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MOUSSA, NAJEM. "SIMULATION STUDY OF TRAFFIC ACCIDENTS IN BIDIRECTIONAL TRAFFIC MODELS." International Journal of Modern Physics C 21, no. 12 (December 2010): 1501–15. http://dx.doi.org/10.1142/s0129183110016007.
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Conditions for the occurrence of bidirectional collisions are developed based on the Simon–Gutowitz bidirectional traffic model. Three types of dangerous situations can occur in this model. We analyze those corresponding to head-on collision; rear-end collision and lane-changing collision. Using Monte Carlo simulations, we compute the probability of the occurrence of these collisions for different values of the oncoming cars' density. It is found that the risk of collisions is important when the density of cars in one lane is small and that of the other lane is high enough. The influence of different proportions of heavy vehicles is also studied. We found that heavy vehicles cause an important reduction of traffic flow on the home lane and provoke an increase of the risk of car accidents.
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Sysoev, Anton, Vladimir Klyavin, Alexandra Dvurechenskaya, Albert Mamedov, and Vladislav Shushunov. "Applying Machine Learning Methods and Models to Explore the Structure of Traffic Accident Data." Computation 10, no. 4 (March 31, 2022): 57. http://dx.doi.org/10.3390/computation10040057.
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The problem of reducing the increasing number of road traffic accidents has become more relevant in recent years. According to the United Nations plan this number has to be halved by 2030. A very effective way to handle it is to apply the machine learning paradigm to retrospective road traffic accident datasets. This case study applies machine learning techniques to form typical “portraits” of drivers violating road traffic rules by clustering available data into seven homogeneous groups. The obtained results can be used in forming effective marketing campaigns for different target groups. Another relevant problem under consideration is to use available retrospective statistics on mechanical road traffic accidents without victims to estimate the probable type of road traffic accident for the driver taking into account her/his personal features (such as social characteristics, typical road traffic rule violations, driving experience, and age group). For this purpose several machine learning models were applied and the results were discussed.
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Planić, Jovana. "Defining risks on road sections during the transport of dangerous goods in the Serbian army using the linear mathematical programming model." Vojnotehnicki glasnik 70, no. 4 (2022): 939–71. http://dx.doi.org/10.5937/vojtehg70-36071.
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Introduction/purpose: The paper presents a model for the selection of a route for the transport of dangerous goods using DEA (Data Envelopment Analysis) models and fuzzy logic systems. The presented model is used to define the risk on road sections during the transport of dangerous goods as well as to select the optimal route for the realization of the transport task. Methods: The model consists of two phases. The first phase includes the application of DEA models in which formed input and output models are connected in the output DEA final form which shows routes with a satisfactory level of traffic safety and at the same time eliminates routes with low traffic safety. The second phase involves the application of fuzzy logic systems, and as a way out of the fuzzy system, preference is given to one route. Route evaluation is based on six criteria, namely: route length, number of access points, AADT (annual average daily traffic), the number of traffic accidents with fatalities, the number of traffic accidents with the injured and the number of traffic accidents with material damage. When the values of the input criteria are entered, a calculation and evaluation is performed, and, as an exit from the fuzzy system, preference is given to one of the entered routes (the route with the lowest level of risk). The criteria used were defined on the basis of expert assessments. Results: A user program that represents decision support in traffic service. Conclusion: The user platform was created for the Matlab R2015a software package with the ability to be adapted to specific problems.
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Droj, Gabriela, Laurențiu Droj, and Ana-Cornelia Badea. "GIS-Based Survey over the Public Transport Strategy: An Instrument for Economic and Sustainable Urban Traffic Planning." ISPRS International Journal of Geo-Information 11, no. 1 (December 30, 2021): 16. http://dx.doi.org/10.3390/ijgi11010016.
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Traffic has a direct impact on local and regional economies, on pollution levels and is also a major source of discomfort and frustration for the public who have to deal with congestion, accidents or detours due to road works or accidents. Congestion in urban areas is a common phenomenon nowadays, as the main arteries of cities become congested during peak hours or when there are additional constraints such as traffic accidents and road works that slow down traffic on road sections. When traffic increases, it is observed that some roads are predisposed to congestion, while others are not. It is evident that both congestion and urban traffic itself are influenced by several factors represented by complex geospatial data and the spatial relationships between them. In this paper were integrated mathematical models, real time traffic data with network analysis and simulation procedures in order to analyze the public transportation in Oradea and the impact on urban traffic. A mathematical model was also adapted to simulate the travel choices of the population of the city and of the surrounding villages. Based on the network analysis, traffic analysis and on the traveling simulation, the elements generating traffic congestion in the inner city can be easily determined. The results of the case study are emphasizing that diminishing the traffic and its effects can be obtained by improving either the public transport density or its accessibility.
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Budzyński, Marcin, Kazimierz Jamroz, Łukasz Jeliński, and Anna Gobis. "The Effects of Roadside Hazards on Road Accident Severity." Journal of KONBiN 49, no. 2 (June 1, 2019): 319–39. http://dx.doi.org/10.2478/jok-2019-0038.
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Abstract The risk of becoming involved in an accident emerges when elements of the transport system do not operate properly (man – vehicle – road – roadside). The road, its traffic layout and safety equipment have a critical impact on road user safety. This gives infrastructural work a priority in road safety strategies and programmes. Run-off-road accidents continue to be one of the biggest problems of road safety with consequences including vehicle roll-over or hitting a roadside object. This type of incident represents more than 20% of rural accidents and about 18% of all road deaths in Poland. Mathematical models must be developed to determine how selected roadside factors affect road safety and provide a basis for new roadside design rules and guidelines.
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TSENG, JIE-JUN, MING-JER LEE, and SAI-PING LI. "HEAVY-TAILED DISTRIBUTIONS IN FATAL TRAFFIC ACCIDENTS: ROLE OF HUMAN ACTIVITIES." International Journal of Modern Physics C 20, no. 08 (August 2009): 1281–90. http://dx.doi.org/10.1142/s0129183109014345.
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Human activities can play a crucial role in the statistical properties of observables in many complex systems such as social, technological, and economic systems. We demonstrate this by looking into the heavy-tailed distributions of observables in fatal plane and car accidents. Their origin is examined and can be understood as stochastic processes that are related to human activities. Simple mathematical models are proposed to illustrate such processes and compared with empirical results obtained from existing databanks.
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Najafi Moghaddam Gilani, Vahid, Seyed Mohsen Hosseinian, Meisam Ghasedi, and Mohammad Nikookar. "Data-Driven Urban Traffic Accident Analysis and Prediction Using Logit and Machine Learning-Based Pattern Recognition Models." Mathematical Problems in Engineering 2021 (May 26, 2021): 1–11. http://dx.doi.org/10.1155/2021/9974219.
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Modeling the severity of accidents based on the most effective variables accounts for developing a high-precision model presenting the possibility of occurrence of each category of future accidents, and it could be utilized to prioritize the corrective measures for authorities. The purpose of this study is to identify the variables affecting the severity of the injury, fatal, and property damage only (PDO) accidents in Rasht city by collecting information on urban accidents from March 2019 to March 2020. In this regard, the multiple logistic regression and the pattern recognition type of artificial neural network (ANN) as a machine learning solution are used to recognize the most influential variables on the severity of accidents and the superior approach for accident prediction. Results show that the multiple logistic regression in the forward stepwise method has R2 of 0.854 and an accuracy prediction power of 89.17%. It turns out that the accidents occurred between 18 and 24 and KIA Pride vehicle has the highest effect on increasing the severity of accidents, respectively. The most important result of the logit model accentuates the role of environmental variables, including poor lighting conditions alongside unfavorable weather and the dominant role of unsafe and poor quality of vehicles on increasing the severity of accidents. In addition, the machine learning model performs significantly better and has higher prediction accuracy (98.9%) than the logit model. In addition, the ANN model’s greater power to predict and estimate future accidents is confirmed through performance and sensitivity analysis.
