Journal articles on the topic 'Road traffic collisions'
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Cabrera-Arnau, Carmen, and Steven R. Bishop. "Urban population size and road traffic collisions in Europe." PLOS ONE 16, no. 8 (August 27, 2021): e0256485. http://dx.doi.org/10.1371/journal.pone.0256485.
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Millions of road traffic collisions take place every year, leading to significant knock-on effects. Many of these traffic collisions take place in urban areas, where traffic levels can be elevated. Yet, little is known about the extent to which urban population size impacts road traffic collision rates. Here, we use urban scaling models to analyse geographic and road traffic collision data from over 300 European urban areas in order to study this issue. Our results show that there is no significant change in the number of road traffic collisions per person for urban areas of different sizes. However, we find individual urban locations with traffic collision rates which are remarkably high. These findings have the potential to inform policies for the allocation of resources to prevent road traffic collisions across the different cities.
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Tian, Zhun. "Investigating Impact of Speed on Traffic Safety using Collision Prediction Model." Advanced Materials Research 779-780 (September 2013): 482–85. http://dx.doi.org/10.4028/www.scientific.net/amr.779-780.482.
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Motor vehicle speed is a risk factor contributing to many road accidents which result in significant social and economic costs. Although a review of previous research shows that the literature is extensive on the impact of speed on traffic safety, the majority of previous researches mainly focused on rural roads while rarely on urban roads. It is crucial that the relationship between speed and road collisions should be investigated in urban areas because of the fact that a high ratio of collisions is occurred on urban roads. The objective of this study is to examine the influence of motor vehicle speed on road collisions on urban road sections. This objective is achieved by developing collision prediction models which quantitatively correlate collision frequency to speed characteristics. It is found that both mean speed and speed standard deviation are positively related to collision frequency. Both of them are risk factors in traffic safety.
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Babaoglu, Liza, and Ceni Babaoglu. "Prediction of Fatalities in Vehicle Collisions in Canada." Promet - Traffic&Transportation 33, no. 5 (October 8, 2021): 661–69. http://dx.doi.org/10.7307/ptt.v33i5.3782.
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Traffic collisions affect millions around the world and are the leading cause of death for children and young adults. Thus, Canada’s road safety plan is to reduce collision injuries and fatalities with a vision of making the safest roads in the world. We aim to predict fatalities of collisions on Canadian roads, and to discover causation of fatalities through exploratory data analysis and machine learning techniques. We analyse the vehicle collisions from Canada’s National Collision Database (1999–2017.) Through data mining methodologies, we investigate association rules and key contributing factors that lead to fatalities. Then, we propose two supervised learning classification models, Lasso Regression and XGBoost, to predict fatalities. Our analysis shows the deadliness of head-on collisions, especially in non-intersection areas with lacking traffic control systems. We also reveal that most collision fatalities occur in non-extreme weather and road conditions. Our prediction models show that the best classifier of fatalities is XGBoost with 83% accuracy. Its most important features are “collision configuration” and “used safety devices” elements, outnumbering attributes such as vehicle year, collision time, age, or sex of the individual. Our exploratory and predictive analysis reveal the importance of road design and traffic safety education.
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Wang, Ningcheng, Yufan Liu, Jinzi Wang, Xingjian Qian, Xizhi Zhao, Jianping Wu, Bin Wu, Shenjun Yao, and Lei Fang. "Investigating the Potential of Using POI and Nighttime Light Data to Map Urban Road Safety at the Micro-Level: A Case in Shanghai, China." Sustainability 11, no. 17 (August 30, 2019): 4739. http://dx.doi.org/10.3390/su11174739.
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The way in which the occurrence of urban traffic collisions can be conveniently and precisely predicted plays an important role in traffic safety management, which can help ensure urban sustainability. Point of interest (POI) and nighttime light (NTL) data have always been used for characterizing human activities and built environments. By using a district of Shanghai as the study area, this research employed the two types of urban sensing data to map vehicle–pedestrian and vehicle–vehicle collision risks at the micro-level by road type with random forest regression (RFR) models. First, the Network Kernel Density Estimation (NKDE) algorithm was used to generate the traffic collision density surface. Next, by establishing a set of RFR models, the observed density surface was modeled with POI and NTL variables, based on different road types and periods of the day. Finally, the accuracy of the models and the predicted outcomes were analyzed. The results show that the two datasets have great potential for mapping vehicle–pedestrian and vehicle–vehicle collision risks, but they should be carefully utilized for different types of roads and collision types. First, POI and NTL data are not applicable to the modeling of traffic collisions that happen on expressways. Second, the two types of sensing data are quite suitable for estimating the occurrence of traffic collisions on arterial and secondary trunk roads. Third, while the two datasets are capable of predicting vehicle–pedestrian collision risks on branch roads, their ability to predict vehicle safety on branch roads is limited.
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Liu, Yan, Siqin Wang, Xuanming Fu, and Bin Xie. "A network-constrained spatial identification of high-risk roads for hit-parked-vehicle collisions in Brisbane, Australia." Environment and Planning A: Economy and Space 51, no. 2 (October 30, 2018): 279–82. http://dx.doi.org/10.1177/0308518x18810531.
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The severe loss of human life and material damage caused by traffic accidents is a growing concern faced by many countries across the world. In Australia, despite a decline in the total number of traffic collisions since 2001, the number of hit-parked-vehicle (HPV) collisions as a special type of road accident has increased over time. Utilizing the road collisions and roadway network data in Brisbane, Australia over a 10-year period from 2001 to 2010, we generated graphics illustrating the spatial patterning of high-risk road segments for HPV crashes identified using the local indicator of network-constrained clusters (LINCS) approach. These spatial patterns vary by days of the week and times of the day. Roads with high risk for HPV collision tend to occur in high-density road networks and cluster around road intersections. The methodology applied in this work is applicable to other network-constrained point-pattern analysis.
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Eid, Hani O., and Fikri M. Abu-Zidan. "Distraction-related road traffic collisions." African Health Sciences 17, no. 2 (July 17, 2017): 491. http://dx.doi.org/10.4314/ahs.v17i2.24.
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Raynham, P., J. Unwin, M. Khazova, and S. Tolia. "The role of lighting in road traffic collisions." Lighting Research & Technology 52, no. 4 (August 26, 2019): 485–94. http://dx.doi.org/10.1177/1477153519870857.
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The paper reports a study that examines how to determine if a road traffic collision took place in daylight or in the dark. An innovative method was developed, based on solar altitude, to establish cut-off points of daylight and darkness determined from a study of daylight availability in England, Scotland and Wales. This approach provides a rigorous method to differentiate daytime and night-time collisions. The criteria were used in a study of the collisions reported in the STATS19 data set for the weeks either side of the clock changes that are necessary between Greenwich Mean Time and British Summer Time. By comparing periods with the same clock time either side of the time change, using the aforementioned method, it was possible to isolate collisions within the same time period that during one week occurred in darkness and in the other week in daylight. The initial finding was that there are 19.3% more collisions in the dark periods and there is an even greater increase (31.7%) in pedestrian injuries.
