Techniques for predicting the trajectory of vulnerable road users are important to the development of perception systems for autonomous vehicles to avoid accidents.The most effective trajectory prediction methods,such...Techniques for predicting the trajectory of vulnerable road users are important to the development of perception systems for autonomous vehicles to avoid accidents.The most effective trajectory prediction methods,such as Social-LSTM,are often used to predict pedestrian trajectories in normal passage scenarios.However,they can produce unsatisfactory prediction results and data redundancy,as well as difficulties in predicting trajectories using pixel-based coordinate systems in collision avoidance systems.There is also a lack of validations using real vehicle-to-pedestrian collisions.To address these issues,some insightful approaches to improve the trajectory prediction scheme of Social-LSTM were proposed,such methods included transforming pedestrian trajectory coordinates and converting image coordinates to world coordinates.The YOLOv5 detection model was introduced to reduce target loss and improve prediction accuracy.The DeepSORT algorithm was employed to reduce the number of target transformations in the tracking model.Image Perspective Transformation(IPT)and Direct Linear Transformation(DLT)theories were combined to transform the coordinates to world coordinates,identifying the collision location where the accident could occur.The performance of the proposed method was validated by training tests using MS COCO(Microsoft Common Objects in Context)and ETH/UCY datasets.The results showed that the target detection accuracy was more than 90%and the prediction loss tends to decrease with increasing training steps,with the final loss value less than 1%.The reliability and effectiveness of the improved method were demonstrated by benchmarking system performance to two video recordings of real pedestrian accidents with different lighting conditions.展开更多
In recent years, we have been able to use various services using the position information of smartphones and tablets. In addition, research on intelligent transport systems (ITS) has been actively conducted. To consid...In recent years, we have been able to use various services using the position information of smartphones and tablets. In addition, research on intelligent transport systems (ITS) has been actively conducted. To consider reducing traffic accidents by exchanging position information between pedestrians and vehicles by vehicle-to-pedestrian communication, we require accurate position information for pedestrians and vehicles. The GPS (global positioning system) is the most widely used method for acquiring position information. However, in urban areas, the GPS signal is affected by the surrounding buildings, which increases the positioning error. In this study, a method to improve the positioning accuracy of pedestrians using the signal strengths from vehicles and beacons was proposed. First, a Kalman filter was applied to the signal strength. Then, the path loss index was dynamically calculated using vehicle-to-vehicle communication. Finally, the position of a pedestrian was obtained using weighted centroid localization (WCL) after filtering the nodes. The positioning accuracy was evaluated using a simulator and demonstrated the superiority of the proposed method.展开更多
The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports f...The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports for the development of edge computing technology.This paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge computing.Through trial and error learning of agent,the optimal spectrum and power can be determined for transmission without global information,so as to balance the communication between vehicle-to-pedestrian and vehicle-to-infrastructure.The results show that the agent can effectively improve vehicle-to-infrastructure communication rate as well as meeting the delay constraints on the vehicle-to-pedestrian link.展开更多
Objective： To explore the relationship between the collision parameters of vehicle and the pedestrian thorax injury by establishing the chest simulation models in car-pedestrian collision at different velocities and ...Objective： To explore the relationship between the collision parameters of vehicle and the pedestrian thorax injury by establishing the chest simulation models in car-pedestrian collision at different velocities and angles. Methods： 87 cases of vehicle-to-pedestrian accidents, with detailed injury information and determined vehicle impact parameters, were included. The severity of injury was scaled in line with the Abbreviated Injury Scale （AIS）. The chest biomechanical response parameters and change characteristics were obtained by using Hyperworks and LS-DYNA computing. Simulation analysis was applied to compare the characteristics of injuries. Results： When impact velocities at 25, 40 and 55 km/h, respectively, 1） the maximum values of thorax velocity criterion （VC） were for 0.29, 0.83 and 2.58 m/s; and at the same collision velocity, the thorax VC from the impact on pedestrian＇s front was successively greater than on his back and on his side; 2） the maximum values of peak stress on ribs were 154,177 and 209 MPa; and at the same velocity, peak stress values on ribs from the impact on pedestrian＇s side were greater than on his front and his back. Conclusion： There is a positive correlation between the severity and risk of thorax injury and the collision velocity and angle of car-thorax crashes. At the same velocity, it is of greater damage risk when the soft tissue of thorax under a front impact; and there is also a greater risk of ribs fracture under a side impact of the thorax. This result is of vital significance for diagnosis and protection of thorax collision injuries.展开更多
