scholarly journals PENENTUAN SIMPANG BERSINYAL RAWAN KECELAKAAN UNTUK IDENTIFIKASI AWAL TERHADAP POTENSI RED LIGHT RUNNING (RLR) DI BANDA ACEH

2019 ◽  
Vol 2 (1) ◽  
pp. 21
Author(s):  
Sofyan M. Saleh ◽  
Sugiarto Sugiarto ◽  
Endang Handayani
Keyword(s):  
Traffic Accidents ◽  
Red Light ◽  
Highway Safety ◽  
Improvement Program ◽  
Red Light Running ◽  
Highway Safety Manual ◽  
Safety Improvement ◽  
Depth Study ◽  
Accident Data ◽  
Equivalent Property

Red Light Running (RLR) is the leading cause of traffic accidents at signal intersections in various countries, including Indonesia. The main reason is the existence of conflicts caused by drivers' behavioral factors who are not obedient or understand about signaling operations. RLR is the most dangerous driver's behavior in a signal intersection, where the driver fails to comply with signaling rules at the intersection so that the conflict occurs. To assess the behavior of the RLR, the first step is to identify the signaled intersections that are most prone to accidents. This is needed to eliminate the location of study or handling due to limited time and costs. The methodology used to determine accident-prone locations is based on the Highway Safety Improvement Program in the Highway Safety Manual (HSM, 2010), namely the planning component consisting of data collection and identification of accident-prone areas in signal intersections. Using accident data of 2013-2015, and by combining three methods of analysis such as frequency, accident rate, and equivalent property damage only methods, then three most accident-prone signal intersections are determined and prioritized for in-depth study of RLR behavior analysis. Red Light Running (RLR) adalah penyebab utama kecelakaan lalu lintas pada simpang bersinyal di berbagai negara termasuk Indonesia. Penyebab utamanya adalah adanya konflik yang diakibatkan oleh faktor perilaku pengemudi yang tidak patuh atau paham tentang pengoperasian persinyalan. RLR merupakan perilaku pengemudi yang paling berbahaya pada simpang bersinyal, dimana pengemudi gagal mematuhi peraturan persinyalan pada simpang sehingga konflik terjadi. Untuk mengkaji perilaku pada RLR perlu dilakukan langkah awal yaitu identifikasi simpang bersinyal yang paling rawan terhadap kecelakaan. Hal ini diperlukan untuk mengeliminasi lokasi kajian atau penanganan akibat keterbatasan waktu dan biaya. Metodologi yang digunakan untuk penentuan lokasi rawan kecelakaan dilakukan mengacu pada Highway Safety Improvement Program di dalam Highway Safety Manual (HSM, 2010), yaitu planning component yang terdiri dari pengumpulan data dan identifikasi daerah rawan kecelakaan pada simpang bersinyal. Menggunakan data kecelakaan tahun 2013-2015 dengan mengombinasikan tiga metode analisis yaitu metode frekuensi, tingkat kecelakaan dan ekuivalensi kerugian harta benda (EPDO) ditentukan tiga simpang bersinyal yang paling rawan kecelakaan dan diprioritaskan untuk dilakukan kajian mendalam terhadap perilaku pelanggaran RLR.

Tools to Identify Safety Issues for a Corridor Safety-Improvement Program

2000 ◽  
Vol 1717 (1) ◽  
pp. 19-27 ◽  
Author(s):  
Jerome P. Breyer
Keyword(s):  
Relational Databases ◽  
Safety Evaluation ◽  
Highway Safety ◽  
New Paradigm ◽  
Safety Hazards ◽  
Improvement Program ◽  
Satellite Systems ◽  
Safety Issues ◽  
Advanced Technologies ◽  
Safety Improvement