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Borucka, Anna, Edward Kozłowski, Piotr Oleszczuk, and Andrzej Świderski. "Predictive analysis of the impact of the time of day on road accidents in Poland." Open Engineering 11, no. 1 (December 12, 2020): 142–50. http://dx.doi.org/10.1515/eng-2021-0017.
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AbstractThe steady increase in the number of road users and their growing mobility mean that the issue of road safety is still a topical one. Analyses of factors influencing the number of road traffic accidents contribute to the improvement of road safety. Because changes in traffic volume follow a daily rhythm, hour of the day is an important factor affecting the number of crashes. The present article identifies selected mathematical models which can be used to describe the number of road traffic accidents as a function of the time of their occurrence during the day. The study of the seasonality of the number of accidents in particular hours was assessed. The distributions of the number of accidents in each hour were compared using the Kruskal-Wallis and Kolmogorov-Smirnov tests. Multidimensional scaling was used to present the found similarities and differences. Similar hours were grouped into clusters, which were used in further analysis to construct the ARMAXmodel and the Holt-Winters model. Finally, the predictive capabilities of each model were assessed.
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Göttlich, Simone, and Thomas Schillinger. "Microscopic and macroscopic traffic flow models including random accidents." Communications in Mathematical Sciences 19, no. 6 (2021): 1579–609. http://dx.doi.org/10.4310/cms.2021.v19.n6.a6.
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Zong, Fang, Huiyong Zhang, Hongguo Xu, Xiumei Zhu, and Lu Wang. "Predicting Severity and Duration of Road Traffic Accident." Mathematical Problems in Engineering 2013 (2013): 1–9. http://dx.doi.org/10.1155/2013/547904.
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This paper presents a model system to predict severity and duration of traffic accidents by employing Ordered Probit model and Hazard model, respectively. The models are estimated using traffic accident data collected in Jilin province, China, in 2010. With the developed models, three severity indicators, namely, number of fatalities, number of injuries, and property damage, as well as accident duration, are predicted, and the important influences of related variables are identified. The results indicate that the goodness-of-fit of Ordered Probit model is higher than that of SVC model in severity modeling. In addition, accident severity is proven to be an important determinant of duration; that is, more fatalities and injuries in the accident lead to longer duration. Study results can be applied to predictions of accident severity and duration, which are two essential steps in accident management process. By recognizing those key influences, this study also provides suggestive results for government to take effective measures to reduce accident impacts and improve traffic safety.
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Wang, Si Shuan. "Mathematical Modeling is Occupied Lane Road Access to the City 's Ability to Influence when the Accident." Advanced Materials Research 971-973 (June 2014): 2107–10. http://dx.doi.org/10.4028/www.scientific.net/amr.971-973.2107.
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With the development of cities, the traffic problem is getting attention , including a wide variety of lane blocking traffic problem is one of the major problems , such as car accidents , construction and other Jeeves , Jeeves research questions have lane is occupied impact on urban road capacity help science to solve these problems , this study had an accident when two easy-to-understand model to solve the problem in question . For question one and question two , we established a model of the actual capacity will be standardized different vehicles , and statistics in the video pcu amount of data analyzed by the choice of the trigonometric curve fitting using cftool Toolbox obtained as a function of the actual capacity and time , and finally by analyzing the relationship between the relevant factors and the number of vehicles in different lanes , traffic signal mechanism to complete the first two questions . For questions three and four problems , we established a mathematical model of the length of the traffic jam , traffic jams build road capacity and the actual length of the upstream traffic , traffic jam quantitative function of time , the same amount through the video pcu statistics , curve fitting , determine the unknown parameters to obtain the corresponding function , and using the prediction and analysis functions . The data given in the problem into three of the four models, solve for T equal to about 5.5 minutes . Model for the inevitable disadvantages , we try to model the new extension partly solved.
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Ma, Lu, and Xuedong Yan. "Assessing Traffic Accident Occurrence of Road Segments through an Optimized Decision Rule." Mathematical Problems in Engineering 2015 (2015): 1–6. http://dx.doi.org/10.1155/2015/592626.
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Statistical models for estimating the safety status of transportation facilities have received great attention in the last two decades. These models also perform an important role in transportation safety planning as well as diagnoses of locations with high accident risks. However, the current methods largely rely on regression analyses and therefore they could ignore the multicollinearity characteristics of factors, which may provide additional information for enhancing the performance of forecasting models. This study seeks to develop more precise models for forecasting safety status as well as addressing the issue of multicollinearity of dataset. The proposed mathematical approach is indeed a discriminant analysis with respect to the goal of minimizing Bayes risks given multivariate distributions of factors. Based on this model, numerical analyses also perform with the application of a simulated dataset and an empirically observed dataset of traffic accidents in road segments. These examples essentially illustrate the process of Bayes risk minimization on predicating the safety status of road segments toward the objective of smallest misclassification rate. The paper finally concludes with a discussion of this methodology and several important avenues for future studies are also provided.
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Cheng, Rui, Ye Pan, and Lian Xie. "Analysis of Vehicle-Pedestrian Accident Risk Based on Simulation Experiments." Mathematical Problems in Engineering 2022 (August 29, 2022): 1–14. http://dx.doi.org/10.1155/2022/7891232.
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Vehicle-pedestrian accidents are one of the main types of road traffic accidents in China because of their mixed traffic features. By analyzing the characteristics of vehicle-pedestrian accidents, the head injury criterion (HIC) was selected as a quantitative index of pedestrian head injury risk, and vehicle-pedestrian collision simulation tests were carried out using PC-Crash. From the collected test data, the multivariate relationship models between the HIC, vehicle speed, and collision angle were fitted for different vehicle types. A risk assessment method for vehicle-pedestrian accidents based on the HIC was proposed by the Fisher optimal segmentation algorithm. Finally, a new index for evaluating the accuracy of accident risk classification, the degree of error classification, was proposed to verify the validity of the accident risk assessment method. The results show that vehicle speed, collision angle, and vehicle type play a key role in pedestrian injury. Flat-headed vehicles are more likely to cause head injuries to pedestrians than high-headed and low-headed vehicles. Rear-end collisions cause more injuries to pedestrians than side collisions. The research results can provide guidance and a basis for accident liability determination, speed limit management, vehicle safety design, and human injury mechanism analysis.
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Povalyaev, S., and O. Saraiev. "MODELING OF THE MECHANISM OF VEHICLE OVERTURNING IN THE PROCESS OF DEVELOPMENT OF ROAD TRAFFIC ACCIDENT." Theory and Practice of Forensic Science and Criminalistics 20, no. 2 (December 4, 2019): 320–28. http://dx.doi.org/10.32353/khrife.2.2019.24.
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The development of mathematical models of vehicle overturning has been given significant attention by many researchers because of the need to obtain reliable information on the circumstances of road traffic accidents. Research of road traffic accidents with the overturning of vehicles is related with the difficulty to determinate the mechanism of overturning, because expert calculation methods do not always use the adapted mathematical models. Most of the methods focus on determining the minimum (critical) speed of vehicles, which leads to its overturning. However, the real speed of vehicles before overturning can be much higher. In this paper, a mathematical model of the process of vehicle overturning after a collision with an immovable lateral obstacle is given. Thus the overturning moment caused by the inertia forces acts on the vehicle, and the moment from the gravity that holds the vehicle from overturning. It is necessary to mark that the shoulder of moment from gravity changes from a maximal value to 0 in the process of vehicle overturning. The mathematical model is based on the basic equation of dynamics for rotational motion. The developed mathematical model is a nonlinear homogeneous differential equation of second order. A solution of this equation is obtained that allows us to determine the conditions for the vehicles overturning and to investigate the basic parameters of the movement of vehicles in the process of overturning from the moment when the center of mass of the vehicle begins to rise until the moment of its maximum lifting. A comparison of the results of calculating the critical speed of vehicles with results obtained on the basis of the law of energy conservation was carried out. The results are fully agreed. The numerical results obtained using a mathematical model for a particular vehicle have been analyzed.
