehicle features. The data confirms that tunnel traffic accidents are more likely to lead to road closures than non-tunnel ones. Besides, tunnel traffic accidents are mainly consisted of rear-end and hit-fixed-object collisions with many speeding cases. Then, a Negative Binomial model is built to statistically identify the factors significantly influencing the road closure time, which is recorded as non-negative integer in the data. The estimation results indicate that collision type, accident severity, road type, driving under the influence, the involvement of heavy trucks, and the number of involved vehicles could significantly influence the road closure time, whereas lighting, road condition, speeding, and area are insignificant. Finally, based on the research findings, some countermeasures are proposed to reduce the road closure time caused by tunnel traffic accidents.

Accident Prone Area Database Analysis in Yogyakarta City

The need for transportation in Indonesia is increasing day by day. This is due to the high population growth, the rapid number of motorized vehicle ownership, as well as the construction of new settlements, which resulted in the need for transportation facilities always increasing. Transportation problems occur as traffic density increases, one of which is traffic accidents. As a first step in reducing the number of accidents, it is necessary to identify accident-prone areas. It is needed to compile a GIS-based traffic accident database that is informative. In this research, two methods of analysis are generally carried out, including analysis of traffic accident-prone areas and analysis in compiling a database based on geographic information systems. In this study, results were obtained regarding the characteristics of traffic accidents in the city of Yogyakarta which included the number of victims of traffic accidents during the period 2016 – 2020, as many as 3,530 people, with the type of vehicle involved in the most accidents being motorcycles, namely 3,671 vehicles. The type of front-rear collision is the most common type of accident and the age most often involved in accidents is in the age range of 20-29 years. Then based on the results of the analysis using three methods of determining DRK, including the equivalent accident number (EAN) method, the frequency method, and the z-score method, obtained five roads that are categorized as accident-prone areas, namely Jenderal Sudirman, Brigjend Katamso, HOS Cokroaminoto, Kusumanegara, and Magelang.

Geographical spatial analysis and risk prediction based on machine learning for maritime traffic accidents: A case study of Fujian sea area

Safety analysis according to the spatial distribution characteristics of maritime traffic accidents is critical to maritime traffic safety management. An accident analysis framework based on the geographic information system (GIS) is proposed to characterize the spatial distribution of maritime traffic accidents occurring in the Fujian sea area in 2007–2020 by employing kernel density estimation and spatial autocorrelation techniques. The sea area is divided into various grids, and in each grid, the mapping relationships between the number and severity of the traffic accidents and the traffic characteristics are established. Machine learning (ML) technology is used to assess whether a grid area is an accident-prone area and to predict accident severity in each grid. The accident prediction of different ML models, including random forest (RF) model, Adaboost model, gradient boosting decision tree (GBDT) model, and Stacking combined model, were compared. The optimality of the Stacking combined model was verified by comparing the experimental results of this model with those of classical prediction models, convolutional neural network (CNN), long short term memory (LSTM), and support vector machine (SVM). According to the results, the maritime accident data set of the entire Fujian sea area shows typical clustering characteristics and positive spatial correlation. That is, the kernel density estimation indicates that subareas, including the Ningde sea area, Fuzhou sea area, and Xiamen sea area, generally have high densities of maritime accidents and the highest risk value within the whole Fujian sea area. High-high accident clustering, that is high cluster areas neighbored by other areas of high cluster, is mainly seen in the Ningde and Fuzhou sea areas, while the Xiamen, Putian, and Zhangzhou subareas show low-low clustering, which are low clusters neighbored by low clusters. Among the ML models, the Stacking combined model shows high accuracy, precision, recall, and F1-score values of 0.912, 0.910, 0.912, and 0.904 in predicting whether a grid area is an accident-prone area and 0.750, 0.745, 0.750, and 0.746 in predicting the accident severity in the grid, indicating its superior maritime traffic accident prediction performance. Based on our analysis of the distribution characteristics and geospatial data, our proposed method demonstrates effective and reliable risk prediction.

Analysis on alteration of road traffic casualties in western China from multi-department data in recent decade.

