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1
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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Song, Minglei, Rongrong Li, and Binghua Wu. "A novel prediction model of traffic accidents based on big data." International Journal of Modeling, Simulation, and Scientific Computing 10, no. 04 (August 2019): 1950022. http://dx.doi.org/10.1142/s1793962319500223.
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The occurrence of traffic accidents is regular in probability distribution. Using big data mining method to predict traffic accidents is conducive to taking measures to prevent or reduce traffic accidents in advance. In recent years, prediction methods of traffic accidents used by researchers have some problems, such as low calculation accuracy. Therefore, a prediction model of traffic accidents based on joint probability density feature extraction of big data is proposed in this paper. First, a function of big data joint probability distribution for traffic accidents is established. Second, establishing big data distributed database model of traffic accidents with the statistical analysis method in order to mine the association rules characteristic quantity reflecting the law of traffic accidents, and then extracting the joint probability density feature of big data for traffic accident probability distribution. According to the result of feature extraction, adaptive functional and directivity are predicted, and then the regularity prediction of traffic accidents is realized based on the result of association directional clustering, so as to optimize the design of the prediction model of traffic accidents based on big data. Simulation results show that in predicting traffic accidents, the model in this paper has advantages of relatively high accuracy, relatively good confidence and stable prediction result.
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Matcha, Bhargav Naidu, Satesh Narayana Namasivayam, Mohammad Hosseini Fouladi, K. C. Ng, Sivakumar Sivanesan, and Se Yong Eh Noum. "Simulation Strategies for Mixed Traffic Conditions: A Review of Car-Following Models and Simulation Frameworks." Journal of Engineering 2020 (January 25, 2020): 1–22. http://dx.doi.org/10.1155/2020/8231930.
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The area of traffic flow modelling and analysis that bridges civil engineering, computer science, and mathematics has gained significant momentum in the urban areas due to increasing vehicular population causing traffic congestion and accidents. Notably, the existence of mixed traffic conditions has been proven to be a significant contributor to road accidents and congestion. The interaction of vehicles takes place in both lateral and longitudinal directions, giving rise to a two-dimensional (2D) traffic behaviour. This behaviour contradicts with the traditional car-following (CF) or one-dimensional (1D) lane-based traffic flow. Existing one-dimensional CF models did the inclusion of lane changing and overtaking behaviour of the mixed traffic stream with specific alterations. However, these parameters cannot describe the continuous lateral manoeuvre of mixed traffic flow. This review focuses on all the significant contributions made by 2D models in evaluating the lateral and longitudinal vehicle behaviour simultaneously. The accommodation of vehicle heterogeneity into the car-following models (homogeneous traffic models) is discussed in detail, along with their shortcomings and research gaps. Also, the review of commercially existing microscopic traffic simulation frameworks built to evaluate real-world traffic scenario are presented. This review identified various vehicle parameters adopted by existing CF models and whether the current 2D traffic models developed from CF models effectively captured the vehicle behaviour in mixed traffic conditions. Findings of this study are outlined at the end.
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H, Harshita Chitla. "Urban Traffic Simulators." International Journal of Informatics and Communication Technology (IJ-ICT) 5, no. 3 (December 1, 2016): 124. http://dx.doi.org/10.11591/ijict.v5i3.pp124-128.
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Computer traffic simulation is a widely used technique in modeling, coming up with and development of traffic networks and systems. It contains a various applications, like traffic forecasting, vehicle navigation devices and so on. This paper discusses about the various types of traffic simulators. Another drawback is that the factors like accidents, public events, and road closures. In addition, we are introducing algorithmic concepts, quantifiable metrics and data structural approaches that might be applied to the simulation systems.
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Félez, Jesus, Joaquin Maroto, Gregorio Romero, and Jose M. Cabanellas. "A Full Driving Simulator of Urban Traffic including Traffic Accidents." SIMULATION 83, no. 5 (May 2007): 415–31. http://dx.doi.org/10.1177/0037549707083109.
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Lee, Jae-Kang, Yong Huh, and Jisoo Park. "Geospatial Simulation System of Mountain Area Black Ice Accidents." Applied Sciences 12, no. 11 (June 3, 2022): 5709. http://dx.doi.org/10.3390/app12115709.
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As the development of mountain areas has recently increased in Korea, existing roads are being renovated, and new highways are being constructed, which increases driving speeds in mountainous areas. However, the mountainous region in northeastern Korea is more likely to form black ice due to higher humidity, frequent fog, and hillshade, depending on the terrain, which can cause serious traffic pileups. In this study, therefore, we present a method to build a more effective black ice prediction and warning system by linking spatial information to the existing road management system that estimates the road surface temperature based on real-time weather information. The spatial information enabled a prediction to be made of the risk level of black ice formation for each time zone by simulating changes in the shadow area based on precise 3D terrain information. Moreover, this information also presented slope and curvature information of the road to estimate the risk zone. The spatial information was integrated with weather data to predict road surface temperature. The proposed system was tested in two mountainous regions with weather data accumulated from 2017 to 2018. As a result, the proposed system anticipated 71% of traffic accidents caused by black ice during the testing period. The results show that the system can contribute significantly to preventing black-ice-related traffic accidents by providing reasonable predictions.
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Li, Xingli, Hua Kuang, Yanhong Fan, and Guoxin Zhang. "Traffic accidents on a single-lane road with multi-slowdown sections." International Journal of Modern Physics C 25, no. 09 (August 26, 2014): 1450036. http://dx.doi.org/10.1142/s0129183114500363.
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In this paper, an extended cellular automaton model is proposed to simulate the complex characteristics of traffic flow and the probability of the occurrence of traffic accidents by considering the modified conditions for determining whether traffic accidents happen and the effect of multi-slowdown sections on a highway. The simulation results show that the multi-slowdown sections can lead to multiphase coexistences (i.e. free flow phase, congestion phase and saturation phase) in traffic system. The fundamental diagram shows that the number of slowdown section does not influence the mean velocity and the mean flow under the periodic boundary condition, but the existence of slowdown sections can effectively reduce the occurrence of traffic accident. In particular, it is found that the probability of car accidents to occur is the largest at the joint of the normal-speed section and slowdown section, and the underlying mechanism is analyzed. In addition, to design the appropriate limited speed and reduce the differences between the normal speed and limited speed will alleviate traffic congestion and reduce the occurrence of traffic accidents obviously.
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Zhang, Zhihao, Wenzhong Yang, and Silamu Wushour. "Traffic Accident Prediction Based on LSTM-GBRT Model." Journal of Control Science and Engineering 2020 (March 5, 2020): 1–10. http://dx.doi.org/10.1155/2020/4206919.
