A Study on the Improvement of Unprotected and U-turn System under the Road Traffic Act in Korea - Comparative review with foreign institutions such as Japan -

2019 ◽  
Vol 12 (3) ◽  
pp. 75-128
Author(s):  
Seungyup Baik ◽  
Author(s):  
Amolkirat Singh ◽  
Guneet Saini

Many people lose their life and/or are injured due to accidents or unexpected events taking place on road networks. Besides traffic jams, these accidents generate a tremendous waste of time and fuel. Undoubtedly, if the vehicles are provided with timely and dynamic information related to road traffic conditions, any unexpected events or accidents, the safety and efficiency of the transportation system with respect to time, distance, fuel consumption and environmentally destructive emissions can be improved. In the field of computer and information science, Vehicular Ad hoc Network (VANET) have recently emerged as an effective tool for improving road safety through propagation of warning messages among the vehicles in the network about potential obstacles on the road ahead. VANET is a research area which is in more demand among the researchers, the automobile industries and scientists to discover about the loopholes and advantages of the vehicular networks so that efficient routing algorithms can be developed which can provide reliable and secure communication among the mobile nodes.In this paper, we propose a Groundwork Based Ad hoc On Demand Distance Vector Routing Protocol (GAODV) focus on how the Road Side Units (RSU’s) utilized in the architecture plays an important role for making the communication reliable. In the interval of finding the suitable path from source to destination the packet loss may occur and the delay also is counted if the required packet does not reach the specified destination on time. So to overcome delay, packet loss and to increase throughput GAODV approach is followed. The performance parameters in the GAODV comes out to be much better than computed in the traditional approach.


Author(s):  
Byeongjoon Noh ◽  
Dongho Ka ◽  
David Lee ◽  
Hwasoo Yeo

Road traffic accidents are a leading cause of premature deaths and globally pose a severe threat to human lives. In particular, pedestrians crossing the road present a major cause of vehicle–pedestrian accidents in South Korea, but we lack dense behavioral data to understand the risk they face. This paper proposes a new analytical system for potential pedestrian risk scenes based on video footage obtained by road security cameras already deployed at unsignalized crosswalks. The system can automatically extract the behavioral features of vehicles and pedestrians, affecting the likelihood of potentially dangerous situations after detecting them in individual objects. With these features, we can analyze the movement patterns of vehicles and pedestrians at individual sites, and understand where potential traffic risk scenes occur frequently. Experiments were conducted on four selected behavioral features: vehicle velocity, pedestrian position, vehicle–pedestrian distance, and vehicle–crosswalk distance. Then, to show how they can be useful for monitoring the traffic behaviors on the road, the features are visualized and interpreted to show how they may or may not contribute to potential pedestrian risks at these crosswalks: (i) by analyzing vehicle velocity changes near the crosswalk when there are no pedestrians present; and (ii) analyzing vehicle velocities by vehicle–pedestrian distances when pedestrians are on the crosswalk. The feasibility of the proposed system is validated by applying the system to multiple unsignalized crosswalks in Osan city, South Korea.


2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.


2014 ◽  
Vol 23 (5) ◽  
pp. 567-585
Author(s):  
Muhammad Masood Rafi ◽  
Ashar Hashmat Lodi ◽  
Muhammad Arsalan Effendi

Purpose – Road traffic crashes (RTCs) result in creating significant social and economic hazard for affectees, their families and society. The purpose of this paper is to present studies which were conducted to study the patterns of RTCs in Karachi which is a metropolitan city of Pakistan. The studies were conducted on one of the busiest roads in the city named as Shara-e-Faisal. The influence and contribution of different factors in RTCs has been studied and hazardous road sections of Shara-e-Faisal have been identified. Based on the data analysis, an evaluation model has been suggested to reduce the hazard of RTCs on Shara-e-Faisal. The objective of the presented studies is to increase the present level of safety of road travel by reducing crashes on Shara-e-Faisal. Design/methodology/approach – Existing data of RTCs in Karachi have been analysed for the presented studies. For this purpose, Shara-e-Faisal was divided in sections of 1 km length to study the vehicle crash pattern. Location surveys were conducted to record physical conditions of this road. A cluster analysis was carried out to identify hazardous sections of the road. An evaluation model has been suggested in the end to reduce the hazard of RTCs by identifying hazardous road sections of Shara-e-Faisal. Findings – The analysis of the data revealed that the crashes were higher over weekend and on Monday. Male population, particularly young people, and motorcycle riders were the largest affectees of RTCs. In general, more daytime crashes were recorded as compared to nighttime crashes. The crashes in the mid block of the road and those involving rear-end collisions were higher. The hazardous road locations were related to poor road conditions. Statistical analysis indicated that alternate routes were required to reduce the RTC hazard on Shara-e-Faisal. Research limitations/implications – The paper is a small, but an original, contribution to identify a potential hazard which is faced by the community in the city. This is the first attempt (to the best of authors’ knowledge) to address the issue of RTCs in Karachi from an engineering view point. Practical implications – The suggested model can be employed by the authorities as a guideline to mitigate the hazard of road crashes in the country. Originality/value – The paper provides valuable information on the road traffic incidents, their pattern and contributing factors in one of the largest metropolis of Pakistan. The suggested model can become helpful in reducing RTCs in Pakistan.