The Arizona Department of Transportation (ADOT) recognizes that a new paradigm in highway safety evaluation was brought about by the advent of advanced technologies such as photo log, geographic information systems (GIS), and global-positioning satellite systems. Whereas these technologies are known to serve distinct singular purposes in a highway agency, ADOT has endeavored to explore the possibilities of integrating these technologies for the purpose of providing an all-encompassing perspective of crash history and roadside characteristics in a multimedia display of GIS maps and related photo imagery. The research provides the account of an analytic tool-development process aimed at improving the recognition of highway safety hazards. These hazards might otherwise be apparent if not for the relative complexity of existing relational databases and spatial GIS infrastructure at ADOT. Previous methods of mining data from the ADOT crash databases were limited in functionality as well as in reliability. By promoting the “visualization” of highway safety conditions, the advanced technologies open a wealth of new opportunities in identifying problematic roadside conditions and crash histories. This is expected to lead to an improved economy of implementing safety improvements that are designed properly to mitigate the “real” conditions that can be identified. The research is a companion to the larger, FHWA-sponsored research into establishing a corridor safety-improvement program for Arizona (FHWA Report FHWA-AZ 98-458).

scholarly journals Selection and assessment of the relevant data for reducing the number of red-light running

Transport ◽  
2016 ◽  
Vol 33 (1) ◽  
pp. 268-279
Author(s):  
Milan Vujanić ◽  
Dalibor Pešić ◽  
Boris Antić ◽  
Nenad Marković
Keyword(s):  
Traffic Accidents ◽  
Road Traffic ◽  
Statistical Significance ◽  
Red Light ◽  
Risk Indicator ◽  
Traffic Light ◽  
Anova Analysis ◽  
Red Light Running ◽  
The City ◽  
Selection And Assessment

Although traffic light controlled intersections separate, the traffic flows by time and space, road traffic accidents still occur, usually due to Red-Light Running (RLR). In order to define countermeasures to solve this problem, it is necessary to collect and analyze certain data that will indicate type of measures, which should be applied. In this paper, it was done on the example of one 3-leg and one 4-leg intersection where citizens provided information about frequent RLR to the City Administration of Belgrade (Serbia). The statistical significance of differences between the collected data was tested by ANOVA analysis and by PostHoc Tukey test, which showed that forecasting of second of RLR after red-light onset could effectively be conducted by Cubic distribution. In order to define the so-called RLR risk indicator for the intersection, the use of the Danger Degree (DD) indicator, that presents the rate between the number of dangerous situations caused by RLR and the total number of RLR, was proposed.

scholarly journals Exploring the Application of the Linear Poisson Autoregressive Model for Analyzing the Dynamic Impact of Traffic Laws on Fatal Traffic Accident Frequency

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Yue Zhang ◽  
Yajie Zou ◽  
Lingtao Wu ◽  
Jinjun Tang ◽  
Malik Muneeb Abid
Keyword(s):  
Traffic Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Moving Average ◽  
Red Light ◽  
Dynamic Impact ◽  
Temperature And Precipitation ◽  
Accident Data ◽  
Poisson Autoregressive Model

Annual fatal traffic accident data often demonstrate time series characteristics. The existing traffic safety analysis approaches (e.g., negative binomial (NB) model) often cannot accommodate the dynamic impact of factors in fatal traffic accident data and may result in biased parameter estimation results. Thus, a linear Poisson autoregressive (PAR) model is proposed in this study. The objective of this study is to apply the PAR model to analyze the dynamic impact of traffic laws and climate on the frequency of fatal traffic accidents occurred in a large time span (from 1975 to 2016) in Illinois. Besides, the NB model, NB with a time trend, and autoregressive integrated moving average model with exogenous input variables (ARIMAX) are also developed to compare their performances. The important conclusions from the modelling results can be summarized as follows. (1) The PAR model is more appropriate for analyzing the dynamic impacts of traffic laws on annual fatal traffic accidents, especially the instantaneous impacts. (2) The law that allows motorcycles and bicycles to proceed on a red light following the rules applicable after a “reasonable period of time” leads to an increase in the frequency of annual fatal traffic accidents by 14.98% in the short term and 30.69% in the long term. The climate factors such as average temperature and precipitation concentration period have insignificant impacts on annual fatal traffic accidents in Illinois. Thus, the modelling results suggest that the PAR model is more appropriate for annual fatal traffic accident data and has an advantage in estimating the dynamic impact of traffic laws.