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Road traffic accidents are a concrete manifestation of road traffic safety levels. The current traffic accident prediction has a problem of low accuracy. In order to provide traffic management departments with more accurate forecast data, it can be applied in the traffic management system to help make scientific decisions. This paper establishes a traffic accident prediction model based on LSTM-GBRT (long short-term memory, gradient boosted regression trees) and predicts traffic accident safety level indicators by training traffic accident-related data. Compared with various regression models and neural network models, the experimental results show that the LSTM-GBRT model has a good fitting effect and robustness. The LSTM-GBRT model can accurately predict the safety level of traffic accidents, so that the traffic management department can better grasp the situation of traffic safety levels.
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Dong, Peng, Xifu Wang, Lifen Yun, and Hongqiang Fan. "Research on the characteristics of mixed traffic flow based on an improved bicycle model." SIMULATION 94, no. 5 (October 30, 2017): 451–62. http://dx.doi.org/10.1177/0037549717736947.
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Mixed traffic flow is a main feature of urban traffic in developing countries. Mixed bicycle flow includes human-powered and electric-powered bicycles and plays an important role in this mixed traffic flow. In mixed bicycle flow, cyclist behavior is flexible and variable. Cyclists move arbitrarily in the road and may influence the vehicle flow at intersections. Therefore, we first propose an improved bicycle model that can reproduce the main features of cyclist behavior, such as overtaking and self-protection. Then a simulation model based on the improved bicycle model is proposed to research the characteristics of mixed traffic flow in intersections. The conflict avoidance rules are then applied in the simulation model to eliminate traffic accidents. The simulation results indicate that the improved bicycle model is practical and that the density–velocity diagram of bicycle flow is similar to real traffic data. The existence of bicycle flow decreases vehicle velocity and worsens traffic flow in mixed traffic flow. However, the influence of bicycle flow might disappear at a particular vehicle density.
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Luin, Blaž, and Stojan Petelin. "COUPLING MODELS OF ROAD TUNNEL TRAFFIC, VENTILATION AND EVACUATION." Transport 35, no. 3 (February 20, 2020): 336–46. http://dx.doi.org/10.3846/transport.2020.12079.
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As road tunnel accidents can result in numerous fatalities and injuries, attention must be paid to accident prevention and management. To address this issue, use of integrated tunnel model for system evaluation and training of road tunnel operators on computer simulator is presented. A unified tunnel model, including traffic, meteorological conditions, ventilation and evacuation that is presented. An overview of simulation models, simulator architecture and challenges during the development are discussed. The integrated tunnel model is used as a core of a simulation system that is capable of reproducing tunnel accidents in real time and it interfaces with Supervisory Control And Data Acquisition (SCADA) interfaces used in real tunnel control centres. It enables operators to acquire experience they could otherwise get only during major accidents or costly exercises. It also provides the possibility for evaluation of tunnel control algorithms and Human Machine Interfaces (HMIs) for efficient operation of all safety systems during upgrades and maintenance. Finally, application of the model for accident analysis and optimization of emergency ventilation control is presented where it was used to identify cause of emergency ventilation malfunction and design fault.
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Lu, Yiding, Zhan Zhang, Xinyi Fang, Linjie Gao, and Linjun Lu. "Resilience of Urban Road Network to Malignant Traffic Accidents." Journal of Advanced Transportation 2022 (May 6, 2022): 1–13. http://dx.doi.org/10.1155/2022/3682472.
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Malignant traffic accidents are typical devastating events suffered by the urban road network. They cause severe functional loss when loading on the urban road network is high, exerting a significant impact on the operation of the city. The resilience of a road network refers to its ability to maintain a certain level of capacity and service when disturbed by external factors and to recover after a disturbance event, which is a crucial factor in the construction of transportation infrastructure systems. A comprehensive understanding of the adverse effects of malignant traffic accidents on the urban road network is imperative, and resilience is a concept employed to systematically explain this. This study investigates the impact of malignant traffic accidents on the resilience of the urban road network. A simulation is carried out focusing on an ideal urban road network, describing the temporal and spatial distribution of the average speed of road sections in the network. Inspired by the simulation experiment results, the ideal resilience curve is summarized, and the theory of resilience concept portrayal is innovatively developed into “6R” (redundancy, reduction, robustness, recovery, reinforcement, and rapidity). Combining the topological and “6R” resilience attributes of the urban road network, the urban road network resilience evaluation system is constructed, which yields an all-round and full-process evaluation for the urban road network with malignant traffic accidents. Results show that under malignant traffic accidents, the resilience of high-class surface roads, such as primary roads, is the poorest, suggesting that more attention and resources must be devoted to high-class surface roads. This study on the urban road network deepens the understanding and portrayal of its resilience and proposes an evaluation method to analyze its performance under disruption events.
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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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Marzoug, R., B. Castillo Téllez, M. Castillo Téllez, G. A. Mejía Pérez, A. Bassam, and O. Oubram. "Optimization of traffic intersection using connected vehicles." International Journal of Modern Physics C 30, no. 06 (June 2019): 1950042. http://dx.doi.org/10.1142/s0129183119500426.
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In this paper, we proposed a model based on the connected vehicles to control the traffic flow at the intersection. To evaluate this model, we studied its impact on the flux and the probability of accidents at the intersection. On the one hand, simulation results showed that the increase in the number of connected vehicles decreases the congestion coefficient and enhances the traffic situation in the system. On the other hand, connected vehicles reduce the probability of accidents at the intersection. In this way, the vehicle intersection (central controller) communication can decrease the congestion and enhance road safety, especially in the intermediate and high traffic conditions.
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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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Yuhara, Naohiro, and Jun Tajima. "Multi-driver agent-based traffic simulation systems for evaluating the effects of advanced driver assistance systems on road traffic accidents." Cognition, Technology & Work 8, no. 4 (September 6, 2006): 283–300. http://dx.doi.org/10.1007/s10111-006-0045-9.
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Yang, Xin, Juncheng Chen, Mantun Yan, Zhao He, Ziyan Qin, and Jiandong Zhao. "Regional Boundary Control of Traffic Network Based on MFD and FR-PID." Journal of Advanced Transportation 2021 (September 3, 2021): 1–12. http://dx.doi.org/10.1155/2021/9730813.