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Subotić, Marko, Nemanja Stepanović, Vladan Tubić, Edis Softić, and Mouhamed Bayane Bouraima. "Models of Analysis of Credible Deviation from Speed Limits on Two-Lane Roads of Bosnia and Herzegovina." Complexity 2022 (October 7, 2022): 1–13. http://dx.doi.org/10.1155/2022/2832175.
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Any deviation of speed in a traffic flow from a speed limit represents a potential risk of traffic accidents, so speed management appears as an imperative. However, an inadequately set speed limit often causes drivers’ noncompliance to it in the conditions of real traffic flow. By determining the value of exceeding the speed limit according to vehicle classes, it is possible to recommend a credible speeding value that can be considered credible up to a value above the speed limit. In this paper, deterministic multistep mathematical models of speed deviation from the speed limit as a function of longitudinal gradient for the proposed vehicle classes were developed. A total of 11 measuring sections with different traffic flow types were analyzed. Based on a detailed analysis of speeding, models for the deviation of the 15th, 50th, and 85th percentiles were obtained, with the aim of adjusting the credible deviation to control measures. The results obtained in this study were compared with a survey of traffic flow speeding on two-lane roads conducted in Serbia.
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MOUSSA, NAJEM. "DANGEROUS SITUATIONS IN TWO-LANE TRAFFIC FLOW MODELS." International Journal of Modern Physics C 16, no. 07 (July 2005): 1133–48. http://dx.doi.org/10.1142/s0129183105007790.
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This paper investigates the probability of car accidents (PCA) in two-lane traffic flow models. We introduce new conditions for the occurrence of dangerous situations (DS) caused by an unexpected lane changing vehicles. Two different lane changing rules are considered, say symmetric and asymmetric. For the symmetric rules, we investigate the influence of the Nagel–Schreckenberg parameters such as the maximal speed, the randomization probability, …, on the PCA when vehicle moves forward or changes lanes. It is found that the forward PCA is as likely as that in one-lane traffic model. As regards to lane changing, the properties of the PCA are qualitatively different from those in one-lane traffic. For the asymmetric rules, we investigate the effect of the slack parameter Δ, introduced to adjust the inversion point of lane-usage, on the PCA. Contrarily to one-lane traffic, the forward PCA in the right lane exhibits two maximums for some range of Δ; the first one is located at low density and the second at high density. The lane changing PCA from right to left is found to decrease with increase of Δ. However, no DS exist when vehicles change from left to right.
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Jabłonka, Jarosław. "The analysis of exigencies of priority of crossing at intersections from the game theory's point of view." AUTOBUSY – Technika, Eksploatacja, Systemy Transportowe 19, no. 6 (September 7, 2018): 110–14. http://dx.doi.org/10.24136/atest.2018.047.
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The assumption that each road participant adheres to the rules, ideally adapts his behavior to the prevailing road conditions, is unrealistic, and as the basis for taking action can lead to collisions and accidents. The article presents the theoretical models allowing to understand the behavior of drivers who deliberately enforce the priority of passing, and their only motivation is the shortest travel time through the intersection. Two types of situations at crossroads are considered: with guided and non-guided traffic with the STOP sign. The presented mathematical models are illustrated by the real-life recordings of drivers available on the Internet.
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Ding, Huizhe, Raja Ariffin Raja Ghazilla, Ramesh Singh Kuldip Singh, and Lina Wei. "Vehicle Driving Risk Prediction Model by Reverse Artificial Intelligence Neural Network." Computational Intelligence and Neuroscience 2022 (October 7, 2022): 1–11. http://dx.doi.org/10.1155/2022/3100509.
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The popularity of private cars has brought great convenience to citizens’ travel. However, the number of private cars in society is increasing yearly, and the traffic pressure on the road is also increasing. The number of traffic accidents is increasing yearly, and the vast majority are caused by small private cars. Therefore, it is necessary to improve the traffic safety awareness of drivers and help car manufacturers to design traffic risk prediction systems. The Backpropagation neural network (BPNN) algorithm is used as the technical basis, combined with the MATLAB operation program, to simulate the driving process of the car. Dynamic predictive models are built to predict and analyze vehicle safety risks. Multiple experiments found that: (1) in various simulations, the simulation driving process of MATLAB is more in line with the actual car driving process; (2) the error between BPNN and the actual driving prediction is within 0.4, which can meet the actual needs. Predictive models are optimized to deploy and predict in various traffic situations. The model can effectively prompt risk accidents, reduce the probability of traffic accidents, provide a certain degree of protection for the lives of drivers and passengers, and significantly improve the safety of traffic roads.
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Lord, Dominique, and Bhagwant N. Persaud. "Accident Prediction Models With and Without Trend: Application of the Generalized Estimating Equations Procedure." Transportation Research Record: Journal of the Transportation Research Board 1717, no. 1 (January 2000): 102–8. http://dx.doi.org/10.3141/1717-13.
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Accident prediction models (APMs) are useful tools for estimating the expected number of accidents on entities such as intersections and road sections. These estimates typically are used in the identification of sites for possible safety treatment and in the evaluation of such treatments. An APM is, in essence, a mathematical equation that expresses the average accident frequency of a site as a function of traffic flow and other site characteristics. The reliability of an APM estimate is enhanced if the APM is based on data for as many years as possible, especially if data for those same years are used in the safety analysis of a site. With many years of data, however, it is necessary to account for the year-to-year variation, or trend, in accident counts because of the influence of factors that change every year. To capture this variation, the count for each year is treated as a separate observation. Unfortunately, the disaggregation of the data in this manner creates a temporal correlation that presents difficulties for traditional model calibration procedures. An application is presented of a generalized estimating equations (GEE) procedure to develop an APM that incorporates trend in accident data. Data for the application pertain to a sample of four-legged signalized intersections in Toronto, Canada, for the years 1990 through 1995. The GEE model incorporating the time trend is shown to be superior to models that do not accommodate trend and/or the temporal correlation in accident data.
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Budzyński, Marcin, Kazimierz Jamroz, and Wojciech Kustra. "Road safety inspection as a tool for road safety management – the polish experience." Journal of KONBiN 42, no. 1 (June 1, 2017): 43–62. http://dx.doi.org/10.1515/jok-2017-0017.
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Abstract In Poland, road inspections were implemented in June 2014 on all national roads. Previous traffic surveys mainly looked at the technical condition of roads, signs and markings; other safety issues were overlooked. The main problem of the inspections is that the qualitative assessment is subjective which affects the classification of the sources of hazard on the road. The paper presents an analysis of the variability of the qualitative assessments of road defects when they are assessed by different teams of inspectors. On this basis, guidelines were developed for the classification of risks based on the relationship between sources of road hazard and the personal and economic losses involved in road accidents. These relationships are quantified using mathematical models to simulate the effect of hazard variability on the consequences of selected road accident causes on sections of the road network.
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Chang, Lv, Qiongqiong Liu, Jin Yan, Peng Liu, Sida Zhu, Xiaoming Hu, Jun Ni, and Tong Zhang. "Risk Field Model Construction and Risk Classification of Hazardous Chemical Transportation." Mathematical Problems in Engineering 2022 (August 25, 2022): 1–13. http://dx.doi.org/10.1155/2022/7075996.
