scholarly journals Assessment of traffic safety at median openings using surrogate safety measures: a case study in India

2020 ◽  
Vol 80 (ET.2020) ◽  
pp. 1-12
Author(s):  
Malaya Mohanty
Keyword(s):  
Developing Countries ◽  
Traffic Safety ◽  
Transportation Engineering ◽  
Crash Data ◽  
Road Crashes ◽  
The Road ◽  
Sight Distance ◽  
Traffic Volumes ◽  
Road Crash ◽  
Stopping Sight Distance

Traffic safety is an integral part of transportation engineering. In developing countries, its importance is even more. Additionally, at uncontrolled median openings, the severity of road crashes increase many fold. Conventionally, road crash data were used to analyse safety. However, in developing countries, the accuracy of this data is highly questionable. Therefore, in this study, a new technique in addition to post encroachment time (PET), which is a surrogate safety measure is used to predict the severity of probable road crashes at median openings. After the extraction of PET values from field data, they have been compared with the minimum braking times obtained from calculation of minimum stopping sight distance. The comparison shows that while the number of road crashes may be less at lower traffic volume levels, however the severity of those crashes is much higher as compared to the road crashes occurring at high traffic volumes.

scholarly journals PENINGKATAN KESELAMATAN DI RUAS JALAN PANTURA KM 46–47 KECAMATAN PATROL KABUPATEN INDRAMAYU

2021 ◽  
Vol 21 (2) ◽  
pp. 101-108
Author(s):  
Arivia Shehera Kurniastuti ◽  
Novita Sari ◽  
Sulistyo Sutanto
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
North Coast ◽  
Traffic Signs ◽  
The Road ◽  
The North ◽  
Road Section ◽  
Sight Distance ◽  
Speed Management ◽  
Stopping Sight Distance

Abstract   The number of traffic accidents that occur in Indramayu Regency continues to increase and causes many casualties and material losses. From the available data, it is known that there is one road section which is an accident-prone area, namely the North Coast Java Road section, KM 46-47, which is located in Patrol District, Indramayu Regency. The flow and speed of traffic on this road is quite high, because of its function as a primary arterial road. This study aims to improve safety on the North Coast Java Road section, KM 46-47. The method used is in the form of observation and field data collection. Furthermore, the data obtained is processed, analyzed, and followed by formulating appropriate recommendations. This study shows that the main cause of accidents is the human factor, especially those related to high traffic speeds. To improve the existing conditions, it is proposed to provide road equipment, especially traffic signs, which are adjusted to the stopping sight distance required by motorized vehicles using the road. In addition, it is necessary to apply speed management as part of efforts to improve traffic safety.   Keywords: traffic accident; stopping sight distance; road equipment, traffic speed; traffic signs.     Abstrak   Angka kecelakaan lalu lintas yang terjadi di Kabupaten Indramayu terus meningkat dan menyebabkan banyak korban jiwa dan kerugian material. Dari data yang ada diketahui bahwa terdapat satu ruas jalan yang termasuk daerah rawan kecelakaan, yaitu ruas Jalan Pantai Utara Jawa, KM 46-47, yang terletak di Kecamatan Patrol, Kabupaten Indramayu. Arus dan kecepatan lalu lintas di ruas jalan tersebut cukup tinggi, karena fungsinya sebagai jalan arteri primer. Studi ini bertujuan untuk meningkatkan keselamatan di ruas Jalan Pantai Utara Jawa KM 46-47. Metode yang digunakan berupa observasi dan pengumpulan data lapangan. Selanjutnya data yang diperoleh diolah, dianalisis, kemudian dirumuskan rekomendasi yang tepat. Studi ini menunjukkan bahwa faktor penyebab kecelakaan yang utama adalah faktor manusia, khususnya yang berhubungan dengan kecepatan lalu lintas yang tinggi. Untuk memperbaiki kondisi yang ada, diusulkan pemberian perlengkapan jalan, khususnya rambu lalu lintas, yang disesuaikan dengan jarak pandang henti yang diperlukan oleh kendaraan bermotor yang melintasi jalan tersebut. Selain itu perlu diterapkan manajemen kecepatan sebagai bagian upaya meningkatkan keselamatan lalu lintas.   Kata-kata kunci: kecelakaan lalu lintas; jarak pandang henti; perlengkapan jalan, kecepatan lalu lintas; rambu lalu lintas.

