为实现车道在正常情况下的少人化、无人化交易服务,为特情车辆提供智慧化的服务,提高车辆的通行效率,完善智慧高速建设。结合云、大数据和人工智能(artificial intelligence,AI)技术,在车道前端以智能硬件和应用软件为载体,后台以软件...为实现车道在正常情况下的少人化、无人化交易服务,为特情车辆提供智慧化的服务,提高车辆的通行效率,完善智慧高速建设。结合云、大数据和人工智能(artificial intelligence,AI)技术,在车道前端以智能硬件和应用软件为载体,后台以软件服务化(software as a service,SaaS)云服务为主要形式,构建智慧收费云+无人收费站系统。该系统节约了路段经营单位的收费运营成本、建设投资成本和后期维护成本,提升了路段经营管理单位的服务水平,彰显了高速公路的智慧服务能力。展开更多
With the growing rate of automated vehicles(AVs)at the lower level of automation,the experimental tests are also in progress with vehicles at higher levels.In the absence of extended digital infrastructures and deploy...With the growing rate of automated vehicles(AVs)at the lower level of automation,the experimental tests are also in progress with vehicles at higher levels.In the absence of extended digital infrastructures and deployment of level 5 full automated vehicles,the physical infrastructure is required to maintain a fundamental role to enable their introduction in public roads.This paper focuses on lane support system(LSS)whose operational design domain(ODD)is strongly connected to the road characteristics and conditions.An experimental test was carried out with a state of the art,and LSS and advanced technologies were used for road monitoring on different roads under various environmental conditions including dry,wet pavements and rain.We applied the generalized estimation equation for logistic regression to account within-cluster homogeneity which is induced by repeated measures on the same road sections.Statistical models allow the identification of variables that are significant for the LSS fault probability among various effects of road features including marking,pavement distress,weather conditions,horizontal curvature,and cross section.Results pointed out the relevance of the wet retro-reflection of marking(RLw)and the horizontal curvature in the definition of ODD for LSS.Threshold values have been proposed for the tested LSS.Wet pavement doesn’t affect the LSS performance when compared to the dry condition.Rain was shown to be critical even with very good road characteristics.展开更多
A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and...A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.展开更多
The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’merging and lane-changing behaviors,while ensuring safety and optimizing traffic flow.However,the...The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’merging and lane-changing behaviors,while ensuring safety and optimizing traffic flow.However,there are few studies that have addressed the merging problem of ramp vehicles and the cooperative lane-change problem of mainline vehicles within a unified framework and proposed corresponding optimization strategies.To tackle this issue,this study adopts a cyber-physical integration perspective and proposes a graph-based solution approach.First,the information of vehicle groups in the physical plane is mapped to the cyber plane,and a dynamic conflict graph is introduced in the cyber space to describe the conflict relationships among vehicle groups.Subsequently,graph decomposition and search strategies are employed to obtain the optimal solution,including the set of mainline vehicles changing lanes,passing sequences for each route,and corresponding trajectories.Finally,the proposed dynamic conflict graph-based algorithm is validated through simulations in continuous traffic with various densities,and its performance is compared with the default algorithm in SUMO.The results demonstrate the effectiveness of the proposed approach in improving vehicle safety and traffic efficiency,particularly in high traffic density scenarios,providing valuable insights for future research in multi-lane merging strategies.展开更多
Continuous-scale trusted safety efficiency evaluation is crucial for the agile development and robust validation of autonomous vehicle intelligence.While the UN R157 Regulation evaluates automated lane-keeping system(...Continuous-scale trusted safety efficiency evaluation is crucial for the agile development and robust validation of autonomous vehicle intelligence.While the UN R157 Regulation evaluates automated lane-keeping system(ALKS)performance baselines through safe collision plots(SCPs)in various scenario clusters,quantifying the specific ALKS safety efficiency remains challenging.We propose a spectrum quantification approach to evaluate the safety efficiency of autonomous vehicles in cut-in scenarios.First,we collected speed-distance data under different cut-in scenarios and extracted essential spectral features to indicate the vehicle motion parameters during the cut-in process.Second,by utilizing Fourier analysis,a spectral analysis model was built to quantify and analyze the vehicle motion characteristics,providing insights into scenario safety.Finally,we created approximate analytical equations for the normalized disturbance frequencies in the nonlinear response scenarios of autonomous driving systems by combining the SCP with a frequency spectrum analysis model.The results showed that the normalized disturbance frequency in the cut-in scenario was approximately 0.2.When the relative longitudinal distance and speed of the vehicle are the same,if the cut-in speed of the cut-in vehicle is larger,the normalized disturbance frequency is higher,indicating that the cut-in process of the autonomous vehicle is more dangerous and may trigger a collision.展开更多