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In recent years, urban traffic congestion has become more serious and the capacity of roads has declined, resulting in frequent traffic accidents. In order to effectively alleviate the traffic congestion of the regional road network, aiming at the problem of lack of accurate OD data of the road network, a regional boundary control method of the traffic network based on fuzzy RBF neural network PID (FR-PID) is proposed by combining the theory of macroscopic fundamental diagram (MFD). Firstly, based on the traffic survey, the simulation model of the study area is built, and the basic data such as the traffic flow and the time occupation rate of each road section are obtained. Secondly, the simulation data are used to test the existence of MFD in the road network, and the controlled area is defined. Then, the vehicle change model of the road network area is established. Then, in view of the problem of poor adaptive ability of traditional PID control, the FR-PID control structure is designed. Finally, an example is verified by VISSIM software. In the simulation, different control methods are used for comparison and verification, and the simulation results are analyzed. The results show that the control effect of the proposed method is better than that of the traditional method, and the regional average accumulative vehicle number, regional average completed volume, regional accumulative delays, and total vehicle travel time are optimized by 28.21%, 41.19%, 27.06%, and 32.73%, respectively. The research results can provide reference for the management of urban congestion, thereby reducing the number of traffic accidents and improving urban traffic safety.
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Miyamoto, Kodai, Taketo Kamasaka, Makoto Sakamoto, and Tsunehiro Yoshinaga. "Basic Study on Expressway Congestion Mitigation using Cellular Automata." International Journal of Recent Technology and Engineering (IJRTE) 10, no. 3 (September 30, 2021): 164–69. http://dx.doi.org/10.35940/ijrte.c6462.0910321.
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Traffic congestion has become a serious social problem in Japan. In particular, traffic congestion causes enormous time and economic losses on expressways, which are intended to facilitate smooth traffic flow. It also causes environmental problems and a decrease in logistics efficiency, so efforts to eliminate or reduce traffic congestion are essential. The elimination and mitigation of traffic congestion on highways is a factor in reducing traffic accidents and fatalities. In recent years, with the improvement of computing capabilities, research on traffic congestion reduction and mitigation has been conducted using traffic simulation. Traffic simulation allows us to reproduce and evaluate traffic phenomena that occur on roads on a computer. The Kakuto Tunnel is located on the border between Ebino City in Miyazaki Prefecture and Hitoyoshi City in Kumamoto Prefecture. The Kakuto Tunnel has insufficient traffic capacity and is frequently congested on holidays. In this study, we created a traffic simulator assuming the Kakuto Tunnel. In the simulation, we examined the effectiveness of increasing the number of lanes as a method of reducing traffic congestion.
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Yücel, Ayhan, Ali Atahan, Turan Arslan, and Umur Sevim. "Traffic Safety at Median Ditches: Steel vs. Concrete Barrier Performance Comparison Using Computer Simulation." Safety 4, no. 4 (November 1, 2018): 50. http://dx.doi.org/10.3390/safety4040050.
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In Turkey, concrete V-shaped ditches are formed at the median section of divided highways to provide drainage. Recent accidents show that these ditches actually present safety risks to vehicles entering the medians. Vehicles either cross over the ditch, roll over, or become trapped in the ditch, depending upon the mass, size, speed, and angle of the entering vehicle. To overcome this safety risk and reduce the severity of these accidents, longitudinal barriers are installed along these ditches. Currently, in Turkey, steel barriers are extensively used to improve traffic safety at median ditches. In this paper, the crash performances of steel and concrete barriers used at medians with ditches are compared. A model of a standard steel EDSP-1.33 barrier and a model of a newly developed concrete C470 barrier were constructed, and impact simulations were performed for when they are installed at a ditch slope break point. A nonlinear finite element program, LS-DYNA, was used for the analysis. A 13,000 kg bus model was used to impact both barriers in accordance with European standard requirements for crash tests. Simulation results show that when the steel EDSP-1.33 barrier is used, the bus has the potential for excessive penetration of the ditch, with significant barrier deformation. Moreover, the barrier damage is extensive, resulting in increased maintenance costs. On the other hand, the concrete C470 barrier successfully contains and redirects the 13,000 kg bus impact, with minimal barrier deformation and safety risk. Even though the concrete barrier slides toward the inside of the ditch, the bus does not enter the ditch area and exits the barrier in a stable manner. Therefore, to increase traffic safety at ditches located at the median section of divided highways in Turkey, utilization of the newly developed concrete barrier C470 is recommended.
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Fonseca, Daniel J., Gary P. Moynihan, Jordan Johnston, and Jordan Jennings. "A Simulation Tool for Hurricane Evacuation Planning." Modelling and Simulation in Engineering 2009 (2009): 1–10. http://dx.doi.org/10.1155/2009/729570.
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Atlantic hurricanes and severe tropical storms are a serious threat for the communities in the Gulf of Mexico region. Such storms are violent and destructive. In response to these dangers, coastal evacuation may be ordered. This paper describes the development of a simulation model to analyze the movement of vehicles through I-65, a major US Interstate highway that runs north off the coastal City of Mobile, Alabama, towards the State of Tennessee, during a massive evacuation originated by a disastrous event such a hurricane. The constructed simulation platform consists of a primary and two secondary models. The primary model is based on the entry of vehicles from the 20 on-ramps to I-65. The two secondary models assist the primary model with related traffic events such as car breakdowns and accidents, traffic control measures, interarrival signaling, and unforeseen emergency incidents, among others. Statistical testing was performed on the data generated by the simulation model to indentify variation in relevant traffic variables affecting the timely flow of vehicles travelling north. The performed statistical analysis focused on the closing of alternative on-ramps throughout the Interstate.
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Marzoug, R., N. Lakouari, O. Oubram, H. Ez-Zahraouy, A. Khallouk, M. Limón-Mendoza, and J. G. Vera-Dimas. "Impact of traffic lights on car accidents at intersections." International Journal of Modern Physics C 29, no. 12 (December 2018): 1850121. http://dx.doi.org/10.1142/s0129183118501218.
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Using the cellular automata Nagel–Schreckenberg (NaSch) model, we numerically study the impact of traffic lights on the probability of car accidents ([Formula: see text]) at the intersection of two roads. It is found that, the probability [Formula: see text] is more stable with variation of the green light ([Formula: see text]) when the symmetric lights are adopted. Moreover, simulation results show the existence of a critical time [Formula: see text], below which ([Formula: see text]) [Formula: see text] increases as the injection rate ([Formula: see text]) increases, however, above which ([Formula: see text]) the growing of [Formula: see text] has for effect the decrease of [Formula: see text]. Furthermore, the decrease of [Formula: see text] is almost always accompanied by a loss of the flux, especially with asymmetrical lights. To overcome this problem, we proposed a strategy that can greatly increase the flux and keep the probability [Formula: see text] as small as possible, especially for the low and high injection rates.
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Rizwan, Ali, Dimitrios A. Karras, Mohammed Dighriri, Jitendra Kumar, Ekta Dixit, Asadullah Jalali, and Amena Mahmoud. "Simulation of IoT-based Vehicular Ad Hoc Networks (VANETs) for Smart Traffic Management Systems." Wireless Communications and Mobile Computing 2022 (May 24, 2022): 1–11. http://dx.doi.org/10.1155/2022/3378558.