scholarly journals Practical Minimum Sample Size for Road Crash Time-Series Prediction Models

2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Fady M. A. Hassouna ◽  
Khaled Al-Sahili
Keyword(s):  
Sample Size ◽  
Traffic Safety ◽  
Prediction Accuracy ◽  
Prediction Models ◽  
Sample Sizes ◽  
Crash Prediction ◽  
Crash Data ◽  
Road Crashes ◽  
Stable Conditions ◽  
Road Crash

Road crashes are problems facing the transportation sector. Crash data in many countries are available only for the past 10 to 20 years, which makes it difficult to determine whether the data are sufficient to establish reasonable and accurate prediction rates. In this study, the effect of sample size (number of years used to develop a prediction model) on the crash prediction accuracy using Autoregressive integrated moving average (ARIMA) method was investigated using crash data for years 1971–2015. Based on the availability of annual crash records, road crash data for four selected countries (Denmark, Turkey, Germany, and Israel) were used to develop the crash prediction models based on different sample sizes (45, 35, 25, and 15 years). Then, crash data for 2016 and 2017 were used to verify the accuracy of the developed models. Furthermore, crash data for Palestine were used to test the validity of the results. The used data included fatality, injury, and property damage crashes. The results showed similar trends in the models’ prediction accuracy for all four countries when predicting road crashes for year 2016. Decreasing the sample sizes led to less prediction accuracy up to a sample size of 25; then, the accuracy increased for the 15-year sample size. Whereas there was no specific trend in the prediction accuracy for year 2017, a higher range of prediction error was also obtained. It is concluded that the prediction accuracy would vary based on the varying socioeconomic, traffic safety programs and development conditions of the country over the study years. For countries with steady and stable conditions, modeling using larger sample sizes would yield higher accuracy models with higher prediction capabilities. As for countries with less steady and stable conditions, modeling using smaller sample sizes (15 years, for example) would lead to high accuracy models with good prediction capabilities. Therefore, it is recommended that the socioeconomic and traffic safety program status of the country is considered before selecting the practical minimum sample size that would give an acceptable prediction accuracy, therefore saving efforts and time spent in collecting data (more is not always better). Moreover, based on the data analysis results, long-term ARIMA prediction models should be used with caution.

scholarly journals Exploring European Heavy Goods Vehicle Crashes Using a Three-Level Analysis of Crash Data

2022 ◽  
Vol 19 (2) ◽  
pp. 663
Author(s):  
Ron Schindler ◽  
Michael Jänsch ◽  
András Bálint ◽  
Heiko Johannsen
Keyword(s):  
System Development ◽  
Information Access ◽  
The European Union ◽  
Crash Data ◽  
Road Crashes ◽  
The Road ◽  
Passive Safety Systems ◽  
Road Crash ◽  
Causation Analysis ◽  
Level Analysis

Heavy goods vehicles (HGVs) are involved in 4.5% of police-reported road crashes in Europe and 14.2% of fatal road crashes. Active and passive safety systems can help to prevent crashes or mitigate the consequences but need detailed scenarios based on analysis of region-specific data to be designed effectively; however, a sufficiently detailed overview focusing on long-haul trucks is not available for Europe. The aim of this paper is to give a comprehensive and up-to-date analysis of crashes in the European Union that involve HGVs weighing 16 tons or more (16 t+). The identification of the most critical scenarios and their characteristics is based on a three-level analysis, as follows. Crash statistics based on data from the Community Database on Accidents on the Roads in Europe (CARE) provide a general overview of crashes involving HGVs. These results are complemented by a more detailed characterization of crashes involving 16 t+ trucks based on national road crash data from Italy, Spain, and Sweden. This analysis is further refined by a detailed study of crashes involving 16 t+ trucks in the German In-Depth Accident Study (GIDAS), including a crash causation analysis. The results show that most European HGV crashes occur in clear weather, during daylight, on dry roads, outside city limits, and on nonhighway roads. Three main scenarios for 16 t+ trucks are characterized in-depth: rear-end crashes in which the truck is the striking partner, conflicts during right turn maneuvers of the truck with a cyclist riding alongside, and pedestrians crossing the road in front of the truck. Among truck-related crash causes, information admission failures (e.g., distraction) were the main crash causation factor in 72% of cases in the rear-end striking scenario while information access problems (e.g., blind spots) were present for 72% of cases in the cyclist scenario and 75% of cases in the pedestrian scenario. The three levels of data analysis used in this paper give a deeper understanding of European HGV crashes, in terms of the most common crash characteristics on EU level and very detailed descriptions of both kinematic parameters and crash causation factors for the above scenarios. The results thereby provide both a global overview and sufficient depth of analysis of the most relevant cases and aid safety system development.

