To address the challenge of distinguishing subjective aggressive driving(initiated by drivers)from hazardous behaviors caused by external cyberattacks,this study proposes an innovative intent recognition framework nam...To address the challenge of distinguishing subjective aggressive driving(initiated by drivers)from hazardous behaviors caused by external cyberattacks,this study proposes an innovative intent recognition framework named Intent-Decipher.By integrating the information credibility outputted by an intrusion detection system(IDS)into a security-aware inverse reinforcement learning(SA-IRL)model,the framework infers the reward function behind vehicle behaviors and classifies three key driving intents:normal,aggressive,and malicious.Experiments were conducted on a semi-synthetic dataset containing 20000 trajectories.Results show that Intent-Decipher significantly outperforms baseline methods in classification accuracy,achieving a macro-average F1-score of 0.94.Notably,Intent-Decipher excels at differentiating subjective aggressive driving from attack-induced behaviors:its F1-score for identifying malicious attack-induced(MAI)intent reaches 0.90,an absolute improvement of 0.16 compared with the standard inverse reinforcement learning(IRL)model(which lacks security awareness and only achieves an F1-score of 0.74).展开更多
Urban intersections contain severe blind zones where buildings and roadside obstacles block lineof-sight sensing,limiting the ability of autonomous vehicles to anticipate hidden hazards.This paper presents an urban-in...Urban intersections contain severe blind zones where buildings and roadside obstacles block lineof-sight sensing,limiting the ability of autonomous vehicles to anticipate hidden hazards.This paper presents an urban-intersection-oriented non-line-of-sight(NLOS)perception framework that exploits specular reflections from building surfaces using 77 GHz frequency-modulated continuous-wave(FMCW)automotive radar.All evaluations are conducted in a MATLAB-based simulation environment that models intersection geometry,building-induced occlusions,and specular reflection-assisted propagation,and generates 77-GHz FMCW radar echoes under controllable interference;real-world validation with measured radar data and richer multipath/material modeling is planned as future work.To improve robustness under noisy intersection interference,we propose a deep-learning-based mitigation module that restores corrupted radar echoes at the chirp level using a compact AlexNet-derived 1D regression backbone,with minimal architectural changes that insert a residual block after conv2 and apply batch normalization to enhance training stability and suppress interference while preserving informative echo characteristics.The restored echoes are then processed by conventional estimation steps to obtain range and azimuth-related angles.Under severe interference(Noise Factor=3.0),unmitigated measurements exhibit large errors(root-mean-square error(RMSE)=5.48 m/18.95°/10.77°for range/angle/azimuth deviation).Conventional AlexNet-based mitigation reduces these errors to 0.75 m/0.83°/0.93°,while the proposed improved AlexNet further reduces them to 0.56 m/0.46°/0.73°.The results demonstrate improved signal stability and measurement accuracy,supporting the potential practicality of low-cost NLOS perception in simulation for safety-critical autonomous driving at occluded urban intersections,subject to future real-world validation.展开更多
Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination syst...Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.展开更多
This paper aims to enhance highway traffic efficiency by integrating a project focused on signal timing optimization at highway intersections.Supported by intelligent technologies,a reasonable optimization system is c...This paper aims to enhance highway traffic efficiency by integrating a project focused on signal timing optimization at highway intersections.Supported by intelligent technologies,a reasonable optimization system is constructed.Practical application demonstrates that the signal timing optimization at highway intersections under this system yields significant results,substantially improving traffic efficiency.This provides a reference for subsequent signal timing optimization at highway intersections,aligning with the development needs of the intelligent transportation context.展开更多
The control of traffic flows on urban roads intersections through the traffic control signals is very important,not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability inc...The control of traffic flows on urban roads intersections through the traffic control signals is very important,not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability increase,but also the traffic accidents evidently decrease.In this paper,an adaptive algorithm of traffic control signals on the urban roads intersections is designed in,this new algorithm can actively adjust the concrete control times of the traffic control signals based on the perceiving information of the waiting vehicles in real time,then the dynamic balance between the traffic control signals and the traffic flows can be realized.Furthermore,through experiment testing and demonstrating,this adaptive algorithm expresses some fine performances,it also shows good application prospect in the field of smart city.展开更多