High-Risk Road Accident Corridors in Dhaka, Bangladesh

2013 ◽  
Vol 65 (3) ◽  
Author(s):  
Ishtiaque Ahmed ◽  
Bayes Ahmed ◽  
Mohd. Rosli Hainin
Keyword(s):  
High Risk ◽  
Traffic Accident ◽  
Safety Management ◽  
Road Transport ◽  
Road Accident ◽  
Highway Safety ◽  
Road Accidents ◽  
Highway Safety Manual ◽  
Roadway Safety ◽  
Accident Data

Bangladesh has one of the highest fatality rates in road accidents and to address the safety problem is a serious concern. Dhaka is the most vulnerable city of the country. Bangladesh Road Transport Authority maintains a database of accidents using outdated software that lacks in geo-referencing facility.  This makes the analysis of accident locations a challenging task. The area for this study was the Dhaka Metropolitan Police area where the concerned forty one police stations are responsible for collecting traffic accident data. The Highway Safety Manual identifies the “Network Screening” as the first step of the Roadway Safety Management Process. This study focuses on locating the accidents on urban roadways in Dhaka and identifies thirty corridors and ranks them using geo-referenced data through developing and using a GIS database. Dhaka-Mymensing Road was found to be the most vulnerable road corridor followed by Airport Road and Mirpur Road respectively. The study recommended special attention and special “Diagnostic” studies as explained in the Highway Safety Manual for the high-risk corridors and to put emphasis on the accident data collection and reporting system. Adoption of modern technologies like GPS and GIS in collecting and reporting of the traffic accident data was emphasized.

scholarly journals Non-motorized Vehicle Traffic Accidents in China: Analysing Road Users’ Precrash Behaviors and Implications for Road Safety

2021 ◽  
Vol 11 (1) ◽  
pp. 105-116
Author(s):  
Xiaoxia Xiong ◽  
Shuichao Zhang ◽  
Lin Guo
Keyword(s):  
Road Safety ◽  
Traffic Accident ◽  
Traffic Accidents ◽  
Rough Set Theory ◽  
Red Light ◽  
Police Department ◽  
Red Light Running ◽  
Road Users ◽  
Different Types ◽  
Motorized Vehicles

The paper aims to explore underlying patterns of non-motorized vehicle (NM, including both regular bicycles and e-bikes) traffic accident occurrences based on precrash behaviors. A quarter-year data of NM accidents was collected by Yinzhou Traffic Police Department of Ningbo, China. Descriptive statistics and Rough Set theory were used to examine rules within different types of NM accidents from temporal, spatial, and behavioral aspects. Some main findings include: behavior patterns of different parties involved vary across different accident types, levels of roads, and intersections; motorized vehicle’s illegal turning as well as NM’s reverse riding are the two key behaviors that deserve concern across all levels of roads and intersection; in addition, for higher level urban roads more attention should be focused on lane violations of motorized vehicles, and for branch roads and intersections prevention efforts could be directed to motorized vehicles’ illegal turning around and NM’s red-light running respectively. Results from this paper could facilitate related staff formulating more targeted policies to make roadways safer.

scholarly journals Investigating Different Types of Red-Light Running Behaviors among Urban e-Bike Rider Mixed Groups

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Fan Zhang ◽  
Chenchen Kuai ◽  
Huitao Lv ◽  
Wenhao Li
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Unobserved Heterogeneity ◽  
Red Light ◽  
Multinomial Logit Model ◽  
Time Of Day ◽  
Signalized Intersections ◽  
Traffic Light ◽  
Safety Level ◽  
Red Light Running

The red-light running (RLR) behaviors of urban mixed e-bike groups (delivery and ordinary e-bike) have become the main cause of traffic accidents at signalized intersections. The primary purpose of this study is to identify influencing factors of e-bike riders’ RLR behaviors, focusing on the role of delivery e-bike riders in mixed e-bike rider groups. Crossing behaviors of 4,180 e-bike samples (2006 delivery e-bikes and 2174 ordinary e-bikes) at signalized intersections are observed in Xi’an, China. The random parameter multinomial logit model is employed to capture the unobserved heterogeneous effects, and the effects of interaction terms are also considered. The results indicate that delivery e-bike riders are more likely to run red lights than ordinary e-bike riders. E-bike type, riders’ age, waiting position, traffic volume, traffic light type, and time of day are associated with crossing behaviors in urban mixed e-bike groups. In addition, the variable of traffic light status is found to account for unobserved heterogeneity. Findings are indicative to the development of effective implications in improving e-bikes’ traffic safety level at signalized intersections.