scholarly journals Calculating TIN-Based 3D Sight Distance and Its Evaluation on Drivers Free-Flow Speed

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Ali Sahaf ◽  
Ali Abdoli ◽  
Abolfazl Mohamadzadeh Moghaddam
Keyword(s):  
Traffic Safety ◽  
Flow Speed ◽  
Night Vision ◽  
Free Flow ◽  
Analysis Model ◽  
Change Rate ◽  
The Road ◽  
Sight Distance ◽  
Free Flow Speed ◽  
Stopping Sight Distance

Sight distance during driving may be limited by side factors such as mountain slopes or trees and buildings in horizontal curves and by the dome of the arc in vertical curves, and the night vision also can be limited in the sag vertical curves by the vehicle’s light. Analyzing driver’s sight distance in the road is very important for traffic safety. In this regard, in order to help the designer, the current rules and guidelines propose the two-dimensional analysis model for the sight distance. In this analysis, the sight distance is calculated separately in the combination of horizontal and vertical curves, and the smallest amount is considered as the sight distance. While, after constructing and operating the road, drivers control their vehicle according to the conditions in their 3D space. Nowadays, given the remarkable advances in computer science, there are many possibilities for 3D modeling of the route. In this research, the goal is to calculate the three-dimensional stopping sight distance at each spatial point by computer modeling the existing roads. The speed of various drivers with conventional riding vehicles under free traffic conditions was obtained by a GPS device. The results showed that, in places such as curves, given the provision of sufficient stopping sight distance, driver’s free-flow speed reduces. Thus, another factor affecting the speed of the drivers is the curvature change rate. Finally, using nonlinear regression modeling a logical relationship was determined and extracted between the three factors of driver’s free-flow speed, 3D stopping sight distance, and curvature change rate of the path.

scholarly journals Lower Volumes, Higher Speeds: Changes to Crash Type, Timing, and Severity on Urban Roads from COVID-19 Stay-at-Home Policies

2021 ◽  
pp. 036119812110444
Author(s):  
Jonathan Stiles ◽  
Armita Kar ◽  
Jinhyung Lee ◽  
Harvey J. Miller
Keyword(s):  
Logistic Regression ◽  
Traffic Safety ◽  
Travel Demand ◽  
Multinomial Logistic Regression ◽  
High Volume ◽  
Time Of Day ◽  
Bayesian Hierarchical ◽  
Crash Data ◽  
The Road ◽  
At Home

Stay-at-home policies in response to COVID-19 transformed high-volume arterials and highways into lower-volume roads, and reduced congestion during peak travel times. To learn from the effects of this transformation on traffic safety, an analysis of crash data in Ohio’s Franklin County, U.S., from February to May 2020 is presented, augmented by speed and network data. Crash characteristics such as type and time of day are analyzed during a period of stay-at-home guidelines, and two models are estimated: (i) a multinomial logistic regression that relates daily volume to crash severity; and (ii) a Bayesian hierarchical logistic regression model that relates increases in average road speeds to increased severity and the likelihood of a crash being fatal. The findings confirm that lower volumes are associated with higher severity. The opportunity of the pandemic response is taken to explore the mechanisms of this effect. It is shown that higher speeds were associated with more severe crashes, a lower proportion of crashes were observed during morning peaks, and there was a reduction in types of crashes that occur in congestion. It is also noted that there was an increase in the proportion of crashes related to intoxication and speeding. The importance of the findings lay in the risk to essential workers who were required to use the road system while others could telework from home. Possibilities of similar shocks to travel demand in the future, and that traffic volumes may not recover to previous levels, are discussed, and policies are recommended that could reduce the risk of incapacitating and fatal crashes for continuing road users.