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To reduce the risk of hazardous chemical road transportation, domestic and foreign scholars have analyzed transportation risks from theoretical points of view and built risk assessment models. Based on 483 cases of hazardous chemical road transportation accidents from 2015 to 2019, this paper analyzes the causes of accidents from the perspective of traffic regulations and constructs a risk field model of hazardous chemical transportation. Through the simulation of an accident by TruckSim, a risk classification is completed according to the risk field model of hazardous chemical transportation. The results show that the model can be used to evaluate the risk of hazardous chemical transportation in complex environments and provide criteria for the safe control of hazardous chemical transportation vehicles.
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Zhong-xiang, Feng, Lu Shi-sheng, Zhang Wei-hua, and Zhang Nan-nan. "Combined Prediction Model of Death Toll for Road Traffic Accidents Based on Independent and Dependent Variables." Computational Intelligence and Neuroscience 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/103196.
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In order to build a combined model which can meet the variation rule of death toll data for road traffic accidents and can reflect the influence of multiple factors on traffic accidents and improve prediction accuracy for accidents, the Verhulst model was built based on the number of death tolls for road traffic accidents in China from 2002 to 2011; and car ownership, population, GDP, highway freight volume, highway passenger transportation volume, and highway mileage were chosen as the factors to build the death toll multivariate linear regression model. Then the two models were combined to be a combined prediction model which has weight coefficient. Shapley value method was applied to calculate the weight coefficient by assessing contributions. Finally, the combined model was used to recalculate the number of death tolls from 2002 to 2011, and the combined model was compared with the Verhulst and multivariate linear regression models. The results showed that the new model could not only characterize the death toll data characteristics but also quantify the degree of influence to the death toll by each influencing factor and had high accuracy as well as strong practicability.
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Pečeliūnas, Robertas, and Olegas Prentkovskis. "Influence of Shock-Absorber Parameters on Vehicle Vibrations during Braking." Solid State Phenomena 113 (June 2006): 235–40. http://dx.doi.org/10.4028/www.scientific.net/ssp.113.235.
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The main goals of the work are to define consistent patterns of impacts exercised by vibration of the vehicle in emergency braking on the vehicle’s movement mode and on the braking distance and to analyze the formation of oscillation. Besides, it is aimed to extend expert’s opportunities for modeling vehicle movement for investigation of accidents’ circumstances related to vehicle braking with the aid of the developed models. A mathematical model of impact exercised by bumper’s characteristics on the vehicle’s braking process has been designed, enabling the determination of coefficients of longitudinal relative forces of the vehicle’s front and rear axles, which depend on the road’s pavement and its condition. The obtained research results extend the vehicle vibration theory in transitional movement modes, which are used in the design and improvement of vehicle suspensions, as well as in traffic accident’s investigation and improvement of methodology of their expertise calculations.
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Al-Zahrani, Abdulrahem. "An Application of Some Mathematical Models to traffic Accident Statistics in Saudi Arabia." Journal of King Abdulaziz University-Engineering Sciences 10, no. 2 (1998): 3–14. http://dx.doi.org/10.4197/eng.10-2.8.
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Vasyutina, A. A., V. V. Popov, A. I. Kondratyev, and A. L. Boran-Keshishyan. "Improvement of the vessel traffic control system for accident-free electronic navigation in the port area." Journal of Physics: Conference Series 2061, no. 1 (October 1, 2021): 012105. http://dx.doi.org/10.1088/1742-6596/2061/1/012105.
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Abstract The increase in the intensity of navigation leads to unsafe navigation, which necessitates the improvement of existing measures to ensure safe navigation using specific mathematical models and methods. The configuration of the mathematical model of the traffic flow of ships obtained in this study is realizable on modern computer technology and can be applied by embedding advanced ship traffic control systems, which is an object of the infrastructure of a modern seaport.
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Akgüngör, Ali Payıdar, and Erdem Doğan. "AN ARTIFICIAL INTELLIGENT APPROACH TO TRAFFIC ACCIDENT ESTIMATION: MODEL DEVELOPMENT AND APPLICATION." TRANSPORT 24, no. 2 (June 30, 2009): 135–42. http://dx.doi.org/10.3846/1648-4142.2009.24.135-142.
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This study proposes an Artificial Neural Network (ANN) model and a Genetic Algorithm (GA) model to estimate the number of accidents (A), fatalities (F) and injuries (I) in Ankara, Turkey, utilizing the data obtained between 1986 and 2005. For model development, the number of vehicles (N), fatalities, injuries, accidents and population (P) were selected as model parameters. In the ANN model, the sigmoid and linear functions were used as activation functions with the feed forward‐back propagation algorithm. In the GA approach, two forms of genetic algorithm models including a linear and an exponential form of mathematical expressions were developed. The results of the GA model showed that the exponential model form was suitable to estimate the number of accidents and fatalities while the linear form was the most appropriate for predicting the number of injuries. The best fit model with the lowest mean absolute errors (MAE) between the observed and estimated values is selected for future estimations. The comparison of the model results indicated that the performance of the ANN model was better than that of the GA model. To investigate the performance of the ANN model for future estimations, a fifteen year period from 2006 to 2020 with two possible scenarios was employed. In the first scenario, the annual average growth rates of population and the number of vehicles are assumed to be 2.0 % and 7.5%, respectively. In the second scenario, the average number of vehicles per capita is assumed to reach 0.60, which represents approximately two and a half‐fold increase in fifteen years. The results obtained from both scenarios reveal the suitability of the current methods for road safety applications.
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Habibzadeh, Mohammad, Mahmoud Ameri, Seyede Mojde Sadat Haghighi, and Hassan Ziari. "Application of Artificial Neural Network Approaches for Predicting Accident Severity on Rural Roads (Case Study: Tehran-Qom and Tehran-Saveh Rural Roads)." Mathematical Problems in Engineering 2022 (June 22, 2022): 1–14. http://dx.doi.org/10.1155/2022/5214703.
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Traffic accidents occur due to a combination of factors that lead to casualties and injuries. By identifying the most effective factors, it is possible for safety authorities to provide appropriate solutions for decreasing the accident severity and implementing preventive measures. The aim of this research was to present models to predict the accident severity on two-lane two-way (TLTW) rural highways in Iran over a one-year period from 2019 to 2020. Therefore, the occurrence probability of any type of accident was determined by artificial neural network (ANN)-based prediction models using nine independent variables affecting the accident severity. This study developed numerous ANN structures using back-propagation to model the potential nonlinear relationship between the accident severity and accident-related factors. Results indicated that among the models, the multilayer perceptron neural network (MLPNN) model with 6-2-2 partition had the best performance and prediction power. This model was developed using the standardized rescaling method for covariates and batch for training. Also, 9, 5, and 2 units were considered automatically for the input, hidden, and output layers, respectively, and the hyperbolic tangent and softmax were used as an activation function in the hidden and output layers, respectively. This model had the lowest cross-entropy error of 39.6 and the highest correct percentage of 82.5%, and the area under the receiver operating characteristic (ROC) curve was 0.852. Moreover, among all the effective variables, pavement condition index, roadside hazard, shoulder width, and passing zone ratio had the greatest impact on the accident severity. Finally, safety strategies were proposed to increase safety and reduce accidents along these roads.
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AlKheder, Sharaf, Fahad AlRukaibi, and Ahmad Aiash. "Risk analysis of traffic accidents’ severities: An application of three data mining models." ISA Transactions 106 (November 2020): 213–20. http://dx.doi.org/10.1016/j.isatra.2020.06.018.
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Kim, Soon Ho, Jong Won Kim, Hyun-Chae Chung, Gyoo-Jae Choi, and MooYoung Choi. "Behavioral Dynamics of Pedestrians Crossing between Two Moving Vehicles." Applied Sciences 10, no. 3 (January 26, 2020): 859. http://dx.doi.org/10.3390/app10030859.