Examining Fatal Crash Reductions by First Harmful Events since the Introduction of the Federal Highway Safety Improvement Program

2013 ◽  
Vol 2364 (1) ◽  
pp. 51-61 ◽  
Author(s):  
Kun-Feng Wu ◽  
Scott C. Himes ◽  
Martin T. Pietrucha
Keyword(s):  
Fixed Effects ◽  
Motor Vehicle ◽  
Spillover Effects ◽  
Highway Safety ◽  
Motor Vehicles ◽  
Improvement Program ◽  
Fatal Crash ◽  
Fatal Crashes ◽  
Safety Improvement ◽  
Federal Highway

The federal Highway Safety Improvement Program (HSIP) has been associated with the reduction in fatal crashes since 2006, but the reasons for the reduction remain largely unknown. This paper examines the reduction in fatal crashes in terms of different types of first harmful events that can provide insight into crash causes and prevention strategies. In this study, fatal crashes were categorized into four types: overturn, collision with motor vehicle in transport, collision with fixed object, and collision with nonmotorist. Fixed-effects and mixed-effects Poisson models were used to estimate the magnitudes of fatal crash reduction by first harmful events for each state. Fatal crashes due to collisions with nonmotorists and motor vehicles in transport have been reduced by 10% and 5.3%, respectively, compared with the 2001 to 2005 period. Fatal crashes due to overturn and collision with a fixed object decreased in some states but remained unchanged or increased in other states. Nevertheless, the numbers of national fixed-object and overturn fatal crashes have been reduced by 3% and 0.7%, respectively, as a whole. This study also investigated possibilities that could be associated with the magnitudes of the reductions, for example, the different traffic laws among states. It was found that although different safety improvement projects were implemented to target the various types of crashes, the improvements were also likely to be beneficial to other crash types. These are referred to as spillover effects. Nationally, fatal crashes have decreased since the introduction of the HSIP partly because of the reduction in fatal crashes due to collisions with nonmotorists and motor vehicles in transport and partly because of spillover effects.

scholarly journals BLACKSPOTS IDENTIFICATION AND ACCIDENT ANALYSIS OF INDUS HIGHWAY (N-55)

2020 ◽  
Vol 15 (11) ◽  
Author(s):  
Muhammad Majid Naeem
Keyword(s):  
High Speed ◽  
Traffic Accidents ◽  
Safety Management ◽  
Road Traffic ◽  
Human Life ◽  
Highway Safety ◽  
Transportation Engineering ◽  
Geometric Problems ◽  
Accident Data ◽  
Investigation Report

Traffic accidents are unavoidable in human life therefore highway safety is one of the most important factors of transportation engineering. After the advent of National highways and freeways, developing nations including Pakistan is facing new dimensions of highway safety challenges, highway safety management demands more attention due to the involvement of high-speed dynamics. This study presents a method by which accident-prone locations commonly termed as Blackspots are been identified. A stretch of 188 KM of National Highway N-55 also known as Indus highway from Peshawar to Lakki Marwat has been selected for the study. Road traffic accident data was only available with local district police in a manual file record (First Investigation Report). Accident data were collected from nine police stations along the selected route for seven years i.e. from 2013 to 2019. After analysis, it was found that most of the accidents occurred due to over speeding and geometric problems. Moreover, it was also found that there are no proper pedestrian crossings. The data was analyzed month and year wise. Fourteen such locations on which five or more fatalities occurred were identified as blackspots. The blackspots are within the range of 1KM.

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