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Darus, Nur Shaeza, Muhamad Nazri Borhan, Siti Zaharah Ishak, Rozmi Ismail, Siti Fatin Mohd. Razali, Nor Aznirahani Mhd Yunin, and Rizati Hamidun. "The Effect of Physical Environment Risk Factors on Vehicle Collisions Severity Involving Child-Pedestrians in Malaysia." SAGE Open 12, no. 1 (January 2022): 215824402110684. http://dx.doi.org/10.1177/21582440211068494.
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This study is aimed at investigating the association between child-pedestrian severity levels of collisions and physical environmental variables. The outcome of this study could be applied to road safety intervention for improving engineering modifications related to children pedestrians. The retrospective analysis was carried out using 6-year data from Royal Malaysia Police records from the years 2009 to 2014. Multinomial logit modeling (MNL) was applied. The results demonstrated that the injury severity of the collisions is related to road geometry, road surface material, road surface condition, traffic system, road marking, traffic control type, lighting condition, speed limit, time of collision, type of location, and land use characteristics. Specifically, fatal injury collisions are significantly increased by t/y intersection; concrete and earth-road surfaces; two-way traffic and dual carriageways; posted speed limits of 70 to 90 km/h; time of collision: 0 to 0659 hours (early morning) and 0700 to 0959 hours (morning); lighting conditions, including dark without street light, and dark with street light; and control type involving police. Meanwhile, cross intersections’ posted speed limits of 80 km/h to 90 km/h and the time of collision from 0 to 0659 hours (early morning) and 1900 to 2459 hours (night), significantly increased serious injury collisions. Notably, the findings revealed the importance of more in-depth studies on physical environmental features that relate to child-pedestrians’ severity level of collisions. This is essential for improvements to physical environmental designs by policymakers. Thus, policymakers and stakeholders can utilize the findings to further improve the physical environment through structure and design.
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Xu, Zhi Qiang. "Research of Mechanics Based on Accident Collision." Advanced Materials Research 1021 (August 2014): 214–17. http://dx.doi.org/10.4028/www.scientific.net/amr.1021.214.
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With the rapid development of the economy, the automotive industry and road transport have also been rapidly developed. Road traffic accidents occur frequently, which not only brings a lot of inconvenience to road traffic management but also threatens people's lives and property. In many road accidents, vehicle collisions are the most serious and dangerous also the largest. So having a comprehensive, systematic study of the car's collision is becoming the world's most pressing subject. The whole process of the collision of moving vehicle is inseparable from the role of the force. So in order to better analyze vehicle collisions and reproduce this process, a lot of mechanical knowledge should be required. This paper studies the vehicle accident reconstruction mechanical problems, laying the foundation of further research.
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Kučas, Andrius, and Linas Balčiauskas. "Impact of Road Fencing on Ungulate–Vehicle Collisions and Hotspot Patterns." Land 10, no. 4 (March 25, 2021): 338. http://dx.doi.org/10.3390/land10040338.
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The number of road traffic accidents decreased in Lithuania from 2002 to 2017, while the ungulate–vehicle collision (UVC) number increased and accounted for approximately 69% of all wildlife–vehicle collisions (WVC) in the country. Understanding the relationship between UVCs, traffic intensity, and implemented mitigation measures is important for the assessment of UVC mitigation measure efficiency. We assessed the effect of annual average daily traffic (AADT) and wildlife fencing on UVCs using regression analysis of changes in annual UVCs and UVC hotspots on different categories of roads. At the highest rates, annual UVC numbers and UVC hotspots increased on lower category (national and regional) roads, forming a denser network. Lower rates of UVC increase occurred on higher category (main) roads, forming sparser road networks and characterized by the highest AADT. Before 2011, both UVC occurrence and fenced road sections were most common on higher-category roads. However, as of 2011, the majority of UVCs occurred on lower-category roads where AADT and fencing had no impact on UVCs. We conclude that wildlife fencing on roads characterized by higher speed and traffic intensity may decrease UVC numbers and at the same time shifting UVC occurrence towards roads characterized by lower speed and traffic intensity. Wildlife fencing re-allocates wildlife movement pathways toward roads with insufficient or no mitigation measures.
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Lovegrove, Gordon R., and Tarek Sayed. "Macro-level collision prediction models for evaluating neighbourhood traffic safety." Canadian Journal of Civil Engineering 33, no. 5 (May 1, 2006): 609–21. http://dx.doi.org/10.1139/l06-013.
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This study describes the development of macro-level (i.e., neighbourhood or traffic zone level) collision prediction models using data from 577 neighbourhoods across the Greater Vancouver Regional District. The objective is to provide a safety planning decision-support tool that facilitates a proactive approach to community planning which addresses road safety before problems emerge. The models are developed using the generalized linear regression modelling (GLM) technique assuming a negative binomial error structure. The resulting models relate traffic collisions to neighbourhood characteristics such as traffic volume, demographics, network shape, and transportation demand management. Several models are presented for total or severe collisions in rural or urban zones using measured and (or) modelled data. It is hoped that quantifying a predictive traffic safety – neighbourhood planning relationship will facilitate improved decisions by community planners and engineers and, ultimately, facilitate improved neighbourhood traffic safety for residents and other road users.Key words: neighbourhood safety, macro-level collision prediction models, road safety, safety planning, transportation demand management, sociodemographic, generalized linear regression modelling.
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Olmez, Sedar, Liam Douglas-Mann, Ed Manley, Keiran Suchak, Alison Heppenstall, Dan Birks, and Annabel Whipp. "Exploring the Impact of Driver Adherence to Speed Limits and the Interdependence of Roadside Collisions in an Urban Environment: An Agent-Based Modelling Approach." Applied Sciences 11, no. 12 (June 8, 2021): 5336. http://dx.doi.org/10.3390/app11125336.
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Roadside collisions are a significant problem faced by all countries. Urbanisation has led to an increase in traffic congestion and roadside vehicle collisions. According to the UK Government’s Department for Transport, most vehicle collisions occur on urban roads, with empirical evidence showing drivers are more likely to break local and fixed speed limits in urban environments. Analysis conducted by the Department for Transport found that the UK’s accident prevention measure’s cost is estimated to be £33bn per year. Therefore, there is a strong motivation to investigate the causes of roadside collisions in urban environments to better prepare traffic management, support local council policies, and ultimately reduce collision rates. This study utilises agent-based modelling as a tool to plan, experiment and investigate the relationship between speeding and vehicle density with collisions. The study found that higher traffic density results in more vehicles travelling at a slower speed, regardless of the degree to which drivers comply with speed restrictions. Secondly, collisions increase linearly as speed compliance is reduced for all densities. Collisions are lowest when all vehicles comply with speed limits for all densities. Lastly, higher global traffic densities result in higher local traffic densities near-collision sites across all adherence levels, increasing the likelihood of congestion around these sites. This work, when extended to real-world applications using empirical data, can support effective road safety policies.
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Find’o, S., M. Skuban, M. Kajba, J. Chalmers, and M. Kalaš. "Identifying attributes associated with brown bear (Ursus arctos) road-crossing and roadkill sites." Canadian Journal of Zoology 97, no. 2 (February 2019): 156–64. http://dx.doi.org/10.1139/cjz-2018-0088.