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This study examines the human behavioral dynamics of pedestrians crossing a street with vehicular traffic. To this end, an experiment was constructed in which human participants cross a road between two moving vehicles in a virtual reality setting. A mathematical model is developed in which the position is given by a simple function. The model is used to extract information on each crossing by performing root-mean-square deviation (RMSD) minimization of the function from the data. By isolating the parameter adjusted to gap features, we find that the subjects primarily changed the timing of the acceleration to adjust to changing gap conditions, rather than walking speed or duration of acceleration. Moreover, this parameter was also adjusted to the vehicle speed and vehicle type, even when the gap size and timing were not changed. The model is found to provide a description of gap affordance via a simple inequality of the fitting parameters. In addition, the model turns out to predict a constant bearing angle with the crossing point, which is also observed in the data. We thus conclude that our model provides a mathematical tool useful for modeling crossing behaviors and probing existing models. It may also provide insight into the source of traffic accidents.
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Petruk, R. V., O. V. Lunova, and V. S. Garkushevskiy. "Improvement of methodology of justification of safe routes for transportation of dangerous substances and cargo." Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, no. 5 (2020): 112–17. http://dx.doi.org/10.33271/nvngu/2021-5/112.
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Purpose. To improve existing methods for safe routing when transporting hazardous materials as well as waste products. Methodology. Methods of mathematical modeling, methods of statistics, methods for predicting risks and long-term environmental consequences are used. Taking into account time factors, the distribution of population into different sections of highways is considered. Findings. Parameters of the transport network and their influence on the magnitude of the risk of an emergency situation and possible accidents in the transportation of hazardous waste (THW) are established in the work. An analysis is conducted of dangerous effects that can be caused by THW taking into account the parameters of road, transport network, type and modes of transport, and others. In order to minimize the risk of accidents during THW, it is proposed to use appropriate approaches and criteria K1 and K2, which take into account the lowest values of dangerous effects on the person during the transportation time, which allow evaluating the safety of the transportation system and the selected route, whereas their product takes into account all the possible main factors of the transportation system. Typical road and rail transport schemes have been identified to ensure a minimum number of accidents and reduce environmental and human hazards. Originality. Approaches are improved to transportation of dangerous goods by motorway and railroad, in particular, the parameters of curvature and inclination of the road, availability of settlements and bridges, meteorological conditions and traffic congestions, which improves the efficiency and safety of transportation of dangerous substances and materials. Practical value. The original mathematical models of mapping the route for transporting dangerous substances are offered while the existing ones are improved. The results of the research can be used by transport companies, public authorities in the transportation of hazardous substances and logistics and non-hazardous industries.
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Fuks, Henryk, and Nino Boccara. "Generalized Deterministic Traffic Rules." International Journal of Modern Physics C 09, no. 01 (February 1998): 1–12. http://dx.doi.org/10.1142/s0129183198000029.
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We study a family of deterministic models for highway traffic flow which generalize cellular automaton rule 184. This family is parameterized by the speed limit m and another parameter k that represents a "degree of aggressiveness" in driving, strictly related to the distance between two consecutive cars. We compare two driving strategies with identical maximum throughput: "conservative" driving with high speed limit and "aggressive" driving with low speed limit. Those two strategies are evaluated in terms of accident probability. We also discuss fundamental diagrams of generalized traffic rules and examine limitations of maximum achievable throughput. Possible modifications of the model are considered.
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Wang, Xinghua, Yong Peng, Weifeng Yu, Pengpeng Xie, Honghao Zhang, Lin Hu, and Yuan Quan. "The Analyses of Vehicle-to-Pedestrian Accidents by Integrating Rigid-Body Simulation and Robust Optimization Techniques." International Journal of Computational Methods 17, no. 07 (May 7, 2019): 1950026. http://dx.doi.org/10.1142/s0219876219500269.
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The objective of this study is to propose an approach for improving the efficiency of accident reconstruction and obtaining the probabilistic distribution of pre-impact parameters through integrating numerical simulation and robust optimization techniques. First, the ranges and probabilistic distribution of collision parameters are determined by investigators. Then, the optimal Latin hypercube design is used to generate sample points in predefined design space and corresponding responses are obtained by PC-Crash. The radial basis functions method is used to construct the surrogate models, accuracy evaluation is conducted using the cross-validation method. Finally, a robust optimization is completed to obtain the probabilistic distribution of collision parameters. Furthermore, a real-world vehicle-to-pedestrian accident is reconstructed to specifically explain and validate the method. The results show that the numerical simulation coupled with robust optimization technique is an effective means of obtaining the probabilistic distribution of pre-impact inputs. The proposed approach will help the traffic accident to scientifically conduct the traffic accident identification.
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Li, Na, and Jian Xin Liu. "A New Computer Simulation of Neck Injury Biomechanics." Key Engineering Materials 467-469 (February 2011): 339–44. http://dx.doi.org/10.4028/www.scientific.net/kem.467-469.339.
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Head and neck injuries are the most frequent severe injury resulting from traffic accidents. Neck injury mechanisms are difficult to study experimentally due to the variety of impact conditions involved, as well as ethical issues, such as the use of human cadavers and animals. Finite element analysis is a comprehensive computer aided mathematical method through which human head and neck impact tolerance can be investigated. Detailed cervical spine models are necessary to better understand cervical spine response to loading, improve our understanding of injury mechanisms, and specifically for predicting occupant response and injury in auto crash scenarios. The focus of this study was to develop a C1–C2 finite element model with optimized mechanical parameter. The most advanced material data available were then incorporated using appropriate nonlinear constitutive models to provide accurate predictions of response at physiological levels of loading. This optimization method was the first utilized in biomechanics understanding, the C1–C2 model forms the basis for the development of a full cervical spine model. Future studies will focus on tissue-level injury prediction and dynamic response.
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Kustra, Wojciech, Joanna Żukowska, Marcin Budzyński, and Kazimierz Jamroz. "Injury Prediction Models for Onshore Road Network Development." Polish Maritime Research 26, no. 2 (June 1, 2019): 93–103. http://dx.doi.org/10.2478/pomr-2019-0029.
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Abstract Integrating different modes of transport (road, rail, air and water) is important for port cities. To accommodate this need, new transport hubs must be built such as airports or sea ports. If ports are to grow, they must be accessible, a feature which is best achieved by building new roads, including fast roads. Poland must develop a network of fast roads that will provide good access to ports. What is equally important is to upgrade the network of national roads to complement fast roads. A key criterion in this case is to ensure that the roads are efficient to minimise time lost for road users and safe. With safety standards and safety management practices varying vastly across the EU, Directive 2008/96/EC of the European Parliament and of the Council was a way to ensure that countries follow procedures for assessing the impact of road projects on road safety and conduct road safety audits, road safety management and road safety inspections. The main goal of the research was to build mathematical models to combine road safety measures, i.e. injury density (DI) and accident density (DA), with road and traffic factors on longer sections, all based on risk analysis. The practical objective is to use these models to develop tools for assessing how new road projects will impact road safety. Because previous research on models to help estimate injuries (I) or injury density (DI) on long sections was scarce, the authors addressed that problem in their work. The idea goes back to how Poland is introducing procedures for assessing the effects of infrastructure on safety and developing a method to estimate accident indicators to support economic analysis for new roads, a solution applied in JASPERS. Another reason for the research was Poland’s insufficient and ineffective pool of road safety management tools in Poland. The paper presents analyses of several models which achieved satisfactory results. They are consistent with the work of other researchers and the outcomes of previous research conducted by the authors. The authors built the models based on a segmentation of national roads into sections from 10 to 50 km, making sure that they feature consistent cross-sections and average daily traffic volumes. Models were built based on the method described by Jamroz (Jamroz, 2011). Using the available road traffic volume data, each section was assigned variables defining geometric and traffic features. Based on studies conducted on road sections, the variables were either averaged over the entire length of the section or calculated as a percentage of the variable occurring over the entire length: related to traffic volume, roadside environment or cross section
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Kiyashko, Larisa A., and Victoria A. Ksenofontova. "RESEARCH OF DEFORMATION AND DESTRUCTION OF CAR ELEMENTS UNDER EXTREME CONDITIONS." International Journal of Advanced Studies 12, no. 2 (June 30, 2022): 21–35. http://dx.doi.org/10.12731/2227-930x-2022-12-2-21-35.