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Nowadays, traffic congestion and increasing road accidents have become a major concern for both developed and developing countries. To overcome this challenge, an internet of things- (IoT-) based Vehicular Ad Hoc Network (VANET) system is proposed in which vehicles interact with other vehicles and infrastructure. These self-organized ad hoc vehicle networks not only boost traffic safety but also enhances the efficiency of traffic management systems. The VANET systems are beneficial in busy locations, where improved data dissemination protocols are used to categorize a vehicle’s transmission. However, the performance of these VANETs is also hampered by network splits and insufficient connections. Under these situations, the proposed simulation model reduces broadcast storms by minimizing redundancies, which is equally beneficial for both rural and urban settings. The suggested Next Forwarder Vehicle (NFV) protocol is based on three factors: position, distance, and orientation. Moreover, the DDP4V technique is used to analyse each of these features. Results indicate that DDP4V is compatible with 96% of all traffic scenarios and simulation durations. It can transport data packets 60% faster due to its broadcast suppression capabilities. Also, in comparison to AID and DBRS, DDP4V has fewer dispersed packets, which results into reduced retransmissions. For 200 automobiles/km2, all these techniques accomplish 35–40% of the needed cars. However, the coverage also faces some restrictions since data packets only reach vehicles on the same side as the originating vehicle. Similarly, DDP4V delivers 90% coverage for 400 vehicles/km2, which is 30% greater than prior techniques. It is observed that the proposed protocol reduces broadcast storms by employing a waggon wheel to choose the next forwarding vehicle. In high-traffic areas, it outperforms standard techniques. Similarly, it employs a patchwork of vehicles outside of the impacted region to convey data. The industrial IoT-based VANETs provide an effective tool to monitor and control traffic besides reducing the number of traffic accidents.
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Lu, Xingyu, Li Fei, Huibing Zhu, Wangjun Cheng, and Zijie Wang. "Modeling traffic flow in work zone sections considering the effect of traffic lights." International Journal of Modern Physics C 32, no. 09 (May 7, 2021): 2150113. http://dx.doi.org/10.1142/s0129183121501138.
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Based on the two-lane highway traffic model with a work zone presented previously, a new traffic model with a work zone under the control of traffic lights is proposed. The length of the waiting area for vehicles before traffic lights is recommended cautiously after numerical simulation. The relationship between the vehicles’ queuing time and the cycle of traffic lights is studied, and the cycle time of traffic lights is obtained also considering people’s endurance to the red light. It is found that the traffic lights are effective to ease the traffic congestion in the work zone when the density is medium, and help to eliminate the inducement of traffic accidents. On the other hand, the simulation results show that traffic lights are not needed in the work zone when the traffic density is small. It indicates that the traffic flow in the work zone area can be optimized by using appropriate traffic management when the traffic density varies.
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Luo, Qiang, Xinqiang Chen, Jie Yuan, Xiaodong Zang, Junheng Yang, and Jing Chen. "Study and Simulation Analysis of Vehicle Rear-End Collision Model considering Driver Types." Journal of Advanced Transportation 2020 (January 23, 2020): 1–11. http://dx.doi.org/10.1155/2020/7878656.
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The reasonable distance between adjacent cars is very crucial for roadway traffic safety. For different types of drivers or different driving environments, the required safety distance is different. However, most of the existing rear-end collision models do not fully consider the subjective factor such as the driver. Firstly, the factors affecting driving drivers’ characteristics, such as driver age, gender, and driving experience are analyzed. Then, on the basis of this, drivers are classified according to reaction time. Secondly, three main factors affecting driving safety are analyzed by using fuzzy theory, and the new calculation method of the reaction time is obtained. Finally, the improved car-following safety model is established based on different reaction time. The experimental results have shown that our proposed model obtained more accurate vehicle safety distance with varied traffic kinematic conditions (i.e., different traffic states, varied driver types, etc.). The findings can help traffic regulation departments issue early warnings to avoid potential traffic accidents on roads.
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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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Wang, Xiliang, Yujing Tang, Qingyu Qi, Guomei Wang, and Bowen Bi. "Optimization of Emergency Transportation Organization of Holiday Tourism Traffic." Wireless Communications and Mobile Computing 2022 (January 7, 2022): 1–8. http://dx.doi.org/10.1155/2022/2264876.
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The purpose of the optimization of holiday traffic emergency traffic organization is to solve the problem of serious traffic jams in holiday scenic spots. Based on the prediction of traffic volume and traffic mode division in the future years of the scenic spot, the traffic accident route is analyzed to provide theoretical support for the emergency traffic organization and planning of the scenic spot. This article takes the Shijiazhuang Jinta Bay scenic area as the research object, based on the traffic volume of the Jinta Bay tourist scenic area from 2009 to 2016, analyzes the traffic environment of the scenic area, predicts the traffic demand, and builds a one-way traffic organization double-layer optimization model. The simulated annealing algorithm is used to solve the model, an emergency transportation organization optimization plan is formulated, and the feasibility of the plan is verified through VISSIM simulation. The results of the study show that the one-way traffic organization method reduces the average vehicle delay by 32.2% and the average queue length by 14.5%. The one-way traffic organization based on branch diversion can more effectively solve the main road jamming and congestion caused by traffic accidents, prevent the occurrence of secondary accidents, and reduce the economic losses of scenic area managers. At the same time, the purpose of ensuring the tourist quality of tourists and the economic interests of scenic spot management departments is ensured.
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Chuprov, Sergey, Ilia Viksnin, Iuliia Kim, Nikita Tursukov, and Gleb Nedosekin. "Empirical Study on Discrete Modeling of Urban Intersection Management System." International Journal of Embedded and Real-Time Communication Systems 11, no. 2 (April 2020): 16–38. http://dx.doi.org/10.4018/ijertcs.2020040102.
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With the growing number of cars in the world, there are corresponding problems that society needs to solve. In metropolises, intersections are generators of traffic jams and traffic accidents. The introduction of unmanned autonomous vehicles is one of the solutions to increase safety on the road. To avoid traffic jams, it is necessary to optimize road traffic. This article proposes a model of the intersection management system. The system aims to organize a conflict-free, safe, and optimal traversal of AVs within the framework of the intelligent transport system of a smart city. The model assumes that at each intersection there are objects of transport infrastructure responsible for building routes at the intersection. To assess the feasibility of the presented model, the authors developed a custom software simulator of a network of urban intersections and conducted experiments. Based on simulation experiments, the use of the developed model can significantly reduce the time spent by unmanned vehicles to overcome the intersection compared to traffic lights.