scholarly journals A Surrogate Video-Based Safety Methodology for Diagnosis and Evaluation of Low-Cost Pedestrian-Safety Countermeasures: The Case of Cochabamba, Bolivia

2019 ◽  
Vol 11 (17) ◽  
pp. 4737
Author(s):  
Lynn Scholl ◽  
Mohamed Elagaty ◽  
Bismarck Ledezma-Navarro ◽  
Edgar Zamora ◽  
Luis Miranda-Moreno
Keyword(s):  
Developing Countries ◽  
Latin American ◽  
Traffic Safety ◽  
Road Safety ◽  
Low Cost ◽  
Video Data ◽  
Crash Risk ◽  
Video Analytics ◽  
Crash Data ◽  
Safety Countermeasures

Due to a lack of reliable data collection systems, traffic fatalities and injuries are often under-reported in developing countries. Recent developments in surrogate road safety methods and video analytics tools offer an alternative approach that can be both lower cost and more time efficient when crash data is incomplete or missing. However, very few studies investigating pedestrian road safety in developing countries using these approaches exist. This research uses an automated video analytics tool to develop and analyze surrogate traffic safety measures and to evaluate the effectiveness of temporary low-cost countermeasures at selected pedestrian crossings at risky intersections in the city of Cochabamba, Bolivia. Specialized computer vision software is used to process hundreds of hours of video data and generate data on road users’ speed and trajectories. We find that motorcycles, turning movements, and roundabouts, are among the key factors related to pedestrian crash risk, and that the implemented treatments were effective at four-legged intersections but not at traditional-design roundabouts. This study demonstrates the applicability of the surrogate methodology based on automated video analytics in the Latin American context, where traditional methods are challenging to implement. The methodology could serve as a tool to rapidly evaluate temporary treatments before they are permanently implemented and replicated.

Examining the factors affecting the severity of run-off-road crashes in Abu Dhabi

2016 ◽  
Vol 43 (2) ◽  
pp. 132-138 ◽  
Author(s):  
Mohamed Shawky ◽  
Hany M. Hassan ◽  
Atef M. Garib ◽  
Hussain A. Al-Harthei
Keyword(s):  
Traffic Safety ◽  
Surface Condition ◽  
Probit Model ◽  
Abu Dhabi ◽  
Factors Affecting ◽  
Environment Factors ◽  
Crash Data ◽  
Road Crashes ◽  
Run Off ◽  
Road Type

Recently, the severity of injuries resulting from traffic crashes has been extensively investigated in numerous studies. However, the number of studies that addressed the severity of the run-off-road (ROR) crashes is relatively low. In the Emirate of Abu Dhabi (AD), approximately 22% of the total serious crashes and fatalities that occurred from 2007 to 2013 were ROR crashes. Despite these facts and the uniqueness of the composition of licensed drivers in AD (approximately 87% of them are non-Emiratis), the factors affecting the occurrence and severity of ROR crashes in AD have not been explicitly addressed in any prior studies. Therefore, this study aims to investigate the characteristics of at-fault drivers involved in ROR crashes in AD, the nature and main causes of those crashes. In this regard, conditional distribution and two-way contingency tables were developed. In addition, this study aims to identify and quantify the factors affecting the severity of ROR crashes such as driver, road, vehicle and environment factors. To achieve this goal, ordered probit model approach was employed. Crash data for a total of 3819 ROR crashes that occurred in AD were employed in the analysis. The results indicated that driver factors (carelessness, speeding, and nationality), vehicle characteristics (vehicle type), and road and environment factors (road type, crash location and road surface condition) were the significant factors influencing the severity of ROR crashes in AD. Countermeasures to improve traffic safety and reduce numbers and severity of ROR crashes in AD were discussed.