基于THUMS(total human model for safety)下肢长骨有限元模型,在材料和单元属性等方面进行了改进.在详细分析行人下肢长骨载荷特点的基础上,采用多种不同载荷工况下较新的生物力学实验数据,对长骨模型进行了前-后和外-内加载方向的准...基于THUMS(total human model for safety)下肢长骨有限元模型,在材料和单元属性等方面进行了改进.在详细分析行人下肢长骨载荷特点的基础上,采用多种不同载荷工况下较新的生物力学实验数据,对长骨模型进行了前-后和外-内加载方向的准静态三点弯曲验证,同时对近心端1/3处、中部和远心端1/3处加载的动态三点弯曲验证.验证结果表明,该模型具有较好的生物逼真度,能够准确地模拟行人下肢长骨的骨折及碰撞响应,可用于后续行人下肢模型的开发,并为行人下肢损伤机理和安全防护研究提供准确高效的研究手段.展开更多
This work presents a simulation model for unsignalized crosswalks which takes into account collisions between vehicles and pedestrians,thus allowing to assess the estimated yearly pedestrian fatality.In particular,we ...This work presents a simulation model for unsignalized crosswalks which takes into account collisions between vehicles and pedestrians,thus allowing to assess the estimated yearly pedestrian fatality.In particular,we focus on a method to calibrate such a model combining measurable crosswalk characteristics,such as maximum speed limit or drivers’compliance,with statistical data for past accidents obtained from local municipality.In order to perform simulations under realistic conditions,we constructed a one-week scenario where pedestrian and vehicle traffic vary using specific patterns each hour of the week.The constructed traffic profile is based on openly available data and the suitability for the scenario considered(a crosswalk in Milan,Italy)is investigated showing that cultural/lifestyle elements determine the variation of weekly traffic.Simulations using the constructed one-week scenario were used to obtain the only non-measurable parameter which account for pedestrians’and drivers’distraction.In addition,we also focused on the presence of elderly pedestrians which have different physiological characteristics compared to adults or children and are becoming an important part of the population in several countries around the globe.The simulation model presented here and the method suggested for calibration may be employed in different contexts,thus allowing to build an important tool to be used not only for transportation efficiency/optimization but also for safety analysis.展开更多
基金support of the Natural Science Foundation of China(Grant No.51775466)the Xiamen City Natural Science Foundation(No.3502Z20227223).
文摘Techniques for predicting the trajectory of vulnerable road users are important to the development of perception systems for autonomous vehicles to avoid accidents.The most effective trajectory prediction methods,such as Social-LSTM,are often used to predict pedestrian trajectories in normal passage scenarios.However,they can produce unsatisfactory prediction results and data redundancy,as well as difficulties in predicting trajectories using pixel-based coordinate systems in collision avoidance systems.There is also a lack of validations using real vehicle-to-pedestrian collisions.To address these issues,some insightful approaches to improve the trajectory prediction scheme of Social-LSTM were proposed,such methods included transforming pedestrian trajectory coordinates and converting image coordinates to world coordinates.The YOLOv5 detection model was introduced to reduce target loss and improve prediction accuracy.The DeepSORT algorithm was employed to reduce the number of target transformations in the tracking model.Image Perspective Transformation(IPT)and Direct Linear Transformation(DLT)theories were combined to transform the coordinates to world coordinates,identifying the collision location where the accident could occur.The performance of the proposed method was validated by training tests using MS COCO(Microsoft Common Objects in Context)and ETH/UCY datasets.The results showed that the target detection accuracy was more than 90%and the prediction loss tends to decrease with increasing training steps,with the final loss value less than 1%.The reliability and effectiveness of the improved method were demonstrated by benchmarking system performance to two video recordings of real pedestrian accidents with different lighting conditions.
文摘In recent years, we have been able to use various services using the position information of smartphones and tablets. In addition, research on intelligent transport systems (ITS) has been actively conducted. To consider reducing traffic accidents by exchanging position information between pedestrians and vehicles by vehicle-to-pedestrian communication, we require accurate position information for pedestrians and vehicles. The GPS (global positioning system) is the most widely used method for acquiring position information. However, in urban areas, the GPS signal is affected by the surrounding buildings, which increases the positioning error. In this study, a method to improve the positioning accuracy of pedestrians using the signal strengths from vehicles and beacons was proposed. First, a Kalman filter was applied to the signal strength. Then, the path loss index was dynamically calculated using vehicle-to-vehicle communication. Finally, the position of a pedestrian was obtained using weighted centroid localization (WCL) after filtering the nodes. The positioning accuracy was evaluated using a simulator and demonstrated the superiority of the proposed method.