Road traffic safety has considerably improved in China. However, the changes may differ in the economically backward and altitude higher western region. This study aims to investigate changes in the occurrence and severity of traffic casualties in western China and illuminate several key causal factors. Traffic accident data from the Annual Traffic Accident Statistics Report combined with population and vehicle data from the China Statistics Bureau between 2009 and 2019, were retrospectively analyzed. Traffic accident numbers, fatalities, human injury (HI), case fatality rates (CFR), mortality per 100,000 population (MRP), and mortality per 10,000 vehicles (MRV) were compared between the western and eastern regions. The HI, CFR, MRV, and MRP between the four groups based on the altitude of cities, below 500 meters, 500 to 1,500 meters, 1,500 to 3,000 meters, and over 3,000 meters, were compared using one-way analysis of variance. One hundred and seventy-eight cases of extremely serious traffic accidents were further analyzed in terms of accident occurrence time, vehicle type, road grade, road shape, accident pattern, and accident reason. The differences of accident characteristics between the eastern and western regions were compared using the chi-square test. The number of traffic accidents and fatalities decreased in low-altitude areas in western China. However, there was a significant increasing trend in the high altitude area. The HI, CFR, MRV, and MRP were higher in the western region than that in the eastern and national. Those accident indicators tended to increase with increasing altitude. And there were statistically significant differences (p < 0.05) among groups from different altitudes. Chi-square test results show that there are statistically significant differences (p < 0.05) in term of road grade, road shape, accident pattern between eastern and western. Low-grade roads, combined curved and sloping roads, and rollover were significant features associated with traffic accidents in the western region. Bad roads were the main cause of rollover accidents in western China, which will lead to more serious casualties. Over speeding, overloading, bad weather, vehicle failure, and driver error were the top five accident causes. Traffic accidents are increasing in high-altitude areas of western China, and they lead to more severe casualties. The characteristics of serious traffic accidents in this part of the country differ from those of the eastern regions. Improving road safety facilities, restrictions of speed, and improving medical treatment at accident scenes may be effective measures to reduce traffic accidents related injuries in the western region.

Analisa Kecelakaan Lalu Lintas di Ruas Jalan Bypass Ngurah Rai Kota Denpasar

The Ngurah Rai Bypass Road in Denpasar City is one of the roads that has a high accident rate. The Ngurah Rai Bypass accommodates traffic flow from the direction of Nusa Dua towards Denpasar City where the number of vehicles continues to increase every year, causing road conditions to become more congested and accidents to occur. The purpose of this study is to analyze the characteristics of traffic accidents on the Ngurah Rai Bypass Road and determine blacksites and blackspots. This study used a data collection method, namely secondary data for three years (2018 – 2020) obtained from the Denpasar City Police Traffic Unit. For calculations using the EAN method or equivalent accident number which is one of several calculation methods to determine accident-prone areas and points. The results of the analysis show that the number of accident incidents over the past three years (2018-2020) totaled 277 incidents with accident characteristics, namely the victim class with the highest level of severity was minor injuries (LR) of 298 people with a percentage of 67%, the highest accident time occurred at light time (06.00 -18.59) as many as 174 incidents with a percentage of 62.8%, the highest type of vehicle involved in an accident, namely motorbikes, 182 incidents with a percentage of 60.5%, the highest gender involved in an accident, namely men 261 people with a percentage of 58.7%, The highest age of victims involved in accidents was 17-30 years with 268 people with a percentage of 60.2%, the highest cause of accidents were road users (riders and pedestrians) with 260 incidents with a percentage of 93.9%. The 7 road segments that are categorized as blacksites on the Bypass Ngurah Rai road in Denpasar City are segment 25 (km 24-25), segment 28 (km 27-28), segment 13 (km 12-13), segment 9 (km 8- 9), segment 18 (km 17 – 18), segment 14 (km 13 – 14), segment 15 (km 14 – 15). Seven points are categorized as blackspots on the Denpasar City Bypass Ngurah Rai road, namely segment 25 (km 24.6 – 24.9), segment 28 (km 27.4 – 27.8), segment 13 (km 12 – 12.7), segment 9 (km 8.7 – 8.9), segment 18 (km 17 – 17.8), segment 14 (km 13 – 13.6), segment 15 (km 14.3 – 15).