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Habitat fragmentation caused by transportation infrastructure is an issue of growing concern worldwide. We show how secondary roads may affect landscape permeability for brown bears (Ursus arctos Linnaeus, 1758). We focused on identifying environmental variables that govern the selection of road-crossing zones by bears (crossing model). We also investigated whether variables that characterize road-crossing zones differ from those that are typical for bear–vehicle collision sites (collision model). The study area was located in north-central Slovakia. To identify road-crossing sites, we used the GPS fixes of 27 bears and identified 35 bear–vehicle collision sites from a different data set. We used mixed-effects logistic regression to model resource selection at road-crossing sites and to compare bear-crossing sites with bear-kill sites. The crossing model showed that the traffic volume with distance to forest and grassland were the most influential factors in bear selection of road-crossing sites. Results of the collision model indicated that successful road crossings by bears were located at different road sections from vehicle collisions, which differed by a traffic volume of 5000 vehicles/24 h. The outcomes of this study can facilitate improved mitigation measures on secondary roads.
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Cunningham, Calum X., Glen E. Liston, Adele K. Reinking, Natalie T. Boelman, Todd J. Brinkman, Kyle Joly, Mark Hebblewhite, et al. "Human and animal movements combine with snow to increase moose-vehicle collisions in winter." Environmental Research Letters 17, no. 12 (December 1, 2022): 125007. http://dx.doi.org/10.1088/1748-9326/aca8bf.
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Abstract Wildlife-vehicle collisions imperil humans, wildlife, and property. Collisions with moose (Alces alces) are especially consequential and there are indications they may increase during severe winters. We tested hypotheses regarding the influence of moose movements and vehicular traffic patterns on collision risk. We first modeled daily snow depth and accumulation across 5.6 million km2 of the North American Arctic-Boreal region. Next, we analyzed the movements and road use of 113 GPS-collared moose in response to snow depth. Finally, we examined the influence of these snow properties on vehicular traffic and 7680 moose-vehicle collisions. As winter progressed and the snowpack deepened in each study area, GPS-collared moose migrated to lower elevations, leading them into areas with shallower snow but higher road densities. This elevational migration corresponded with a higher probability of road-use by moose (by up to ten-fold) in winter than in summer. Corresponding to these patterns, moose-vehicle collisions were 2.4–5.7 times more frequent from December through February (compared to early summer). Collision risk was highest when and where snow depth was less than 120 cm, indicating that migration into areas with shallower snow increased collision risk in those areas. Most (82%) moose-vehicle collisions occurred after dark. This pattern was strongest during winter, when nighttime traffic volumes were eight times higher than summer due to longer nights. Overall, our findings suggest that concurrent seasonal changes in human and wildlife behavior increase the frequency of moose-vehicle collisions during winter. Snow depth influences collisions primarily through its impacts on moose movement, while strong seasonal changes in daylight hours cause an increase in nighttime traffic that further contributes to risk. This information may help predict times and places where risk of moose-vehicle collisions are highest and to develop seasonally dynamic mitigation strategies.
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Butsenko, Elena. "How Data Mining Can Improve Road Safety in Cities." Social Sciences 11, no. 3 (March 16, 2022): 130. http://dx.doi.org/10.3390/socsci11030130.
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Traffic collisions pose a serious problem for cities due to the annually increasing number of vehicles. Information about incidents that occur on roads is important for the corresponding monitoring bodies, authorities, and emergency services. To ensure traffic safety, the data have to be visible, clean, and transparently displayed. This research was, therefore, aimed at developing a methodology for monitoring motor vehicle collision data and applying visualization techniques to evidence from New York City. The method showed that the largest number of motor vehicle traffic crashes occurred in Lower Manhattan due to its high population and traffic density. With these data, the road agencies of the city can put potentially dangerous road sections under control and make them safer for both drivers and pedestrians. Further development of the system may be associated with data analytics and visualization, resulting in new layers of heatmaps that not only provide details on car collision hotspots, which serve as the main target indicator for traffic safety authorities, but also break them down into social facilities, such as schools. This feature will enable assessment of how safe it is around a school and the evaluation of the impact of an underpass or a traffic enforcement camera on the number of collisions. The motor vehicle traffic crash (MVTC) monitoring system will help in comparing city districts and regions in terms of safety, seeing trends, realizing what exactly is happening at interchanges, and understanding the reasons behind. The methodology, in addition, can be supplemented with an analysis of risk factors for MVTCs, the efficiency of adopted measures and road renovations that are carried out, and many other functions.
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Keisham, Supriya, Pabitramala Nandeibam, Kh Pradipkumar Singh, George Vanlalchhuanga, and H. Nabachandra. "Retrospective study on fatal road traffic accident in Aizawl, Mizoram during 2014-2018." IP International Journal of Forensic Medicine and Toxicological Sciences 6, no. 3 (September 15, 2021): 91–94. http://dx.doi.org/10.18231/j.ijfmts.2021.020.
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A traffic collision, also called a motor vehicle collision, car accident, occurs when a vehicle collides with another vehicle, pedestrian, animal, road debris, or any stationary obstruction, such as a tree, pole or building. Traffic collisions often result in injury, disability, death and damage to property as well as financial cost to both the society & individuals involved.
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Volchatova, I. V. "ACCIDENT RATE AND VICTIMS OF ROAD TRAFFIC IN A BIG CITY." World of Transport and Transportation 15, no. 4 (August 28, 2017): 202–13. http://dx.doi.org/10.30932/1992-3252-2017-15-4-18.
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For the English abstract and full text of the article please see the attached PDF-File (English version follows Russian version).ABSTRACT Based on the statistics of road accidents, an analysis of accident and injury rates on the roads of Irkutsk was carried out. It is shown that, for the most part, the causes of road accidents are violation of traffic rules by drivers and pedestrians, unsatisfactory road conditions. It was revealed that the greatest number of accidents occurs in the summer-autumn period. Most often, vehicle collisions and pedestrian collisions are recorded. About 40 % of road accidents with victims are committed in the foci of accident rate, the distribution of which directly depends on density of settlement of the territory and the functional specifics of the city’s administrative units. Keywords: motor transport, road traffic accident, accident rate on roads, foci of accident, severity of accident consequences, road safety.
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Kang, Liuwang, Ankur Sarker, and Haiying Shen. "Velocity Optimization of Pure Electric Vehicles with Traffic Dynamics and Driving Safety Considerations." ACM Transactions on Internet of Things 2, no. 1 (February 2021): 1–24. http://dx.doi.org/10.1145/3433678.