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The article is devoted to the improvement of the methodology for the examination of the operation the vehicles in extreme conditions that occur during road traffic accidents (RTA). Of great interest in the field of road safety are the tasks of determining the causes of RTA and the conditions under which they occur. There are computer systems that allow modeling the processes of interaction automobile vehicles with obstacles and among themselves during an accident. These developments based on various mathematical models of the car collision process. The most reliable and promising are systems that based on methods for analyzing plastic deformations and destruction of car structural elements during an accident. The basis of these methods is the law of conservation energy or the model of the transition of the kinetic energy of a moving vehicle into the potential energy of a structure deformed after an accident. This process described with the help of the parameter – the energy equivalent of the speed. The analysis of the object is study – automobile body structures carried out. They classified as thin-walled shell structures that are easily plastically deformed. The available methods for solving the problems of analysis the elastic-plastic deformations in such structures do not allow providing the high accuracy of the solution necessary for the examination of the RTA.
 Purpose – improvement of the methodology for conducting an autotechnical examination of an accident.
 Methodology: solution of inverse problems of continuum mechanics.
 Results: a variant of the finite element representation of the design and a method of the variational approach to determining the energy criteria of the process under study were developed. It provides the greatest accuracy in solving the tasks.
 Practical implications: it is expedient to apply the obtained results when carrying out an autotechnical examination of an accident.
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Park, Sangmin, Byung-Won On, Ryong Lee, Min-Woo Park, and Sang-Hwan Lee. "A Bi–LSTM and k-NN Based Method for Detecting Major Time Zones of Overloaded Vehicles." Symmetry 11, no. 9 (September 12, 2019): 1160. http://dx.doi.org/10.3390/sym11091160.
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Overloaded vehicles such as large cargo trucks tend to cause large traffic accidents. Such traffic accidents often bring high mortality rates, including injuries and deaths, and cause fatal damage to road structures such as roads and bridges. Therefore, there is a vicious circle in which a lot of the budgets is spent for accident restoration and road maintenance. It is important to control overloaded vehicles that are around roads in urban areas. However, it often takes a lot of manpower to track down on overloaded vehicles at appropriate interception points during a specific time. Moreover, the drivers tend to avoid interception by bypassing the interception point, while exchanging interception information with each other. In this work, the main bridges in a city are chosen as the interception point. Since installing vehicle-weighing devices on the road surface is expensive and the devices cause frequent faults after the installation, inexpensive general-purpose Internet of Things (IoT) sensors, such as acceleration and gyroscope sensors, are installed on the bridges. First, assuming that the sensing value of the overloaded vehicle is different from the nonoverloaded vehicle, we investigate the difference in the sensed values between the overloaded and nonoverloaded vehicles. Then, based on the hypothesis, we propose a new method to identify prime time zones with overloaded vehicles. Technically, the proposed method comprises two steps. In the first step, we propose a new bridge traffic classification model using Bidirectional Long Short-Term Memory (Bi–LSTM) that automatically classifies time series data to either high or low traffic condition. The Bi–LSTM model has higher accuracy than existing neural network models because it has a symmetric neural network structure, by which input information can be processed in forward and backward directions. In the second step, we propose a new method of automatically identifying top-k time zones with many overloaded vehicles under the high traffic condition. It first uses the k-Nearest Neighbor (NN) algorithm to find the sensing value, most similar to the actual sensing value of the overloaded vehicle, in the high traffic cluster. According to the experimental results, there is a high difference of the sensing values between the overloaded and the nonoverloaded vehicle, through statistical verification. Also, the accuracy of the proposed method in the first step is ~75%, and the top-k time zones in which overloaded vehicles are crowded are identified automatically.
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Qin, Yanyan, Hao Wang, and Daiheng Ni. "Lighthill-Whitham-Richards Model for Traffic Flow Mixed with Cooperative Adaptive Cruise Control Vehicles." Transportation Science 55, no. 4 (July 2021): 883–907. http://dx.doi.org/10.1287/trsc.2021.1057.
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In the future, road traffic will incorporate a random mix of manual vehicles and cooperative adaptive cruise control (CACC) vehicles, where a CACC vehicle will degrade to an adaptive cruise control (ACC) vehicle when vehicle-to-vehicle communications are not available. This paper proposes a generalized framework of the Lighthill-Whitham-Richards (LWR) model for such mixed vehicular flow under different CACC penetration rates. In this approach, the kinematic wave speed propagating through the mixed platoon was theoretically proven to be the slope of mixed fundamental diagram. In addition, the random degradation from CACC to ACC was captured in mathematical expectation for traffic scenarios where the CACC only monitors one vehicle ahead. Three concrete car-following models, the intelligent driver model (IDM) and CACC/ACC models validated by Partners for Advanced Transit and Highways (PATH) program, were selected as examples to investigate the propagation of small perturbations and shock waves. Numerical simulations were also performed based on the selected car-following models. Moreover, the derived mixed LWR model was applied to solve some traffic flow problems. It indicates that the proposed LWR model is able to describe the propagation properties of both small perturbations and shock waves. The mixed LWR model can also be used to solve some practical problems, such as the queue caused by a traffic accident and the impact of a moving bottleneck. More importantly, the proposed generalized framework admits other CACC/ACC/regular car-following models, including those developed from further experiments.
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Karthikeyan, P., Wei-Lun Chen, and Pao-Ann Hsiung. "Autonomous Intersection Management by Using Reinforcement Learning." Algorithms 15, no. 9 (September 13, 2022): 326. http://dx.doi.org/10.3390/a15090326.
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Developing a safer and more effective intersection-control system is essential given the trends of rising populations and vehicle numbers. Additionally, as vehicle communication and self-driving technologies evolve, we may create a more intelligent control system to reduce traffic accidents. We recommend deep reinforcement learning-inspired autonomous intersection management (DRLAIM) to improve traffic environment efficiency and safety. The three primary models used in this methodology are the priority assignment model, the intersection-control model learning, and safe brake control. The brake-safe control module is utilized to make sure that each vehicle travels safely, and we train the system to acquire an effective model by using reinforcement learning. We have simulated our proposed method by using a simulation of urban mobility tools. Experimental results show that our approach outperforms the traditional method.
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Li, Wenjun, Lidong Tan, and Ciyun Lin. "Modeling driver behavior in the dilemma zone based on stochastic model predictive control." PLOS ONE 16, no. 2 (February 24, 2021): e0247453. http://dx.doi.org/10.1371/journal.pone.0247453.
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Driver behavior is considered one of the most important factors in the genesis of dilemma zones and the safety of driver-vehicle-environment systems. An accurate driver behavior model can improve the traffic signal control efficiency and decrease traffic accidents in signalized intersections. This paper uses a mathematical modeling method to study driver behavior in a dilemma zone based on stochastic model predictive control (SMPC), along with considering the dynamic characteristics of human cognition and execution, aiming to provide a feasible solution for modeling driver behavior more accurately and potentially improving the understanding of driver-vehicle-environment systems in dilemma zones. This paper explores the modeling framework of driver behavior, including the perception module, decision-making module, and operation module. The perception module is proposed to stimulate the ability to perceive uncertainty and select attention in the dilemma zone. An SMPC-based driver control modeling method is proposed to stimulate decision-making behavior in the dilemma zone. The operation module is proposed to stimulate the execution ability of the driver. Finally, CarSim, the well-known vehicle dynamics analysis software package, is used to verify the proposed models of this paper. The simulation results show that the SMPC-based driver behavior model can effectively and accurately reflect the vehicle motion and dynamics under driving in the dilemma zone.