2014 ◽  
Vol 505-506 ◽  
pp. 1148-1152
Author(s):  
Jian Qun Wang ◽  
Xiao Qing Xue ◽  
Ning Cao

The road traffic accidents caused huge economic losses and casualties, so it had been focused by the researchers. Lane changing characteristic is the most relevant characteristic with safety. The intent of lane changing was discussed. Firstly, the factors affecting the intent were analyzed, the speed satisfaction value and the space satisfaction value were proposed; then the data from the University of California, Berkeley was extracted and the number of vehicles changed lane more often and the vehicle ID were obtained; the BP neural network classification model was established, it was trained and testified by actual data. The results shown the method could predict the intent accurately.


2021 ◽  
Vol 116 (1) ◽  
pp. 299-304
Author(s):  
Assel Aliyadynovna Sailau

The number of vehicles on the roads of Almaty, Kazakhstan is growing from year to year. This brings about an increasing intensity and density of traffic flows in the streets which leads to congestion, decreasing speed of the traffic flow, increasing environmental pollution caused by car emissions, and which can potentially lead to the road traffic accidents (RTA), including fatalities. While the number of injuries grows up mainly due to drivers’ non-compliance with the speed limit, the environmental pollution is caused by longer traffic jams. Therefore, to reduce the level of road traffic injuries and emissions into the environment it is necessary to ensure the uniform movement of traffic flows in cities. Currently, one of the effective ways to do it is the use of transport telematics systems, in particular, control systems for road signs, road boards and traffic lights. The paper presents an analysis of existing systems and methods of traffic light regulation. The  analyses of the systems and methods are based on the use of homogeneous data, that is the data on standard parameters of traffic flows. The need in collecting and analyzing additional semi-structured data on the factors that have a significant impact on the traffic flows parameters in cities is shown as well. The work is dedicated to solving the problem of analysis and forecast of traffic flows in the city of Almaty, Kazakhstan. GPS data on the location of individual vehicles is used as the initial data for solving this problem. By projecting the obtained information onto the graph of the city's transport network, as well as using additional filtering, it is possible to obtain an estimate of individual parameters of traffic flows. These parameters are used for short-term forecast of the changes in the city's transport network.


2021 ◽  
Vol 5 (12(81)) ◽  
pp. 26-32
Author(s):  
V. Volkov ◽  
E. Nabatnikova ◽  
E. Lebedev

The groups of participants of the pedestrian and automobile flows, whose actions cause the greatest danger to the occurrence of conflict situations in the zone of unregulated transition, are identified. The factors determining the likelihood of a traffic accident at an unregulated transition are systematized, for which probability estimates of the occurrence of road traffic accidents are calculated. As an estimated parameter, the hazard coefficient of a conflict point of an unregulated transition is proposed, which is determined by the ratio of the probability of a traffic accident in the real-time hourly interval to the average annual probability of a traffic accident reduced to the hourly interval. The dependences of the hazard ratio of an unregulated transition are established on the most significant factors: the speed mode of transport in the area before the transition and the state of the road surface.


2018 ◽  
Vol 40 ◽  
pp. 01004 ◽  
Author(s):  
A. Bukova-Zideluna ◽  
A. Villerusa ◽  
A. Lama

Latvian national road accident statistics shows that for the vulnerable road users’ situation is critical, since pedestrians are involved in more than a quarter of road traffic accidents. This paper gives an analysis on pedestrians involved in road traffic accidents based on the road safety accident database in Latvia for the years 2010–2014. The total number of cases does not change significantly, however there has been an increase in pedestrian fatality rates over the period. From the total number of traffic accidents with pedestrians involved 92.4% had injuries, 6.8% were lethal cases and others didn't suffer from injuries. Out of 342 fatalities 37.7% occurred during the winter period, 56.1% in adverse weather (overcast, fog, rain or snow), 69.9% during twilight or darkness and 26.9% on weekends. Out of all accidents 55.3% occurred in the capital city Riga, but fatality rate was higher on main state roads. 8.1% of the total number of pedestrians involved in road traffic accidents was found to have alcohol in their blood right after the road traffic accident. Fatality rate was higher for those with exceeded BAC. Pedestrian injury risk analysis was associated with demographical and traffic-related factors, urbanization, visibility and seasonal patterns.


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