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As Electric Vehicles (EVs) become increasingly popular, their battery-related problems (e.g., short driving range and heavy battery weight) must be resolved as soon as possible. Velocity optimization of EVs to minimize energy consumption in driving is an effective alternative to handle these problems. However, previous velocity optimization methods assume that vehicles will pass through traffic lights immediately at green traffic signals. Actually, a vehicle may still experience a delay to pass a green traffic light due to a vehicle waiting queue in front of the traffic light. Also, as velocity optimization is for individual vehicles, previous methods cannot avoid rear-end collisions. That is, a vehicle following its optimal velocity profile may experience rear-end collisions with its frontal vehicle on the road. In this article, for the first time, we propose a velocity optimization system that enables EVs to immediately pass green traffic lights without delay and to avoid rear-end collisions to ensure driving safety when EVs follow optimal velocity profiles on the road. We collected real driving data on road sections of US-25 highway (with two driving lanes in each direction and relatively low traffic volume) to conduct extensive trace-driven simulation studies. Results show that our velocity optimization system reduces energy consumption by up to 17.5% compared with real driving patterns without increasing trip time. Also, it helps EVs to avoid possible collisions compared with existing collision avoidance methods.
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Wang, Michael I. C., Charles H. P. Wen, and H. Jonathan Chao. "Roadrunner+: An Autonomous Intersection Management Cooperating with Connected Autonomous Vehicles and Pedestrians with Spillback Considered." ACM Transactions on Cyber-Physical Systems 6, no. 1 (January 31, 2022): 1–29. http://dx.doi.org/10.1145/3488246.
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The recent emergence of Connected Autonomous Vehicles (CAVs) enables the Autonomous Intersection Management (AIM) system, replacing traffic signals and human driving operations for improved safety and road efficiency. When CAVs approach an intersection, AIM schedules their intersection usage in a collision-free manner while minimizing their waiting times. In practice, however, there are pedestrian road-crossing requests and spillback problems, a blockage caused by the congestion of the downstream intersection when the traffic load exceeds the road capacity. As a result, collisions occur when CAVs ignore pedestrians or are forced to the congested road. In this article, we present a cooperative AIM system, named Roadrunner+ , which simultaneously considers CAVs, pedestrians, and upstream/downstream intersections for spillback handling, collision avoidance, and efficient CAV controls. The performance of Roadrunner+ is evaluated with the SUMO microscopic simulator. Our experimental results show that Roadrunner+ has 15.16% higher throughput than other AIM systems and 102.53% higher throughput than traditional traffic signals. Roadrunner+ also reduces 75.62% traveling delay compared to other AIM systems. Moreover, the results show that CAVs in Roadrunner+ save up to 7.64% in fuel consumption, and all the collisions caused by spillback are prevented in Roadrunner+.
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Saayman, R. "Die fisika van motorbotsings en padverkeersveiligheid." Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 10, no. 3 (July 8, 1991): 112–36. http://dx.doi.org/10.4102/satnt.v10i3.500.
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A survey is given of the interdependent physical variables and principles relevant to the motion of a road vehicle in a traffic situation and its application to analyse and prevent actual collisions. As introduction recent RSA collision statistics and research results on contributing factors and types of collisions which occur, are presented. Then speed as cause is investigated with a discussion of the relative velocity between vehicles; stopping ability and safe following distances; the decision to stop or not at a changing traffic light; as well as estimations of the speed before collisions from wheel skidding marks and projectile flips and vaults. Thirdly vehicle stability is discussed with applications of weight displacement during sudden accelerations; explanations for skidding out of and turning over on a road bend; as well as load displacement.
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Metar, Manas. "Software Design for Adaptive Laser Headlights." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (November 30, 2021): 581–88. http://dx.doi.org/10.22214/ijraset.2021.38847.
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Abstract: The road traffic collisions and injuries, is still a major concern in automotive field. A disproportionate number of fatal accidents happen at nighttime. The major part of the collision is contributed by the human factors. Yet the technology in automobile is continuously assisting drivers while driving. Driving in the dark is not always easy as roads aren’t always illuminated, in such cases a powerful headlight is needed to illuminate most of the road. But such headlights cause glare to the oncoming traffic and again the chances of collision increase, with risking lives of passengers. Therefore, a need of smart headlamps which can illuminate the road far ahead without glaring the oncoming traffic is generated. This research aims to build a Laser based adaptive headlight system which can fulfil the need. The headlight design is proposed using Tinkercad software in which Arduino circuit has been used and software design is presented. The system works well with responding to the steering angle and controls the intensity of light preventing oncoming traffic from getting glared. Keywords: Adaptive headlight system, laser headlights, Arduino, Arduino software design, design of headlight system, cornering lights, effects of laser headlights, Tinkercad
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Giummarra, Melita J., Ben Beck, and Belinda J. Gabbe. "Classification of road traffic injury collision characteristics using text mining analysis: Implications for road injury prevention." PLOS ONE 16, no. 1 (January 27, 2021): e0245636. http://dx.doi.org/10.1371/journal.pone.0245636.
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Road traffic injuries are a leading cause of morbidity and mortality globally. Understanding circumstances leading to road traffic injury is crucial to improve road safety, and implement countermeasures to reduce the incidence and severity of road trauma. We aimed to characterise crash characteristics of road traffic collisions in Victoria, Australia, and to examine the relationship between crash characteristics and fault attribution. Data were extracted from the Victorian State Trauma Registry for motor vehicle drivers, motorcyclists, pedal cyclists and pedestrians with a no-fault compensation claim, aged > = 16 years and injured 2010–2016. People with intentional injury, serious head injury, no compensation claim/missing injury event description or who died < = 12-months post-injury were excluded, resulting in a sample of 2,486. Text mining of the injury event using QDA Miner and Wordstat was used to classify crash circumstances for each road user group. Crashes in which no other was at fault included circumstances involving lost control or avoiding a hazard, mechanical failure or medical conditions. Collisions in which another was predominantly at fault occurred at intersections with another vehicle entering from an adjacent direction, and head-on collisions. Crashes with higher prevalence of unknown fault included multi-vehicle collisions, pedal cyclists injured in rear-end collisions, and pedestrians hit while crossing the road or navigating slow traffic areas. We discuss several methods to promote road safety and to reduce the incidence and severity of road traffic injuries. Our recommendations take into consideration the incidence and impact of road trauma for different types of road users, and include engineering and infrastructure controls through to interventions targeting or accommodating human behaviour.
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Brysiewicz, P. "Pedestrian road traffic collisions in South Africa." Accident and Emergency Nursing 9, no. 3 (July 2001): 194–97. http://dx.doi.org/10.1054/aaen.2001.0261.
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Graham, Daniel J., Cian Naik, Emma J. McCoy, and Haojie Li. "Do speed cameras reduce road traffic collisions?" PLOS ONE 14, no. 9 (September 16, 2019): e0221267. http://dx.doi.org/10.1371/journal.pone.0221267.
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Mohammed, Ali Ahmed, Kamarudin Ambak, Ahmed Mancy Mosa, and Deprizon Syamsunur. "A Review of the Traffic Accidents and Related Practices Worldwide." Open Transportation Journal 13, no. 1 (June 30, 2019): 65–83. http://dx.doi.org/10.2174/1874447801913010065.