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Avramović, Zoran, Milorad Cvijan, and Emir Smailović. "The reliability estimate of throw pedestrian using traditional and computer methods." Tehnika 75, no. 4 (2020): 504–12. http://dx.doi.org/10.5937/tehnika2004504a.
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The development of information technology has created conditions for development and implementation of software for the simulation of traffic accidents. Among large number software tools which are being used in Europe, software PC Crash stand out. In this paper comparative analysis of distance throw of pedestrian using the traditional and contemporary methods was realized. The distance throw of pedestrian using the software PC Crash, depending on the height and weight of pedestrian is showed. By using of statistical methods difference between traditional and contemporary methods was researched.
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Hong, Seok-Bum, Byung-Woong Lee, Chang-Hoon Kim, and Hong-Sik Yun. "System Dynamics Modeling for Estimating the Locations of Road Icing Using GIS." Applied Sciences 11, no. 18 (September 14, 2021): 8537. http://dx.doi.org/10.3390/app11188537.
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Road icing can cause large traffic accidents on highways because, unlike snowy roads, its location is difficult to identify and it can occur rapidly, even during rainy weather. In this study, the amount and location of road icing were modeled and simulated over time based on the system dynamics theory. The simulation is expressed on the geographic information system (GIS) and facilitates advance detection of the location and amount of road icing that occurs unexpectedly unlike previous studies. Modeling was designed to process spatial and meteorological data after combining them. The spatial data used for modeling were Hillshade, Water System, Bridge, and Road (Highway). Air temperature, cloudiness, vapor pressure, wind speed, and precipitation were used as meteorological data. The amount of road icing was estimated by scientifically designing the parameters related to its occurrence between spatial and meteorological data. Based on this, the amount of road icing by location was simulated per 1m2 using the GIS. The simulation results showed that the amount of road icing that began to increase from AM 08:00 reached its peak (an average of 213.62 g/m2) at noon and then slowly decreased. Additionally, when simulated with GIS, the sum amount of road icing between AM 12:00 and PM 13:00 was a maximum of 1707.292 (g/14 h) and a minimum of 360.082 (g/14 h) for each location. Hypothesis testing was conducted on whether road icing significantly occurs at actual points vulnerable to traffic accidents. Based on the results, the average significance level was calculated to be less than 0.05. Therefore, the alternative hypothesis that the model can estimate road icing in vulnerable areas was adopted. The verified simulation can be useful data to government agencies (e.g., road traffic authority) in their programs to prevent traffic accidents caused by road icing.
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Allen, R. Wade, Henry T. Szostak, and Theodore J. Rosenthal. "Modeling Driver/Vehicle Performance in Emergency Maneuvers." Proceedings of the Human Factors Society Annual Meeting 32, no. 10 (October 1988): 573–77. http://dx.doi.org/10.1518/107118188786762711.
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The combined performance of the driver and vehicle determine whether accidents result from traffic conflicts, road hazards, etc. This paper describes the driver behavior and hazard scenario aspects of a computer simulation which models both vehicle dynamics and driver steering and braking behavior. The technical aspects of the simulation have previously been published. The issue of how much the driver and vehicle contribute to accident involvement is addressed, and antilock brake evaluation is used as an example.
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Yang, Choong Heon, Hoe Kyoung Kim, Jin Guk Kim, and Soullam Kim. "Impact of an automated road debris removal system on traffic flow using VISSIM." SIMULATION 96, no. 9 (June 19, 2020): 725–35. http://dx.doi.org/10.1177/0037549720931159.
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This study introduces a state-of-the-art road debris removal system (i.e., automated road debris removal system (ROBOS)) and analyzes its impact on traffic flow using the microscopic simulation model, VISSIM. Robust simulation scenarios were established, and the major parameters of individual scenarios were also included based on extensive interviews with road workers. The performances of road workers and the ROBOS in regard to road debris removal were investigated in terms of four measures of effectiveness. These included queue, density, percentage delay, and number of vehicle stops. To mimic the major arterial roadways in South Korea, two-lane, three-lane, and four-lane roads were considered for implementing the road debris removal process. The simulation results as well as the statistical analysis revealed that the ROBOS outperforms the direct removal by road workers in all aspects. Thus, the ROBOS can remove the debris more safely and efficiently. The findings of this research can improve institutional operational guidelines for the ROBOS by providing an appropriate range for its parameters. This can result in enhancing traffic safety and efficiency. Notwithstanding the simulation results, the more unexpected cases, such as the driver carelessness during removal work, should be reflected in future research to thoroughly prevent the potential risk of accidents as well as maintaining smooth traffic flow.
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Feng, Tianjun, and Tan Gao. "Risk analysis of road traffic accidents based on improved data mining method." International Journal of Simulation and Process Modelling 18, no. 4 (2022): 253. http://dx.doi.org/10.1504/ijspm.2022.10053299.
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Feng, Tianjun, and Tan Gao. "Risk analysis of road traffic accidents based on improved data mining method." International Journal of Simulation and Process Modelling 18, no. 4 (2022): 253. http://dx.doi.org/10.1504/ijspm.2022.128271.
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Abdunazarov, Jamshid, Miroslava Mikusova, and Kyandoghere Kyamakya. "The System Dynamic and Compram Methodologies for Modelling, Simulation and Forecasting of Road Safety of Uzbekistan." Journal of KONBiN 51, no. 3 (October 1, 2021): 49–63. http://dx.doi.org/10.2478/jok-2021-0033.
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Abstract In Uzbekistan, about 2,000 people die every year as a result of a traffic accident. At the same time, according to the Pulitzer Centre on Crisis Reporting, the Republic has the lowest rate in road mortality among the countries in the Central Asian region - for every 100,000 people, it is 11.32 people. Losses from road accidents in Uzbekistan equivalent up to 2.8% of GDP that is also one of the lowest indicators. But according to traffic safety experts, the losses from accidents are greater than reported data. Nowadays there are a lot of methods to analyse and ensure road safety and traffic management on the roads. The authors believe that road safety is a complex societal problem not only in Uzbekistan but all over the world. One of these methods is System Dynamic (SD) and COMplex PRoblem hAndling Methodology (COMPRAM). In this work, the Vensim PLE SD software tool (it is one SD tool amongst many others) has been used to perform the SD modelling of the case study at hand. In the methods of system dynamics, a computer model is created using a graphical technique for constructing flow diagrams and causal relationships of the system under study and then simulated on a computer. COMPRAM allows us to figure out the way to handle complex societal problems while involving a System Dynamics (SD) simulation option. There are similarities between COMPRAM and the traditional way of analysing road safety. In traditional ways, each element or factor is studied as a separate phenomenon. These indicators are studied in the stages of COMPRAM. This article has been studied a different aspect of how road accidents happen. The developed a comparison (according to six criteria) of the different modelling paradigms which have been historically used to assess road safety. Also, the authors made a comparison of the COMPRAM methodology with the traditional road safety assessment approach to highlight similarities and differences.