基金supported by National Natural Science Foundation of China(No.61871283)the Foundation of Pre-Research on Equipment of China(No.61400010304)Major Civil-Military Integration Project in Tianjin,China(No.18ZXJMTG00170).
文摘The development of communication technology will promote the application of Internet of Things,and Beyond 5G will become a new technology promoter.At the same time,Beyond 5G will become one of the important supports for the development of edge computing technology.This paper proposes a communication task allocation algorithm based on deep reinforcement learning for vehicle-to-pedestrian communication scenarios in edge computing.Through trial and error learning of agent,the optimal spectrum and power can be determined for transmission without global information,so as to balance the communication between vehicle-to-pedestrian and vehicle-to-infrastructure.The results show that the agent can effectively improve vehicle-to-infrastructure communication rate as well as meeting the delay constraints on the vehicle-to-pedestrian link.
基金The Natural Science Foundation of China （Project number 31271006）, the Chongqing Natural Science Fund （Project number CSTC2012JJYS0004）.
文摘Objective： To explore the relationship between the collision parameters of vehicle and the pedestrian thorax injury by establishing the chest simulation models in car-pedestrian collision at different velocities and angles. Methods： 87 cases of vehicle-to-pedestrian accidents, with detailed injury information and determined vehicle impact parameters, were included. The severity of injury was scaled in line with the Abbreviated Injury Scale （AIS）. The chest biomechanical response parameters and change characteristics were obtained by using Hyperworks and LS-DYNA computing. Simulation analysis was applied to compare the characteristics of injuries. Results： When impact velocities at 25, 40 and 55 km/h, respectively, 1） the maximum values of thorax velocity criterion （VC） were for 0.29, 0.83 and 2.58 m/s; and at the same collision velocity, the thorax VC from the impact on pedestrian＇s front was successively greater than on his back and on his side; 2） the maximum values of peak stress on ribs were 154,177 and 209 MPa; and at the same velocity, peak stress values on ribs from the impact on pedestrian＇s side were greater than on his front and his back. Conclusion： There is a positive correlation between the severity and risk of thorax injury and the collision velocity and angle of car-thorax crashes. At the same velocity, it is of greater damage risk when the soft tissue of thorax under a front impact; and there is also a greater risk of ribs fracture under a side impact of the thorax. This result is of vital significance for diagnosis and protection of thorax collision injuries.
文摘基于THUMS(total human model for safety)下肢长骨有限元模型,在材料和单元属性等方面进行了改进.在详细分析行人下肢长骨载荷特点的基础上,采用多种不同载荷工况下较新的生物力学实验数据,对长骨模型进行了前-后和外-内加载方向的准静态三点弯曲验证,同时对近心端1/3处、中部和远心端1/3处加载的动态三点弯曲验证.验证结果表明,该模型具有较好的生物逼真度,能够准确地模拟行人下肢长骨的骨折及碰撞响应,可用于后续行人下肢模型的开发,并为行人下肢损伤机理和安全防护研究提供准确高效的研究手段.
基金financially supported by the JST-Mirai Program Grant Number JPMJMI17D4.
文摘This work presents a simulation model for unsignalized crosswalks which takes into account collisions between vehicles and pedestrians,thus allowing to assess the estimated yearly pedestrian fatality.In particular,we focus on a method to calibrate such a model combining measurable crosswalk characteristics,such as maximum speed limit or drivers’compliance,with statistical data for past accidents obtained from local municipality.In order to perform simulations under realistic conditions,we constructed a one-week scenario where pedestrian and vehicle traffic vary using specific patterns each hour of the week.The constructed traffic profile is based on openly available data and the suitability for the scenario considered(a crosswalk in Milan,Italy)is investigated showing that cultural/lifestyle elements determine the variation of weekly traffic.Simulations using the constructed one-week scenario were used to obtain the only non-measurable parameter which account for pedestrians’and drivers’distraction.In addition,we also focused on the presence of elderly pedestrians which have different physiological characteristics compared to adults or children and are becoming an important part of the population in several countries around the globe.The simulation model presented here and the method suggested for calibration may be employed in different contexts,thus allowing to build an important tool to be used not only for transportation efficiency/optimization but also for safety analysis.