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A traffic accident, a traffic collision or crash occurs when a vehicle collides with another vehicle, pedestrian, animal, road barriers, or any stationary obstruction such as a tree or a utility pole. Traffic collisions may result in injury, death, vehicle damage and possession damage. Motor vehicle collisions cause death and disability as well as a financial burden. Traffic accidents cause many losses especially of human life, property damages, and loss of resources. Indeed, even in strife influenced countries such as Afghanistan, Libya, Pakistan, and Yemen, road traffic remains the most common cause of fatal injuries, causing between two and eight times more fatalities than war and lawful mediation. The World Health Organization (WHO) 2013 assessed the traffic casualty rate in the Eastern Mediterranean Region (EMR) to be the second most elevated rate universally after the African Region and extending a few other countries in the region. The aim of this paper was to enrich the global highway safety knowledge by revealing the catastrophic impact of traffic accidents on the economy of the societies and the safety of the common worldwide.
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Popescu, Bianca, and Tarek Sayed. "Developing Macrolevel Collision Prediction Models to Evaluate Bicycle Safety in Vancouver, British Columbia, Canada." Transportation Research Record: Journal of the Transportation Research Board 2659, no. 1 (January 2017): 25–32. http://dx.doi.org/10.3141/2659-03.
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To encourage greener cities while reducing the impacts of the transportation system—such as impacts on climate change, traffic congestion, and road safety—governments have been investing in sustainable modes of transportation, such as cycling. A safe and comfortable cycling environment is critical to encourage bicycle trips because cyclists are usually subject to greater safety risks. Engineering approaches to road safety management have traditionally addressed road safety by reacting to existing collision records. For bicycle collisions, which are rare events, a proactive approach is more appropriate. This study described the use of bicycle-related macrolevel (i.e., neighborhood or zonal-level) collision prediction models as empirical tools in road safety diagnosis and planning. These models incorporated an actual bicycle exposure indicator (the number of bicycle kilometers traveled). The macrolevel bicycle–vehicle collisions models were applied at the zonal level to a case study of Vancouver, British Columbia, Canada. Collision-prone zones in Vancouver were identified, and the highest-ranked zones were diagnosed to identify bicycle safety issues and to recommend potential safety countermeasures. The findings from this study suggest that the safety issues may be a result of high density and commercial land use type, coupled with a high traffic volume, particularly on arterial routes, and high bicycle volumes on routes with mixed vehicle and bicycle traffic. The case study demonstrated the use of the models to enhance bicycle safety proactively.
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Klöcker, Ulrike, David B. Croft, and Daniel Ramp. "Frequency and causes of kangaroo - vehicle collisions on an Australian outback highway." Wildlife Research 33, no. 1 (2006): 5. http://dx.doi.org/10.1071/wr04066.
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Kangaroo–vehicle collisions are frequent on Australian highways. Despite high economic costs, detrimental effects on animal welfare, and potential impacts on population viability, little research has been done to investigate the impact of road mortality on kangaroo populations, where and why accidents occur, and how the collisions can be mitigated. We therefore collected data on species (Macropus rufus, M. giganteus, M. fuliginosus, M. robustus), sex and age of kangaroos killed on a 21.2-km bitumenised section of outback highway over 6 months in far western New South Wales, Australia. The spatial and temporal distribution of road-killed kangaroos was investigated in relation to the cover and quality of road-side vegetation, road characteristics, the density of kangaroos along the road, climatic variables and traffic volume. A total of 125 kangaroos were found killed on the road at a rate of 0.03 deaths km–1 day–1. Grey kangaroos of two species (M. giganteus, M. fuliginosus) were under-represented in the road-kill sample in comparison with their proportion in the source population estimated during the day. No bias towards either sex was found. The age structure of road-killed kangaroos was similar to age structures typical of source kangaroo populations. Road-kills mainly occurred in open plains country. In road sections with curves or stock races, road-kill frequencies were higher than expected. Greater cover and greenness of roadside vegetation at the verge probably attracted kangaroos to the road and variation in this vegetation affected the spatial distribution of road-kills. The temporal distribution of road-kills was positively correlated with the volume of night-time traffic. The probability of a kangaroo–vehicle collision increased exponentially with traffic volume. Results are discussed in relation to the potential for mitigation of kangaroo–vehicle collisions.
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Linn, Nyi Nyi, Kai Liu, and Qiang Gao. "A Contention-Free Cooperative MAC Protocol for Eliminating Heterogenous Collisions in Vehicular Ad Hoc Networks." Sensors 23, no. 2 (January 16, 2023): 1033. http://dx.doi.org/10.3390/s23021033.
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In vehicular ad hoc networks (VANETs), efficient data dissemination to a specified number of vehicles with minimum collisions and limited access delay is critical for accident prevention in road safety. However, packet collisions have a significant impact on access delay, and they may lead to unanticipated link failure when a range of diversified collisions are combined due to complex traffic conditions and rapid changes in network topology. In this paper, we propose a distributed contention-free cooperative medium access control (CFC-MAC) protocol to reduce heterogenous collisions and unintended access delay in stochastic traffic scenarios. Firstly, we develop a cooperative communication system model and cooperative forwarding mechanism to explore the optimum road path between the source and destination by identifying the potential cooperative vehicles. Secondly, we propose a vectorized trajectory estimation mechanism to suppress merging collisions by identifying the relative velocity of vehicles with different speeds in a specific time interval. Based on the case study, typical heterogeneous collisions and aggregated heterogeneous collisions at dissociated positions and associated positions are investigated. In both cases, we propose the corresponding collision-resolving mechanisms by methodically recapturing the colliding time slot or acquiring the available free time slots after identifying the access vehicles and comparing the received signal strengths. Performance analysis for collision probability and access delay is conducted. Finally, the simulation results show that the proposed protocol can achieve deterministic access delay and a minimal collision rate, substantially outperforming the existing solutions.
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Aiyewalehinmi, E. O. "Analysis of Road Traffic Crashes/Collisions In Ondo State Roads." IOSR Journal of Engineering 03, no. 08 (August 2013): 10–22. http://dx.doi.org/10.9790/3021-03841022.
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Davies, Christopher, Wendy Wright, Fiona Hogan, and Casey Visintin. "Predicting deer–vehicle collision risk across Victoria, Australia." Australian Mammalogy 42, no. 3 (2020): 293. http://dx.doi.org/10.1071/am19042.
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The risk of deer–vehicle collisions (DVCs) is increasing in south-east Australia as populations of introduced deer expand rapidly. There are no investigations of the spatial and temporal patterns of DVC or predictions of where such collisions are most likely to occur. Here, we use an analytical framework to model deer distribution and vehicle movements in order to predict DVC risk across the State of Victoria. We modelled the occurrence of deer using existing occurrence records and geographic climatic variables. We estimated patterns of vehicular movements from records of average annual daily traffic and speeds. Given the low number of DVCs reported in Victoria, we used a generalised linear regression model fitted to DVCs in California, USA. The fitted model coefficients suggested high collision risk on road segments with high predicted deer occurrence, moderate traffic volume and high traffic speed. We used the California deer model to predict collision risk on Victorian roads and validated the predictions with two independent datasets of DVC records from Victoria. The California deer model performed well when comparing predictions of collision risk to the independent DVC datasets and generated plausible DVC risk predictions across the State of Victoria.