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Terentyev, Vyacheslav, Konstantin Andreev, Nikolay Anikin, Natalya Morozova, and Alexander Shemyakin. "The use of simulation when designing road junctions." E3S Web of Conferences 164 (2020): 03042. http://dx.doi.org/10.1051/e3sconf/202016403042.
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The high level of motorization in most countries of the world is the reason for the increase in the number of car accidents. Currently, it is understood that a further increase in the number of cars without significant changes in the transport infrastructure will only aggravate the already difficult situation on roads. The article addresses the issues of road traffic injuries and statistical information on road accidents. The analysis of the work of leading transport engineers presents the results of studies on the use of computer modeling tools for designing road conditions at various levels. From the presented analysis, it is possible to conclude that the most suitable tool for assessing the safety of road junctions is the PTV VISSIM software package, which also allows to export vehicle trajectories to SSAM software. In the framework of the analytic survey of the intersection safety, based on the analysis of vehicle trajectories, the parameters of the future conflict of the planned road junctions were established. Studies have shown that a road junction at different levels makes possible to triple the safety of junctions in comparison with the roundabout. The use of simulation allows not to wait for emergency cases, but to evaluate hypothetical structures and alternative layout options for road junctions, where it is not possible to use traditional, statistical models for assessing the probability of car accidents.
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Mo, Tong, Keyi Li, Junjie Zhang, Lingqiao Qin, Zhufei Huang, and Haijian Li. "Collaborative Strategies and Simulation of Vehicle Group Behaviors for Off-Ramp Areas." Journal of Advanced Transportation 2020 (December 22, 2020): 1–11. http://dx.doi.org/10.1155/2020/8817364.
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With the increase of vehicle ownership and the rapid growth of urban traffic, the problem of congestion in the off-ramp area of the main expressway has become the main factor restricting overall section efficiency and inducing traffic accidents. This paper focuses on the problem of group collaborative lane-changing behaviors of off-ramp vehicles and through vehicles in off-ramp areas and proposes four kinds of vehicle group collaborative strategies based on different road space balance conditions. According to a three-lane expressway scene, a VISSIM-based simulation model is built and the optimization scheme is simulated and evaluated. The simulation results show that with the increase of traffic flow in off-ramp areas, a flow-balance strategy for downstream lanes where off-ramp vehicles merge with the outside lane in advance is more advantageous. When vehicles are leaving the main road, if traffic flow is heavy, the flow-balance strategy for lanes where off-ramp vehicles merge with the outside lane in advance (for example, the proportion of off-ramp vehicles in three lanes is 0 : 0 : 1) is better; otherwise, when the traffic flow on the main road is relatively small, the flow-balance strategy for lanes where off-ramp vehicles are distributed in lanes with different ratios (e.g., 1 : 3 : 6) is better. What is more, for future traffic management in connected vehicle environments, it can be concluded that collaborative vehicle lane-changing strategies with different traffic flow states can help to enhance traffic efficiency.
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Abdelghany, Ahmed, Hani Mahmassani, Khaled Abdelghany, Hasan Al-Ahmadi, and Wael Alhalabi. "Incidents in high-volume elongated crowd facilities: A simulation-based study." SIMULATION 95, no. 9 (September 11, 2018): 823–43. http://dx.doi.org/10.1177/0037549718794882.
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This paper presents the main findings of a simulation-based study to evaluate incidents in pedestrian/crowd tunnels and similar elongated confined facilities, with high-volume heterogeneous traffic. These incidents, when occur, imposes hazardous conditions that always result in significant number of fatalities. The aim of this study is to understand how these facilities perform under different irregular scenarios and possibly identify potential causes of accidents. The problem of studying incidents in large-scale high-volume pedestrian facilities is that these incidents are difficult to expect or replicate. Thus, studying these facilities through real-life scenarios is almost impossible. Accordingly, a micro-simulation assignment model for multidirectional pedestrian movement is used for this purpose. The model adopts a Cellular Automata (CA) discrete system, which allows detailed representation of the pedestrians’ walkways in the tunnel. The modeling approach captures crowd dynamics through representation of behavioral decisions of heterogeneous pedestrians at the individual level. Several experiments are conducted to study the pedestrian flow in the proposed tunnel considering different operational scenarios including demand levels, heterogeneous traffic, evacuation scenario, and tunnel blockage. Results show that flow of large pedestrian volumes through a long confined linear structure, such as a tunnel, are subject to the same flow dynamics as we observe with vehicular traffic. In particular, they are subject to the formation of “clumps” and shock waves that can rapidly propagate and lead to inefficient operation, including flow breakdown with stop-and-go waves.
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Zeng, Changqing, Zhendong Mu, and Qingjun Wang. "Classifying Driving Fatigue by Using EEG Signals." Computational Intelligence and Neuroscience 2022 (March 24, 2022): 1–13. http://dx.doi.org/10.1155/2022/1885677.
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Fatigue driving is one of the main reasons for the occurrence of traffic accidents. Brain-computer interface, as a human-computer interaction method based on EEG signals, can communicate with the outside world and move freely through brain signals without relying on the peripheral neuromuscular system. In this paper, a simulation driving platform composed of driving simulation equipment and driving simulation software is used to simulate the real driving process. The EEG signals of the subjects are collected through simulated driving, and the EEG of five subjects is selected as the training sample, and the remaining one is the subject. As a test sample, perform feature extraction and classification experiments, select any set of normal signals and fatigue signals recorded in the driving fatigue experiment for data analysis, and then study the classification of driver fatigue levels. Experiments have proved that the PSO-H-ELM algorithm has only about 4% advantage compared with the average accuracy of the KNN algorithm and the SVM algorithm. The gap is not as big as expected, but as a new algorithm, it is applied to the detection of fatigue EEG. The two traditional algorithms are indeed more suitable. It shows that the driver fatigue level can be judged by detecting EEG, which will provide a basis for the development of on-board, real-time driving fatigue alarm devices. It will lay the foundation for traffic management departments to intervene in driving fatigue reasonably and provide a reliable basis for minimizing traffic accidents.
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Cherednichenko, Kostiantyn. "URBAN TRANSPORT NETWORK OPTIMIZATION MODELING IN INTEGRATED TRANSPORT SYSTEMS." Dorogi i mosti 2022, no. 25 (March 17, 2022): 259–69. http://dx.doi.org/10.36100/dorogimosti2022.25.259.