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Butsanets, Artem, Evgeniy Ol’Khovik, Vladimir Karetnikov, and Victor Senchenko. "Issues of building an intelligent water transport management system." E3S Web of Conferences 326 (2021): 00029. http://dx.doi.org/10.1051/e3sconf/202132600029.
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The current level of technology in terms of instruments, devices and software enables the construction of local intelligent transport systems that contribute to the prevention of accidents. It has become possible to build crewless and unmanned vessels. Geographical information services such as Google Maps, Mapbox, OpenStreetMap have already shown their effectiveness. The relevance of the study stems from the possibility to partially automate ship’s route planning nowadays. As navigation monitoring is carried out by means of VHF (very high frequency) - Automatic Identification System (AIS) receivers, the authors propose to collect and analyse data. However, for the construction of the geographical information system and data processing, the authors justified the proposal to build the concept, methodological foundations, mathematical models and scenarios, which will serve as the basis for the development of software for the geographical information system. They propose data types for constructing time/speed matrices for planning optimal routes based on the current navigational situation. The data collected will provide a 12-36 hour forecast and allow for the determination of vessel speeds and times, considering vessel specifications, traffic of other vessels, queue at locks, forecast of hydro- and meteorological conditions, estimates of traffic intensity and density. The service is expected to optimise the route in terms of speed and journey time to meet the transport and logistics challenge.
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Varotto, Silvia F., Haneen Farah, Tomer Toledo, Bart van Arem, and Serge P. Hoogendoorn. "Resuming Manual Control or Not?: Modeling Choices of Control Transitions in Full-Range Adaptive Cruise Control." Transportation Research Record: Journal of the Transportation Research Board 2622, no. 1 (January 2017): 38–47. http://dx.doi.org/10.3141/2622-04.
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Automated vehicles and driving assistance systems such as adaptive cruise control (ACC) are expected to reduce traffic congestion, accidents, and levels of emissions. Field operational tests have found that drivers may prefer to deactivate ACC in dense traffic flow conditions and before changing lanes. Despite the potential effects of these control transitions on traffic flow efficiency and safety, most mathematical models evaluating the impact of ACC do not adequately represent that process. This research aimed to identify the main factors influencing drivers’ choice to resume manual control. A mixed logit model that predicted the choice to deactivate the system or overrule it by pressing the gas pedal was estimated. The data set was collected in an on-road experiment in which 23 participants drove a research vehicle equipped with full-range ACC on a 35.5-km freeway in Munich, Germany, during peak hours. The results reveal that drivers were more likely to deactivate the ACC and resume manual control when approaching a slower leader, when expecting vehicles cutting in, when driving above the ACC target speed, and before exiting the freeway. Drivers were more likely to overrule the ACC system by pressing the gas pedal a few seconds after the system had been activated and when the vehicle decelerated. Everything else being equal, some drivers had higher probabilities to resume manual control. This study concludes that a novel conceptual framework linking ACC system settings, driver behavior characteristics, driver characteristics, and environmental factors is needed to model driver behavior in control transitions between ACC and manual driving.
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Huang, Jing, Yong Peng, Jikuang Yang, Dietmar Otte, and Bingyu Wang. "A study on correlation of pedestrian head injuries with physical parameters using in-depth traffic accident data and mathematical models." Accident Analysis & Prevention 119 (October 2018): 91–103. http://dx.doi.org/10.1016/j.aap.2018.07.012.
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Semchenko, N. "RESEARCH OF THE ECONOMIC FACTORS IMPACT ON THE AUTOMOBILIZATION LEVEL." Municipal economy of cities 6, no. 159 (November 27, 2020): 161–68. http://dx.doi.org/10.33042/2522-1809-2020-6-159-161-168.
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Mortality from road accidents continues to rise, amounting to 1.35 million deaths per year. It is emphasized that today injuries as a result of road accidents are the main cause of children death and young people aged 5-29 years and the three main causes of person’s death aged 5 to 44 years. Studies of road safety various aspects in different countries have shown that the world has long and steadily formed a global problem of irregular road accidents. First of all, the inverse dependence of the emergency risk on the material well-being of countries is clearly visible. The risk of death as a result of road accidents in low-income countries is three times higher than in high-income countries. The highest rates are in Africa (26.6 cases per 100,000 people) and the lowest in Europe (9.3 cases per 100,000 people). In addition, in recent years, experts are trying to link the actual accident rate in countries with the life quality of their populations. Quality of life as a concept includes not only the material level but also the satisfaction of spiritual needs, health, life expectancy, environmental conditions, moral and psychological climate, emotional comfort, etc., which ultimately determines the transport culture of the population. In this regard, it is of interest to identify links between the results of rating assessments of the people life quality in different countries and the level of these countries road safety typical. To do this, first of all it is necessary to assess the economic factors impact on the motorization level, which is insufficiently studied. The purpose is to determine the dependences of the economic factors impact, namely gross domestic product per capita and average wages, on the motorization level. The data for the study were taken from official statistical sources. The results were processed by methods of mathematical statistics and regression analysis. According to the results of the experiments, regression models were obtained for European countries; Asia and Oceania; The Middle East; Africa; North, Central America and the Caribbean; South America. The comparison of the simulated values and the initial data showed a high degree of correlation. The originality lies in the fact that the regularities of the economic factors influence on the motorization level are investigated, which makes it possible to obtain predicted values in the future. Improving the efficiency and safety of vehicles on the road network is possible based on the use of the motorization level predicted values in research. The obtained research results can be used to determine the feasibility of introducing certain measures to organize traffic.
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Chen, Wan-Hui, Chih-Yung Lin, and Ji-Liang Doong. "Effects of Interface Workload of In-Vehicle Information Systems on Driving Safety." Transportation Research Record: Journal of the Transportation Research Board 1937, no. 1 (January 2005): 73–78. http://dx.doi.org/10.1177/0361198105193700111.
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Driver distraction and lack of awareness of the driving situation are major causes of accidents in the urban areas in Taiwan; failing to obey traffic signals is the third leading accident cause. Numerous innovative in-vehicle information systems (IVIS) could be used collectively to provide drivers with a variety of information, such as messages from intersection collision warning systems (ICWS) by way of different in-vehicle interfaces. How the different IVIS interfaces influence driver workload and safety is always an important issue. This study investigates the effects of auditory ICWS messages on driver performance while the driver's visual, hearing, or mental processing attention resources (or all three) are engaged by secondary tasks. This type of engagement or distraction commonly occurs when a driver uses IVIS. The secondary tasks used to distract drivers were created by different types of mathematical questions presented with different types of display devices (e.g., voice from a speaker or numbers shown on a liquid crystal display screen or head-up display). Mixed linear models were employed to examine the factors influencing driver perception–reaction time with the consideration of repeated measures. Several factors, including several main factors and an interaction, were found to be significant. The most important finding was that the interaction between provision of ICWS information and the display format indicated that an auditory warning message could increase driver perception–reaction time while a driver was distracted by an auditory task. In addition, it was found that driver distraction due to different mental processing tasks had a significant impact on driver perception–reaction time.
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Hashimoto, Kohjiro, Tetsuyasu Yamada, Takeshi Tsuchiya, Kae Doki, Yuki Funabora, and Shinji Doki. "Detection of contributing object to driving operations based on hidden Markov model." International Journal of Advanced Robotic Systems 16, no. 5 (September 1, 2019): 172988141987679. http://dx.doi.org/10.1177/1729881419876794.