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Yang, Bo, Yao Wu, Weihua Zhang, and Jie Bao. "Modeling Collision Probability on Freeway: Accounting for Different Types and Severities in Various LOS." Sustainability 12, no. 18 (September 9, 2020): 7386. http://dx.doi.org/10.3390/su12187386.
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In this study, collision-related data were collected on the I-880 freeway of California in the United States from 2006 to 2011. Our objective was to study the collision probability of different collision types and severities in different traffic states. The traffic states were divided by the traditional level of service (LOS) method. Various Bayesian conditional logit models have been established to analyze the relationship between the collision probability of different collision patterns and LOSs. The results showed that LOS A had the best safety performance associated with all of the collision types and severities, LOS C had the worst safety performance associated with hit object collisions, LOS D had the worst safety performance associated with sideswipe collisions and rear end collisions, and LOS F had the worst safety performance associated with injury collisions. The five-stage Bayesian random parameter sequential logit model was established to quantify the effects of different variables on the collision probability of various collision types and severities. In addition to LOS, the visibility, road surface, weather, ramp, and number of lanes had significant effects on different collision types and severities.
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Shimada, Ryo, and Kazuhiko Kibayashi. "Changes in the number of traffic collisions during the various waves of COVID-19 infection in Japan." PLOS ONE 17, no. 12 (December 15, 2022): e0278941. http://dx.doi.org/10.1371/journal.pone.0278941.
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An analysis of the national traffic collision trends in Japan for the January 2018 to June 2022 period using existing statistical data indicates that the number of traffic incidents, injuries, and fatalities decreased over time. After the outbreak of COVID-19 in December 2019, traffic volume decreased. In this study, to explore how the COVID-19 pandemic correlates with traffic collisions, we used the Spearman rank correlation of non-parametric statistical test to compare the number of COVID-19 infections with the number of traffic collisions. The number of COVID-19 infections showed a significant inverse correlation with the number of traffic collisions nationwide, in some regions, and in some prefectures. When the number of COVID-19 infections increased, a State of Emergency or Semi-Emergency Spread Prevention Measures were repeatedly declared. We submit that these measures along with the restrictions on the population’s autonomy and movement to prevent the spread of infection, reduces the number of traffic incidents, injuries, and fatalities owing to a decrease in traffic volume. Therefore, these lessons learned from the COVID-19 pandemic advocate that regulation of vehicle traffic volume is an effective means of reducing the occurrence of traffic collisions. These results can be applied to future policy development to support road safety improvements during unique events.
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Kisilowski, Jerzy, and Jarosław Zalewski. "Chosen Problems of Road Accidents Analyses in Poland." Journal of Konbin 8, no. 1 (January 1, 2008): 125–34. http://dx.doi.org/10.2478/v10040-008-0107-6.
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Chosen Problems of Road Accidents Analyses in Poland This article offers classification of car collisions from the point of view of the most frequent accidents and crash tests. The most important problems are the consequences of incomplete control of a car. The article focuses on the safety of road traffic in Poland and presents an attempt to analyze the causes of most frequent collisions and their consequences. It gives statistical data and attempts to analyze the level of road traffic safety. Some important indicators are shown here to compare the situation in France and Poland, which enabled verification of some opinions about road traffic safety in Poland.
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Fitri, Etty Yusrika, and Suhadi Purwantara. "The Identification of Characteristic, Cause, and Disaster Management of Traffic Accident at the Sungailiat – Belinyu Road." International Journal of Multicultural and Multireligious Understanding 8, no. 10 (October 5, 2021): 204. http://dx.doi.org/10.18415/ijmmu.v8i10.3035.
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This study aims to identify the characteristic, cause, and disaster management of traffic accidents at the Sungailiat – Belinyu road. The research method used is descriptive quantitative. Data collection techniques is in the form of documentation and observation. The data collected then analyzed using data analysis techniques with classification methods. Based on the research done, the results obtained are the accidents that occur on Jalan Raya Sungailiat - Belinyu are the most common in Riau Silip District with a percentage of 59.8%. The accidents characteristics on Sungailiat - Belinyu road based on the time of the incident, mostly occurred during the afternoon to evening at 12.00 - 17.59 WIB and in the evening at 18.00 - 23.59 WIB. Based on the type of collision, the most common types of collisions are frontal collisions by 30% and collisions due to loss of control by 26.6%. Based on road users, road users who are most involved in accidents are motorcycles by 40%, cars by 23.3%, dump trucks by 10%, and the other vehicles in a small percentage. As for the factors causing the accident, it was found that the accident was caused by road users (73.33%), road factors (23.33%), and environmental factors (6.66%). The handling of accident management is arranged according to the causative factors that are done before, when it occurs, and after an accident occurs as an effort to reduce the risk of accidents on the Sungailiat – Belinyu road, Bangka Regency.
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Sroczyński, Andrzej, Adam Kurowski, Szymon Zaporowski, and Andrzej Czyżewski. "Examining Impact of Speed Recommendation Algorithm Operating in Autonomous Road Signs on Minimum Distance between Vehicles." Remote Sensing 14, no. 12 (June 10, 2022): 2803. http://dx.doi.org/10.3390/rs14122803.
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An approach to a new kind of recommendation system design that suggests safe speed on the road is presented. Real data obtained on roads were used for the simulations. As part of a project related to autonomous road sign development, a number of measurements were carried out on both local roads and expressways. A speed recommendation model was created based on gathered traffic data employing the traffic simulator. Depending on the traffic volume and atmospheric conditions prevailing on the road, as well as the surface conditions, the proposed system recommends the safe speed for passing vehicles by influencing the distance from the preceding vehicle to prevent collisions. The observed effect of the system application was an increase in the minimal distance between vehicles in most simulations.
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Ossei, Paul Poku Sampene, Eric Agyeman-Duah, William Gilbert Ayibor, Nicholas Niako, and Kwakye Foster Safo. "Latent Medical Conditions of Drivers Involved in Road Traffic Collisions in Ghana: Implication from Autopsy Findings." Clinical Pathology 14 (January 2021): 2632010X2110438. http://dx.doi.org/10.1177/2632010x211043871.
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Background: Unlike some neighboring countries like Nigeria, few studies on actual causes, impact and the prevention of road traffic collisions have been carried out in Ghana. There is the need for further research and this study sought to link injuries that caused the death of drivers involved in vehicular collisions to the latent possible contributing diseases and medical conditions in these drivers and how these conditions predispose them to the collisions. Methods: This is a retrospective study that used the forensic autopsy records of driver fatalities and various injuries and medical conditions of drivers involved in road traffic collisions. Information on all drivers was retrieved from archives at the Komfo Anokye Teaching Hospital’ Pathology Unit. Demographics and cause of death were used in selecting the cases, including all driver-related road traffic collisions from 2009 to 2014. Results: A total of 1842 road traffic collisions were recorded with 127 of them being driver related. There were 31 cases (24.4%) in 2014; the highest cases recorded for this study, with the least recorded in 2009 with only 12 cases (9.4%). There were 121 (95.3%) male drivers and 6 female drivers (4.7%). Most of the male drivers were between the ages of 30 and 39 with 39 cases, while that of females was between 40 and 49 years with 6 cases. There was no significant statistical correlation between age and sex ( P = .124). No statistical correlation also existed between sex and year ( P = .331). Pathologies of all body systems were established. Cardiovascular diseases were the most prevalent systemic medical condition seen in the drivers with 44.1%. Conclusion: The study established that the drivers had various latent medical conditions and all these could lead to possible incapacitation, affecting driver judgment, leading to collisions on the road. The National Road Safety Commission (NRSC) should request medical screening before issuing driver licenses.