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Abstract In world practice, one of the main features of integrated transport systems, is the delivery of goods "door-to-door", which is impossible without the road transport is being used at the final stage of transportation. Today, the situation on the Ukrainian roads has a negative trend in terms of traffic jams and accidents, which creates a risk of delay or damage to freight during the transportation process. The problem is how to optimize the urban transport network to meet the growing demand for transportation and reduce traffic congestion. Purpose. Investigate the root causes of traffic congestion and develop a tool in order to optimize the city network on the example of a traffic interchange. Analytical and experimental with the use of computer 3D-simulation. For a practical demonstration, a model of one of the most problematic, from the point of view of traffic jams, transport interchanges in Kyiv, was developed. An optimization experiment was conducted, which demonstrated an increase in interchange capacity by 26,2% and reduction in average transportation time by 60, 47%. It is a difficult task to optimizing the transport network, because if you conduct an experiment with a real system, any changes could be catastrophic. In addition, it is necessary to anticipate the growth of traffic, take into account the economic, territorial and industrial characteristics of settlements. The research clearly demonstrates the possibilities of simulation computer modeling in this aspect. The purposed solution allows to optimize the city transport network without significant investment, and could reduce the risk of accidents, financial and time costs for transportation of goods by city in the global aspect. Keywords: freight transport, intersections, integrated transport systems, urban transport network, optimization, imitation modeling.
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Choi, Yongsoon, Seryong Baek, Cheonho Kim, Junkyu Yoon, and Seongkwan Mark Lee. "Simulation of AEBS Applicability by Changing Radar Detection Angle." Applied Sciences 11, no. 5 (March 5, 2021): 2305. http://dx.doi.org/10.3390/app11052305.
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As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.
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Zhang, Yuxuan, Ranhang Zhao, Haofang Wang, Tao Peng, and Huaqing Zhao. "A Gateway to Rapid Prediction of Water Quality: A Case Study in China’s South-to-North Water Diversion Project." Water 13, no. 17 (September 1, 2021): 2407. http://dx.doi.org/10.3390/w13172407.
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Water quality assurance is the primary factor for the successful operation of water diversion projects across river basins. The rapid prediction of water pollution is the basis for timely and effective emergency control and disposal measures. In China, since the open channels intersect with numerous waterways and traffic arteries, water transfer projects are prone to sudden water pollution accidents. In this paper, the rapid prediction method was developed for sudden water pollution accidents that possibly occurred in the East Route of the South-to-North Water Diversion Project (ERP) in Shandong Province. With the empirical formula of the pollution transfer law, a rapid prediction model of water quality (WQRP) was established based on the simulation of the typical accidents in the main channel. Finally, four typical accidents were selected as application examples, and the prediction results were compared with the results from a computer numerical simulation to demonstrate the validity of the model. The results showed that the prediction results by the WQRP model meet the accuracy requirements. This method is of great significance for providing water transport security in the extreme conditions of long-distance water transfer projects.
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Chuprov, Sergey, Ilya Viksnin, Iuliia Kim, Egor Marinenkov, Maria Usova, Eduard Lazarev, Timofey Melnikov, and Danil Zakoldaev. "Reputation and Trust Approach for Security and Safety Assurance in Intersection Management System." Energies 12, no. 23 (November 28, 2019): 4527. http://dx.doi.org/10.3390/en12234527.
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Crossroads are the main traffic jam generators in densely populated cities. Unmanned vehicles and intelligent transportation systems can significantly reduce congestion and improve road safety by eliminating the main cause of traffic accidents—the human factor. However, full confidence in their safety is necessary. This paper addresses the contextual data integrity problem, when an unmanned autonomous vehicle transmits incorrect data due to technical problems, or malicious attacks. We propose an approach based on trust and reputation that allows detecting vehicles transmitting bogus data. To verify the feasibility of the approach on practice, we conducted both software and physical simulations using the model of intersection and unmanned autonomous vehicle models. The simulation results show that the approach applied allows detecting vehicles with bogus data and excluding them from the group, thus increasing the safety of the intersection traversal by other vehicles.
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MA, Yanli, Yanjiang LOU, and Yaowu WANG. "Road Traffic Accidents Model and Its Application Based on Driver's Self-Mistakes." Journal of Transportation Systems Engineering and Information Technology 10, no. 4 (August 2010): 101–5. http://dx.doi.org/10.1016/s1570-6672(09)60059-3.
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Wu, Wenjing, Renchao Sun, Yongxing Li, and Runchao Chen. "Cooperative U-Turn Merging Behaviors and Their Impacts on Road Traffic in CVIS Environment." Journal of Advanced Transportation 2020 (February 10, 2020): 1–14. http://dx.doi.org/10.1155/2020/4158569.
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U-turn behavior of vehicle is one of the main causes of urban traffic congestion and accidents. A collaborative U-turn merging control algorithm is studied with collision avoidance and delay minimization for vehicles under Cooperative Vehicle Infrastructure System (CVIS) environment. Two control strategies, zip merging and platoon merging control, are proposed. The applicability of these two strategies is compared from the perspective of efficiency and driving comfort. The cellular automaton simulation system composed of a two-way four-lane traffic flow with a U-turn facility in middle of road is established with cooperative control algorithm imbedded. The influence of cooperative U-turn merging behaviors on traffic performance is evaluated by analyzing the arrival rates of main lane and U-turn vehicles and their relationship between one another. The simulation results show that the arrival rate of vehicles on target lane has a great impact on traffic delay. The cooperative control can improve the traffic flow only in the condition that the arrival rate of vehicles on target lane is less than 0.7. It provides some practical references for transportation agencies to meet efficiency requirements of the U-turn section when they apply cooperative control strategy.
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Xi, Jianfeng, Shiqing Wang, Tongqiang Ding, Jian Tian, Hui Shao, and Xinning Miao. "Detection Model on Fatigue Driving Behaviors Based on the Operating Parameters of Freight Vehicles." Applied Sciences 11, no. 15 (August 2, 2021): 7132. http://dx.doi.org/10.3390/app11157132.
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Whether in developing or developed countries, traffic accidents caused by freight vehicles are responsible for more than 10% of deaths of all traffic accidents. Fatigue driving is one of the main causes of freight vehicle accidents. Existing fatigue driving studies mostly use vehicle operating data from experiments or simulation data, exposing certain drawbacks in the validity and reliability of the models used. This study collected a large quantity of real driving data to extract sample data under different fatigue degrees. The parameters of vehicle operating data were selected based on significant driver fatigue degrees. The k-nearest neighbor algorithm was used to establish the detection model of fatigue driving behaviors, taking into account influence of the number of training samples and other parameters in the accuracy of fatigue driving behavior detection. With the collected operating data of 50 freight vehicles in the past month, the fatigue driving behavior detection models based on the k-nearest neighbor algorithm and the commonly used BP neural network proposed in this paper were tested, respectively. The analysis results showed that the accuracy of both models are 75.9%, but the fatigue driving detection model based on the k-nearest neighbor algorithm is more reliable.