scholarly journals Practice Analysis of Road Traffic Crashes Accident of a City in China

2012 ◽  
Vol 5 ◽  
pp. 105-110
Author(s):  
Li Wei Hu ◽  
Jian Xiong
Keyword(s):  
Traffic Safety ◽  
Road Traffic ◽  
Crash Severity ◽  
Crash Analysis ◽  
Expected Number ◽  
Traffic Crashes ◽  
Road Traffic Crashes ◽  
Road Crashes ◽  
The Road ◽  
Types Of Information

Many studies focused on the development of crash analysis approaches have resulted in aggregate practices and experiences to quantify the safety effects of human, geometric, traffic and environmental factors on the expected number of deaths, injuries, and/or property damage crashes at specific locations. Traffic crashes on roads are a major cause of road crashes in the metropolitan area of Xi’an. In an attempt to identify causes and consequences, reported traffic crashes for six years in Xi’an were analyzed using a sample of 2038 reports. The main types of information from such reports were extracted, coded, and statistically analyzed. Important results were obtained from frequency analyses as well as multiple contributory factors related to traffic crashes, including crash severity, time and location of occurrence, geometry of the road, AADT and v/c. This paper presents the results of such analyses and provides some recommendations to improve traffic safety and further studies to analyze potential crash locations.

A Territorial Dimension Can Be Useful for Managing Long-Term Regional Road Safety

2019 ◽  
pp. 248-267
Author(s):  
Alessandro Sciullo ◽  
Sylvie Occelli
Keyword(s):  
Spatial Data ◽  
Population Distribution ◽  
Local Level ◽  
Crash Data ◽  
Road Crashes ◽  
Fine Grained ◽  
Urban Settlements ◽  
Road Crash ◽  
Main Observation ◽  
Gis Methods

Analysis of road crashes at the local level is necessary for targeting and implementing effective countermeasures. This chapter presents a contribution to this task. It describes the research carried out in Piedmont, Italy, where an exploratory approach has been used to link road crash data with information about the spatial characteristics of urban settlements. The analytic strategy is developed in three steps. First, fine-grained spatial data for road crashes, land use, traffic counts, and population distribution are linked by GIS methods. Second, a selection of the data is implemented at the municipality level and processed through a cluster analysis to identify territorial accident profiles. Finally, to show their analytic potential, one case study is discussed that considers road segments as main observation units.

Evaluation of Roundabout-Related Single-Vehicle Crashes

2017 ◽  
Vol 2637 (1) ◽  
pp. 17-26 ◽  
Author(s):  
Beau Burdett ◽  
Andrea R. Bill ◽  
David A. Noyce
Keyword(s):  
Negative Binomial ◽  
Vehicle Crashes ◽  
Impaired Driving ◽  
Crash Data ◽  
Road Crashes ◽  
Run Off ◽  
Traffic Volumes ◽  
Single Vehicle ◽  
Total Proportion ◽  
Crash Types

Roundabouts reduce fatal and injury crashes at intersections when converted from other intersection control types. In Wisconsin, roundabouts have been linked to a 38% decrease in fatal and injury crashes. Part of this reduction can be attributed to crash types that result in the mitigation of more serious injuries. However, the reduction comes at a cost because other crash types, such as single-vehicle collisions, may increase. Six years of crash data on 53 roundabouts in Wisconsin were examined for crash causes and geometric characteristics that affected single-vehicle crashes. Weather and impaired driving, particularly by younger drivers, were primary causes for more than half of all single-vehicle crashes at the study roundabouts. Younger drivers (18 to 24 years of age) were involved in a significantly higher proportion of single-vehicle crashes than the total proportion of licensed drivers in that age group. Younger drivers were involved in approximately one-third of all crashes that involved impaired driving and in two-thirds of all speed-related single-vehicle crashes. A negative binomial model was constructed to estimate run-off-road crashes at approaches. It was found that roundabouts with higher approach speeds and higher traffic volumes experienced more run-off-road crashes. Landscaped central islands experienced significantly lower frequencies of run-off-road crashes.

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