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Hamid, Shaista, and Nitin Arora. "Research paper on improvement of road infrastructure to implement road safety at an intersection of military hospital road." IOP Conference Series: Earth and Environmental Science 889, no. 1 (November 1, 2021): 012027. http://dx.doi.org/10.1088/1755-1315/889/1/012027.
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Abstract Geometrical plan lacks on existing streets would prompt an expected mishap, for example, a mishap occurs at the sharp bends, layered asphalt conditions, and dangerous asphalt surface. Street auto collision has been expanding in the Southern Region of Tigray, of which this region was appeared to have disturbing rates. As indicated by the Southern Tigray Regional Police, the more rate of street car crashes were recorded in Garhi, Brimah pull and jekhani regions. This examination study zeroed in on the investigation of auto collisions identified with mathematical plan boundaries of the current black top street. While the information for the investigation covered course information, auto collision report from the police headquarters containing a few wounds, crashes, and destroyed the properties, just as meetings and poll studies to individuals who are straightforwardly engaged with street voyages, are thought of. The essential information has basically covered the math of the street which was estimated during the site study, street security review utilizing the agenda, meeting, and poll study. Then again, the auxiliary information gathered from the traffic the executive’s office in the area workplaces. On this, the outcomes introduced as line diagrams, pie outlines, figures for street car crash and sketch for the proposed improvement in the street plan issue. In view of the aftereffects of the investigation in the year 2015 to year 2019, it discovered that there were 1866 Road Traffic Accidents have been happening nearby the overview street areas. It uncovered that the essential driver of street car crashes in the investigation region exuded from the street plan components because of some mathematical lacks at the auto collision inclined regions uncovered that the essential driver of street car crashes in the examination region radiated from the street plan components because of some mathematical insufficiencies at the car crash inclined regions. Hence, this investigation reasoned that the recurrence of event of street auto collisions and the figure of setbacks is altogetherexpanding. This street mishap would endure if the concerned offices don’t satisfactorily address the disease.
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Rao, Dinesh. "Fatal road traffic collisions-An autopsy based study." IP International Journal of Forensic Medicine and Toxicological Sciences 6, no. 3 (September 15, 2021): 113–17. http://dx.doi.org/10.18231/j.ijfmts.2021.024.
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The Deaths due to Road Traffic Collision has become a Major Public Health issue, hence Understanding the Deaths and the Factors involved is important to prevent Fatalities and at the same time Prevent Road Traffic Collision in General. The present Study is a Retrospective Study conducted during the period 2013 to November 2020. Road Traffic Accidents constituted 39.35%[n-1168] of the Cases. Males formed the Majority of the Victims contributing to 83.04% of the cases. Majority of the Victims were I the age group 31-40 years, consisting of 422 victims. The least Age Group affected were those below the age 10years and those individuals above the age 70years. Light Motor Vehicle were the Major Contributor to the Accidents, contributing to 46.40%[n-542] of the cases. Head and Neck was the Major region affected in 795 cases. The Maximum Fatality reported were due to Head or Craniocerebral Injuries in 87% of the cases. Abrasions were Present in all the Victims. Majority of the Deaths were due to Traumatic Shock reported in on the Spot Deaths or Brought Dead Victims in 35.45% [n-414] cases. The commonest Cause of Death reported after 07days of Treatment, were Septicemia, Lung infections, Peritonitis, Coma. Craniocerebral Injuries were the Main Contributors to Fatality in 87% of Accidents. Majority of Deaths were due to Traumatic Shocks due to Multiple injuries involved. Importance of Emergency Care is well understood in this study.
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Santos, Sara M., António Mira, Pedro A. Salgueiro, Pedro Costa, Denis Medinas, and Pedro Beja. "Avian trait-mediated vulnerability to road traffic collisions." Biological Conservation 200 (August 2016): 122–30. http://dx.doi.org/10.1016/j.biocon.2016.06.004.
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Clarke, David D., Patrick Ward, Craig Bartle, and Wendy Truman. "Work-related road traffic collisions in the UK." Accident Analysis & Prevention 41, no. 2 (March 2009): 345–51. http://dx.doi.org/10.1016/j.aap.2008.12.013.
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Chatzaraki, Vasiliki, Michael J. Thali, Garyfalia Ampanozi, and Wolf Schweitzer. "Fatal Road Traffic Vehicle Collisions With Pedestrian Victims." American Journal of Forensic Medicine and Pathology 39, no. 2 (June 2018): 130–40. http://dx.doi.org/10.1097/paf.0000000000000382.
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Sánchez-González, María Pilar, Ángel Tejada-Ponce, Josiane Bonnefoy, and Francisco Escribano-Sotos. "Regional conditions and road traffic collisions on rural roads in Chile." Journal of Transport & Health 20 (March 2021): 100996. http://dx.doi.org/10.1016/j.jth.2020.100996.
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Petin, V. V., and A. V. Keller. "Description and tests of a control system for automatic emergency braking of a car with an algorithm for predicting the adhesion of automobile tires to the road surface." Journal of Physics: Conference Series 2061, no. 1 (October 1, 2021): 012100. http://dx.doi.org/10.1088/1742-6596/2061/1/012100.
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Abstract Every year the number of cars in the world is steadily growing, which in turn leads to an increase in road accidents. Russia, as the largest country by area in the world, has a number of traffic-related features that are not typical for other regions, including changing road and climatic conditions. The sharp increase in the number of accidents in the first hours after precipitation is especially noticeable, that indicates the difficulty to adapt to the changing traffic situation for vehicle drivers. More than 60% of collisions, according to the traffic police databases for 2018-2019, occur due to incorrect predictions by drivers of the braking distance of their cars. As a rule, this can happen due to the inexperience of the driver, incorrect assessment of the current adhesion properties of the roadway, distraction to a mobile phone, the climate or multimedia system of the car, movement with insufficient visibility. Preventing collisions occurring in such scenarios is the main task of an intelligent driver assistance system such as the automatic emergency braking system. The main part of this system is an adequate assessment of dynamically changing road and climatic conditions and warning the driver of a possible collision hazard, as well as automatic action on the vehicle’s brake drive to prevent a collision. The article describes control algorithms for assessing and predicting dangerous situations.
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Singh, Sanjay K. "The Neglected Epidemic: Road Traffic Crashes in India." Metamorphosis: A Journal of Management Research 11, no. 2 (July 2012): 27–49. http://dx.doi.org/10.1177/0972622520120204.