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With increase in the number of elderly people in the Japanese society, traffic accidents caused by elderly driver is considered problematic. The primary factor of the traffic accidents is a reduction in their driving cognitive performance. Therefore, a system that supports the cognitive performance of drivers can greatly contribute in preventing accidents. Recently, the development of devices for visually providing information, such as smart glasses or head up display, is in progress. These devices can provide more effective supporting information for cognitive performance. In this article, we focus on the selection problem of information to be presented for drivers to realize the cognitive support system. It has been reported that the presentation of excessive information to a driver reduces the judgment ability of the driver and makes the information less trustworthy. Thus, indiscriminate presentation of information in the vision of the driver is not an effective cognitive support. Therefore, a mechanism for determining the information to be presented to the driver based on the current driving situation is required. In this study, the object that contributes to execution of avoidance driving operation is regarded as the object that drivers must recognize and present for drivers. This object is called as contributing object. In this article, we propose a method that selects contributing objects among the appeared objects on the current driving scene. The proposed method expresses the relation between the time series change of an appeared object and avoidance operation of the driver by a mathematical model. This model can predict execution timing of avoidance driving operation and estimate contributing object based on the prediction result of driving operation. This model named as contributing model consisted of multi-hidden Markov models. Hidden Markov model is time series probabilistic model with high readability. This is because that model parameters express the probabilistic distribution and its statistics. Therefore, the characteristics of contributing model are that it enables the designer to understand the basis for the output decision. In this article, we evaluated detection accuracy of contributing object based on the proposed method, and readability of contributing model through several experiments. According to the results of these experiments, high detection accuracy of contributing object was confirmed. Moreover, it was confirmed that the basis of detected contributing object judgment can be understood from contributing model.
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Yamashita, Shigeshi, Kodo Ito, Sho Kawakami, and Truong Dinh Anh Khoa. "Optimal Education Plan of Employees Using Maintenance Model." International Journal of Mathematical, Engineering and Management Sciences 6, no. 4 (July 18, 2021): 1009–24. http://dx.doi.org/10.33889/ijmems.2021.6.4.059.
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The employee education is indispensable for companies to improve productive efficiency and product quality. In general, the employee education is divided into two types, i.e., On-job trainings and Off-job ones, and Off-job trainings are divided into two types, i.e., compulsory educations and non-compulsory ones. Compulsory educations such as safety program and compliance education, are necessary to maintain daily production without any accidents. Although all employees of a department and a division gather in a classroom annually in conventional compulsory educations, daily e-learning education complements and strengthens conventional compulsory ones today because employees forget what they learn by annual learning. In past studies, the logit model is used for modeling the influence from education receipt to its memory condition and quantitative relationship between the effect of traffic safety education and the accident-related human-errors was clarified. The effectiveness of the safety driving educational program was indicated by Structural Equation Modelling method. In this paper, an annual compulsory which is complemented and strengthened by e-learning, is discussed. The expected cost rate of education is expressed using imperfect maintenance models and optimal policies which minimizes it is considered. Although we use the exponential function which denotes the occurrence probability of accidents which are caused by forgetting lessons, the actual occurrence probability which is approximated from the actual data would be a complicated one. For solving such complex optimization problems, metaheuristic methods can be applied.
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Sebesan, Ioan, Gabriel Popa, and Marius Adrian Spiroiu. "Researches on the Behavior of the Supporting Structure of Railway Traction Vehicles under the Effect of Shock Dynamic Forces." Applied Mechanics and Materials 659 (October 2014): 237–42. http://dx.doi.org/10.4028/www.scientific.net/amm.659.237.
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During circulation the railway vehicle is subjected to the action of dynamic forces under the effect of shocks that appear in the driving system caused by stick slip phenomenon, dynamic forces arising from the rolling process when the wheelset is passing over accidental vertical unevenness of the track and also longitudinal dynamic forces occurring in the case of buffering, respectively those caused by frontal impact (the crash forces). The present paper presents the mechanical and mathematical models which are underlying the evaluation of the magnitude of these forces as well as their effects on the resistance of supporting structure of the vehicle and on traffic safety.
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KOZHEVNIKOV, M. "EMERGENCE PROCESS SIMULATION OF DESTRUCTIVE EVENTSON THE TERRITORIES OF THE REGION WITH HIGH ENGAGEMENT LEVEL OF FIRE AND RESCUE UNITS." Fire and Emergencies: prevention, elimination 3 (2021): 89–97. http://dx.doi.org/10.25257/fe.2021.3.89-97.
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Purpose. The main objectives of the article include the analysis of fire and rescue units activities and emergence process simulation of destructive events on the territories of the region with a high level of workload. The main principle of organizational design is to respond timely to any destructive event which has happened in the settlement, when it is sufficient to eliminate this event with a set of means and forces. In this regard, it is necessary to analyze the operational situation, simulate the conditions in which fire and rescue units operate, and then take into account the obtained results when making recommendations for fire and rescue units reorganization of towns and regions on the proposed territories. Methods. To achieve the objectives stated above applying mathematical and statistical models, the emergence process of events including fires, traffic accidents, emergencies has been described. Findings. The detailed analysis of the current operational situation on the studied territories with high engagement level of fire and rescue units has been carried out. Applying probabilistic-statistical modeling, it has been found that the emergence process of destructive events comply with Poisson’s distribution with the corresponding parameter. Research application field. The obtained results will make it possible to develop recommendations on reorganizing and improving fire protection of towns on the studied territories. Conclusions. In future, it is of interest to simulate the time characteristics of fire and rescue units’ operation in the region: to build an appropriate mathematical model, to study the employment time and arrival time of fire and rescue unit at the scene.
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Afonin, M., T. Postranskyy, and O. Bondarchuk. "DETERMINATION MODEL OF MAXIMUM DRIVING DURATION DURING DANGEROUS GOODS TRANSPORTATION." Municipal economy of cities 6, no. 166 (November 30, 2021): 184–89. http://dx.doi.org/10.33042/2522-1809-2021-6-166-184-189.
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The increase and compaction of large cities population of in Ukraine encourage the use of more resources for the construction of various settlements, as well as for the maintenance and operation of other facilities. Accordingly, the volume of cargo transportation associated with the creation and maintenance of these facilities is increasing. All new tasks related to the safety of dangerous cargo transportation are being created. The article considers the topical issue of the influence of human factors on traffic safety. It is known that in the process of road freight there are interconnected elements that form the system "driver - car - road - environment". If the technical parameters of cars and roads are known and can be predicted, then the variable parameters of the environment and the driver are further the least studied elements of this system. When transporting dangerous goods, the cost of driver error is extremely high, as accidents that can occur involving such vehicles have serious consequences. The following studies were used in the research: methods of field research to establish the values of traffic flow intensities on highways; in-house research methods to determine the value of road capacity; electrophysiological methods to determine changes in the functional state of drivers; methods of system analysis for processing the results of research and their interpretation; methods of statistical and mathematical analysis for the formation of models for determining the maximum allowable driving time of drivers who carry dangerous goods. Experimental studies of driver's regulatory systems activity index change, considering different ages and socionic groups were carried out. This task also included study of road condition complexity impact on the driver during second class dangerous goods transportation in the settlements or out of them.
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Liao, Yiqi, Pengpeng Shangguan, Yiran Peng, and Taorong Qiu. "A New Feature Analysis Approach to Selecting Channels of EEG for Fatigue Driving." Computational and Mathematical Methods in Medicine 2022 (October 4, 2022): 1–13. http://dx.doi.org/10.1155/2022/4640426.
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Fatigued driving is a significant contributor to traffic accidents. There are some issues with common EEG data of 32 channels, 64 channels, and 128 channels, such as difficult acquisition, high data redundancy, and difficult practical application. A new channel selection method called ReliefF_SFS is proposed to address the problem of how to reduce the number of channels while maintaining classification accuracy. It combines the ReliefF algorithm and the sequential forward selection (SFS) algorithm. When only T6, O1, Oz, T4, P3, and FC3 are used, the classification accuracy under Theta_Std+FE combined with ReliefF_SFS achieves 99.45%. The strategy suggested in this paper not only ensures the recognition accuracy but also reduces the number of channels when compared to other models based on the same data set.