Current research on lane-keeping systems ignores the effect of the driver and external resistance on the accuracy of tracking the lane centerline.To reduce the lateral deviation of the vehicle,a lane-keeping control m...Current research on lane-keeping systems ignores the effect of the driver and external resistance on the accuracy of tracking the lane centerline.To reduce the lateral deviation of the vehicle,a lane-keeping control method based on the fuzzy Takagi-Sugeno(T-S)model is proposed.The method adopts a driver model based on near and far visual angles,and a driver-road-vehicle closed-loop model based on longitudinal nonlinear velocity variation,obtaining the expected assist torque with a robust H∞controller which is designed based on parallel distributed compensation and linear matrix inequality.Considering the external influences of tire adhesion and aligning torque when the vehicle is steering,a feedforward compensation control is designed.The electric power steering system is adopted as the actuator for lane-keeping,and active steering redressing is realized by a control motor.Simulation results based on Carsim/Simulink and real vehicle test results demonstrate that the method helps to maintain the vehicle in the lane centerline and ensures driving safety.展开更多
文摘为实现车道在正常情况下的少人化、无人化交易服务,为特情车辆提供智慧化的服务,提高车辆的通行效率,完善智慧高速建设。结合云、大数据和人工智能(artificial intelligence,AI)技术,在车道前端以智能硬件和应用软件为载体,后台以软件服务化(software as a service,SaaS)云服务为主要形式,构建智慧收费云+无人收费站系统。该系统节约了路段经营单位的收费运营成本、建设投资成本和后期维护成本,提升了路段经营管理单位的服务水平,彰显了高速公路的智慧服务能力。
基金partially financed by“Astro Database”Project of the University of Catania
文摘With the growing rate of automated vehicles(AVs)at the lower level of automation,the experimental tests are also in progress with vehicles at higher levels.In the absence of extended digital infrastructures and deployment of level 5 full automated vehicles,the physical infrastructure is required to maintain a fundamental role to enable their introduction in public roads.This paper focuses on lane support system(LSS)whose operational design domain(ODD)is strongly connected to the road characteristics and conditions.An experimental test was carried out with a state of the art,and LSS and advanced technologies were used for road monitoring on different roads under various environmental conditions including dry,wet pavements and rain.We applied the generalized estimation equation for logistic regression to account within-cluster homogeneity which is induced by repeated measures on the same road sections.Statistical models allow the identification of variables that are significant for the LSS fault probability among various effects of road features including marking,pavement distress,weather conditions,horizontal curvature,and cross section.Results pointed out the relevance of the wet retro-reflection of marking(RLw)and the horizontal curvature in the definition of ODD for LSS.Threshold values have been proposed for the tested LSS.Wet pavement doesn’t affect the LSS performance when compared to the dry condition.Rain was shown to be critical even with very good road characteristics.
基金Project(51175159)supported by the National Natural Science Foundation of ChinaProject(2013WK3024)supported by the Science andTechnology Planning Program of Hunan Province,ChinaProject(CX2013B146)supported by the Hunan Provincial InnovationFoundation for Postgraduate,China
文摘A technology for unintended lane departure warning was proposed. As crucial information, lane boundaries were detected based on principal component analysis of grayscale distribution in search bars of given number and then each search bar was tracked using Kalman filter between frames. The lane detection performance was evaluated and demonstrated in ways of receiver operating characteristic, dice similarity coefficient and real-time performance. For lane departure detection, a lane departure risk evaluation model based on lasting time and frequency was effectively executed on the ARM-based platform. Experimental results indicate that the algorithm generates satisfactory lane detection results under different traffic and lighting conditions, and the proposed warning mechanism sends effective warning signals, avoiding most false warning.