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Deaths and injuries resulting from road traffic crashes are a major and growing public health problem in India. Every week nearly 2,500 people get killed and 9,000 get injured due to traffic accidents. Traffic accidents have now earned India a dubious distinction; with nearly 127,000 deaths annually, the country has overtaken China to top the world in road fatalities. While in many developed and developing countries including China, the situation is generally improving, India faces a worsening situation. Road traffic collisions on the nation's roads claim five times more lives now than they did three decades ago. Without increased efforts and new initiatives, the total number of road traffic deaths in India is likely to cross the mark of 250,000 by 2025. There is thus an urgent need to recognize the worsening situation in road deaths and injuries and to take appropriate action. Certain interventions such as enforcement of legislation to control vehicle speed and alcohol consumption, mandating the use of seat-belts and helmets, and safer design and use of roads and vehicles have huge potential to reduce the incidence and impact of road traffic crashes. The time has come for the central, state, and local governments to act now. Acting now will save thousands of lives.
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Tijani, Ahmed, Richard Molyet, and Mansoor Alam. "Collision Warning System Using Naïve Bayes Classifier." Technium: Romanian Journal of Applied Sciences and Technology 4, no. 5 (June 4, 2022): 39–56. http://dx.doi.org/10.47577/technium.v4i5.6653.
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Motor vehicle crashes can lead to traumatic experiences. High-impact collisions usually cause severe injuries or fatalities. A collision warning system that analyzes driving behaviors and warns drivers of impending crashes can prevent road collisions and save lives, so increasing traffic safety. An application of the Naïve Bayes classifier model to determine the potential for rear-end collisions between highway vehicles is presented. The Naïve Bayes classifier is a supervised machine-learning model based on Bayes’s theorem. Two vehicles are utilized, with one vehicle following the other. The parameters studied are speed, distance, acceleration, and deceleration. Training examples involving over 100 potential collision scenarios have been evaluated. Simulation results show that the model successfully responds to and correctly predicts potential collisions.
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Ellis, William A., Sean I. FitzGibbon, Benjamin J. Barth, Amanda C. Niehaus, Gwendolyn K. David, Brendan D. Taylor, Helena Matsushige, et al. "Daylight saving time can decrease the frequency of wildlife–vehicle collisions." Biology Letters 12, no. 11 (November 2016): 20160632. http://dx.doi.org/10.1098/rsbl.2016.0632.
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Daylight saving time (DST) could reduce collisions with wildlife by changing the timing of commuter traffic relative to the behaviour of nocturnal animals. To test this idea, we tracked wild koalas ( Phascolarctos cinereus ) in southeast Queensland, where koalas have declined by 80% in the last 20 years, and compared their movements with traffic patterns along roads where they are often killed. Using a simple model, we found that DST could decrease collisions with koalas by 8% on weekdays and 11% at weekends, simply by shifting the timing of traffic relative to darkness. Wildlife conservation and road safety should become part of the debate on DST.
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Leung, Kevin, Jerry Iu, Gabriel Gelgor, and Arbri Halili. "Collision Statistics: A Study in Toronto Road Safety." STEM Fellowship Journal 2, no. 1 (July 1, 2016): 49–54. http://dx.doi.org/10.17975/sfj-2016-009.
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This study set out to determine the major causes of vehicle collisions in the City of Toronto and to propose solutions to the issue. We have made use of Toronto Open Data to gather statistics on wellbeing demographics, traffic, economics, and collisions. Data was analyzed and it was determined that six neighbourhoods deviated from the normal ratio of collisions to road volume. We researched these six neighbourhoods and determined that most accidents occur in commercial areas and the least accidents happen in residential areas. Residential areas are not areas where large amounts of people collect daily, but commercial areas are, and the high amounts of pedestrian movement within commercial areas coupled with vehicle traffic likely increases the chance of collisions. Vehicle accidents can be reduced in several ways, such as producing more PSAs, enforcing jaywalk prevention, reducing speeding and employing advents in driving technology such as driverless cars.
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ErickTandi, Tinyami, Tinyami ErickTandi, Tinyami ErickTandi, KyungHee Kim, Tambetakaw Njang Gilbert, JaeWook Choi, and JaeWook Choi. "Motorcycle-Related Head and Limbs Injuries from Road Traffic Accident at a Second Level Hospital in Cameroon." Journal of Preventive Medicine And Care 2, no. 3 (March 8, 2019): 20–28. http://dx.doi.org/10.14302/issn.2474-3585.jpmc-19-2633.
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Motorcycles have been increasing used widely in various urban, suburban and villages in Cameroon with an increased in accidents resulting to injuries among the population. Head and limbs injuries are responsible for most of the cases encountered from related crashes. A prospective study on head and limbs injuries resulting from motorcycle crash were assessed among the different cases brought to the casualty and emergency department of the Kumba district hospital. Most of the injured cases were of motorcycle and other vehicle collisions 203 (47.65) and the least among motorcycle lone crash 51 (11.97). Motorcycle to motorcycle collisions accounted for 107 (25.12 %) of the cases. 65 (15.26%) were motorcycle with pedestrians related collision. Stepping up and facilitating the regulations on licenses and the use of personal protective equipment for riders, improvement of roads infrastructures with pedestrian path, expanding health facilities and equipment, and human resources for health as well as empowering the population on road safety measures will be very important for RTAs control measures of the nation.
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Kuyumcu, Zeliha Cagla, Suhrab Ahadi, and Hakan Aslan. "Analysis of Pedestrian-Vehicle Crashes Using Artificial Learning Methods: City of Sakarya Case Study." Academic Perspective Procedia 4, no. 2 (November 6, 2021): 221–30. http://dx.doi.org/10.33793/acperpro.04.02.54.
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The lives of approximately 1.3 million people are cut short every year as a result of road traffic crashes. Between 20 and 50 million people suffer non-fatal injuries, with many incurring a disability as a result of their injury. The risk of dying in a road traffic crash is more than 3 times higher in low-income countries than in high-income countries [1]. In Turkey, 18% of traffic accidents was related to pedestrian-vehicle collisions in urban roads in 2020. In addition, 20% of death toll caused by accidents is pedestrians in 2020 [2]. This study deals with the some of classifiers to forecast the number of injuries as a result of traffic accidents. The classifier’s performance ratios were also examined.
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Riadh, Harizi. "Land artificialization, economic growth, and road insecurity: Theoretical improvements and empirical validation for the case of Algeria." Technium Social Sciences Journal 18 (April 7, 2021): 241–55. http://dx.doi.org/10.47577/tssj.v18i1.3073.
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This paper applies the Kuznets (1955) curve approach to road traffic crashes in Algeria based on active population, motorization rate, income per capita, and land artificialization. It aims to establish a link between economic development and road safety by estimating the terms of quadratic equations related to the occurrence of traffic collisions. The results reveal that a link between economic development and road safety can be validated by two econometric specifications for the Kuznets curve (KC). Indeed, because economic conditions remained favorable, the Algerian economy reached its inflection point in 2011 and then entered the second phase of the KC. The increase in the level of economic development then in turn led to an improved road-safety situation in terms of lower mortality rates on the roads.