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Branzi, Valentina, Monica Meocci, Lorenzo Domenichini, and Margherita Calcinai. "A Combined Simulation Approach to Evaluate Overtaking Behaviour on Two-Lane Two-Way Rural Roads." Journal of Advanced Transportation 2021 (August 20, 2021): 1–18. http://dx.doi.org/10.1155/2021/9973138.
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A significant percentage of road fatalities and injuries occur in the nonmotorway rural road network. One of the main causes of accidents on these roads is represented by overtaking, as, by its nature, it involves a risk of a head-on collision with oncoming traffic. The paper describes a combined simulation approach (driving simulator and traffic microsimulation) designed to examine the influence of different traffic conditions on passing manoeuvres on two-lane two-way rural roads. The main focus was the evaluation of the end of the passing manoeuvre because it reflects the risk of a head-on collision. In addition, the study aimed to assess the usefulness of the proposed combined approach in the ability to proactively and quickly diagnose traffic safety problems and consequently to evaluate appropriate solutions. The data collected with an interactive driving simulator on a sample of 54 participants have been used to adjust some input data of the traffic microsimulation software. A specific situation consisting of a stationary heavy vehicle obstructing the entire lane was repeated in both experiments. The analyses focused on time-to-collision (TTC), defined as the remaining gap between the passing vehicle and the oncoming vehicle at the end of the passing manoeuvre. The results showed that the type of manoeuvre performed is significantly influenced by the traffic condition. Furthermore, the manoeuvre is influenced by the gap between two successive vehicles in the opposite lanes. Focusing on the end of the manoeuvre, it was found how a traffic increase leads to a significant reduction of the TTC values. Furthermore, the comparative analysis conducted between the data recorded following the combined approach and those obtained using exclusively the input data of the microsimulation software supports the usefulness of the proposed methodology for conducting road safety analyses, especially in complex traffic environments where drivers’ behaviour plays a decisive role.
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Mocholí Belenguer, Ferran, Antonio Martínez-Millana, Antonio Mocholí Salcedo, Víctor Milián Sánchez, and María Josefa Palomo Anaya. "Disdrometer Performance Optimization for Use in Urban Settings Based on the Parameters that Affect the Measurements." Symmetry 12, no. 2 (February 20, 2020): 303. http://dx.doi.org/10.3390/sym12020303.
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There are currently different types of commercial optical disdrometers to measure the rainfall intensity, of which many are commonly used for monitoring road conditions. Having information about the amount of rain, the composition of the precipitation particles and visibility are essential to avoid accidents, which requires intelligent systems that warn drivers and redirect traffic. However, few studies related to Intelligent Transport Systems (ITS) have been performed regarding why these devices are not optimized for this type of applications. Therefore, this paper analyzes and evaluates the operating mode of these equipment through their theoretical model, which will allow the design of prototypes of disdrometers with different characteristics. In addition, this model will be implemented in a simulation program, through which an exhaustive study analyzing how the type of precipitation and its intensity affect the measures provided by the model will be conducted. In this way, the results will help optimize its operation to be thus used in urban settings, which will allow obtaining more accurate real-time information, better traffic management, and a reduction in the number of accidents.
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Kuang, Li, Jianbo Zheng, Kemu Li, and Honghao Gao. "Intelligent Traffic Signal Control Based on Reinforcement Learning with State Reduction for Smart Cities." ACM Transactions on Internet Technology 21, no. 4 (July 22, 2021): 1–24. http://dx.doi.org/10.1145/3418682.
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Efficient signal control at isolated intersections is vital for relieving congestion, accidents, and environmental pollution caused by increasing numbers of vehicles. However, most of the existing studies not only ignore the constraint of the limited computing resources available at isolated intersections but also the matching degree between the signal timing and the traffic demand, leading to high complexity and reduced learning efficiency. In this article, we propose a traffic signal control method based on reinforcement learning with state reduction. First, a reinforcement learning model is established based on historical traffic flow data, and we propose a dual-objective reward function that can reduce vehicle delay and improve the matching degree between signal time allocation and traffic demand, allowing the agent to learn the optimal signal timing strategy quickly. Second, the state and action spaces of the model are preliminarily reduced by selecting a proper control phase combination; then, the state space is further reduced by eliminating rare or nonexistent states based on the historical traffic flow. Finally, a simplified Q-table is generated and used to optimize the complexity of the control algorithm. The results of simulation experiments show that our proposed control algorithm effectively improves the capacity of isolated intersections while reducing the time and space costs of the signal control algorithm.
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He, Zhenbang. "Expressway Information Collection Processing and Control Technology Based on RFID Internet of Things." Journal of Control Science and Engineering 2022 (September 13, 2022): 1–7. http://dx.doi.org/10.1155/2022/1194161.
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In order to solve the problems of highway traffic congestion and frequent traffic accidents, a technology method for highway information collection, processing, and control based on RFID Internet of Things is proposed. The highway information collection and processing control technology designed in this paper is based on radio frequency identification technology to realize the collection of highway vehicle information, analyze, and process the collected information, and finally get the road condition information. Through the extraction and analysis of the traffic flow information in the video surveillance, the background difference method is used to extract the relevant vehicle factors in the video, including the extraction of traffic flow information, vehicle model extraction, and vehicle speed extraction. Traffic detection provides convenience. The experimental data shows that from Monday to Friday on weekdays, the road congestion rates are 2.72%, 1.94%, 2.77%, 2.27%, and 3.47% respectively; the average vehicle speed on weekdays is 89.96 km/h, and the test results are fast and accurate. The proposed method integrates road information collection and road information service, realizes traffic detection when there are vehicles, and realizes detection and perception of large-scale road traffic systems. Travelers provide real-time traffic information and navigation services.
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Li, Jin Fang, Shun Mu Fang, Han Wu He, and Jun Wei Wen. "Realization of the Car Tire Puncture in Virtual Environment." Applied Mechanics and Materials 475-476 (December 2013): 1433–38. http://dx.doi.org/10.4028/www.scientific.net/amm.475-476.1433.
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Traffic accidents,which are caused by faulty tires, have caused great losses to people's life and property.At present, generally,researching prevention measures of tires puncture are through real car tires tests around domestic and international. I made a research about automobile tires puncture performance in a virtual driving environment ,to build a virtual car tires puncture research system in combination with the VC platform and EON simulation software, and used the Logitech G25 controller to manipulate virtual cars, then real-time human-computer interaction was achieved.