基金supported by the National Key R&D Program of China(2022YFB2503200)the National Natural Science Foundation of China,Science Fund for Creative Research Groups(52221005).
文摘The on-ramp merging in multi-lane highway scenarios presents challenges due to the complexity of coordinating vehicles’merging and lane-changing behaviors,while ensuring safety and optimizing traffic flow.However,there are few studies that have addressed the merging problem of ramp vehicles and the cooperative lane-change problem of mainline vehicles within a unified framework and proposed corresponding optimization strategies.To tackle this issue,this study adopts a cyber-physical integration perspective and proposes a graph-based solution approach.First,the information of vehicle groups in the physical plane is mapped to the cyber plane,and a dynamic conflict graph is introduced in the cyber space to describe the conflict relationships among vehicle groups.Subsequently,graph decomposition and search strategies are employed to obtain the optimal solution,including the set of mainline vehicles changing lanes,passing sequences for each route,and corresponding trajectories.Finally,the proposed dynamic conflict graph-based algorithm is validated through simulations in continuous traffic with various densities,and its performance is compared with the default algorithm in SUMO.The results demonstrate the effectiveness of the proposed approach in improving vehicle safety and traffic efficiency,particularly in high traffic density scenarios,providing valuable insights for future research in multi-lane merging strategies.
基金the National Key R&D Program of China(Grant No.2021YFB1600403)the National Natural Science Foundation of China(Grant Nos.51805312 and 52172388).
文摘Continuous-scale trusted safety efficiency evaluation is crucial for the agile development and robust validation of autonomous vehicle intelligence.While the UN R157 Regulation evaluates automated lane-keeping system(ALKS)performance baselines through safe collision plots(SCPs)in various scenario clusters,quantifying the specific ALKS safety efficiency remains challenging.We propose a spectrum quantification approach to evaluate the safety efficiency of autonomous vehicles in cut-in scenarios.First,we collected speed-distance data under different cut-in scenarios and extracted essential spectral features to indicate the vehicle motion parameters during the cut-in process.Second,by utilizing Fourier analysis,a spectral analysis model was built to quantify and analyze the vehicle motion characteristics,providing insights into scenario safety.Finally,we created approximate analytical equations for the normalized disturbance frequencies in the nonlinear response scenarios of autonomous driving systems by combining the SCP with a frequency spectrum analysis model.The results showed that the normalized disturbance frequency in the cut-in scenario was approximately 0.2.When the relative longitudinal distance and speed of the vehicle are the same,if the cut-in speed of the cut-in vehicle is larger,the normalized disturbance frequency is higher,indicating that the cut-in process of the autonomous vehicle is more dangerous and may trigger a collision.
基金National Natural Science Foundation of China(Grant Nos.51675151,U1564201)Open Fund of the Key Laboratory of Advanced Perception and Intelligent Control of High-end Equipment of Ministry of Education(Grant No.GDSC202013).
文摘Current research on lane-keeping systems ignores the effect of the driver and external resistance on the accuracy of tracking the lane centerline.To reduce the lateral deviation of the vehicle,a lane-keeping control method based on the fuzzy Takagi-Sugeno(T-S)model is proposed.The method adopts a driver model based on near and far visual angles,and a driver-road-vehicle closed-loop model based on longitudinal nonlinear velocity variation,obtaining the expected assist torque with a robust H∞controller which is designed based on parallel distributed compensation and linear matrix inequality.Considering the external influences of tire adhesion and aligning torque when the vehicle is steering,a feedforward compensation control is designed.The electric power steering system is adopted as the actuator for lane-keeping,and active steering redressing is realized by a control motor.Simulation results based on Carsim/Simulink and real vehicle test results demonstrate that the method helps to maintain the vehicle in the lane centerline and ensures driving safety.