This article explores the intersections of Buddhism,Daoism,and contemporary French literary practice in the study of the everyday(quotidien).Since the 1980s,French literature has increasingly shifted its focus from th...This article explores the intersections of Buddhism,Daoism,and contemporary French literary practice in the study of the everyday(quotidien).Since the 1980s,French literature has increasingly shifted its focus from the exotic to the mundane,engaging with theoretical frameworks developed by scholars such as Henri Lefebvre and Michel de Certeau.Drawing on Buddhist notions of emptiness and dependent arising,as well as Daoist principles of yin-yang interdependence,the article bridges Eastern and Western philosophies to demonstrate the everyday not as a static or trivial backdrop,but as a dynamic and transformative space.It further examines how representations of daily life in the works of Georges Perec and Jacques Roubaud employ the meticulous documentation of mundane details to uncover hidden patterns,rhythms,and structures of human experience.Through literary fieldwork,Perec and Roubaud challenge conventional perceptions of the everyday,unveiling its depth,complexity,and potential for reinvention.展开更多
The discrete fracture network model is a powerful tool for fractured rock mass fluid flow simulations and supports safety assessments of coal mine hazards such as water inrush.Intersection analysis,which identifies al...The discrete fracture network model is a powerful tool for fractured rock mass fluid flow simulations and supports safety assessments of coal mine hazards such as water inrush.Intersection analysis,which identifies all pairs of intersected fractures(the basic components composing the connectivity of a network),is one of its crucial procedures.This paper attempts to improve intersection analysis through parallel computing.Considering a seamless interfacing with other procedures in modeling,two algorithms are designed and presented,of which one is a completely independent parallel procedure with some redundant computations and the other is an optimized version with reduced redundancy.A numerical study indicates that both of the algorithms are practical and can significantly improve the computational performance of intersection analysis for large-scale simulations.Moreover,the preferred application conditions for the two algorithms are also discussed.展开更多
Discrete fracture models are used for investigating precise processes of groundwater flow in fractured rocks,while a disc-shaped parallel-plates model for a single fracture is more reasonable and efficient for computa...Discrete fracture models are used for investigating precise processes of groundwater flow in fractured rocks,while a disc-shaped parallel-plates model for a single fracture is more reasonable and efficient for computational treatments.The flow velocity has a large spatial differentiation which is more likely to produce non-linear flow and additional head losses on and nearby intersections in such shaped fractures,therefore it is necessary to understand and quantify them.In this study,both laboratory experiments and numerical simulations were performed to investigate the total head loss on and nearby the intersections as well as the local head loss exactly on the intersections,which were not usually paid sufficient attention or even ignored.The investigation results show that these two losses account for 29.17%-84.97%and 0-73.57%of the entire total head loss in a fracture,respectively.As a result,they should be necessarily considered for groundwater modeling in fractured rocks.Furthermore,both head losses become larger when aperture and flow rate increase and intersection length decreases.Particularly,the ratios of these two head losses to the entire total head loss in a fracture could be well statistically explained by power regression equations with variables of aperture,intersection length,and flow rates,both of which achieved high coefficients of determination.It could be feasible through this type of study to provide a way on how to adjust the groundwater head from those obtained by numerical simulations based on the traditional linear flow model.Finally,it is practicable and effective to implement the investigation approach combining laboratory experiments with numerical simulations for quantifying the head losses on and nearby the intersections between disc-shaped fractures.展开更多
Urban intersections without traffic signals are prone to accidents involving motor vehicles and pedestrians.Utilizing computer vision technology to detect pedestrians crossing the street can effectively mitigate the o...Urban intersections without traffic signals are prone to accidents involving motor vehicles and pedestrians.Utilizing computer vision technology to detect pedestrians crossing the street can effectively mitigate the occurrence of such accidents.Faced with the complex issue of pedestrian occlusion at signal-free intersections,this paper proposes a target detection model called Head feature And ENMS fusion Residual connection For CNN(HAERC).Specifically,the model includes a head feature module that detects occluded pedestrians by integrating their head features with the overall target.Additionally,to address the misselection caused by overlapping candidate boxes in two-stage target detection models,an Extended Non-Maximum Suppression classifier(ENMS)with expanded IoU thresholds is proposed.Finally,leveraging the CityPersons dataset and categorizing it into four classes based on occlusion levels(heavy,reasonable,partial,bare),the HAERC model is experimented on these classes and compared with baseline models.Experimental results demonstrate that HAERC achieves superior False Positives Per Image(FPPI)values of 46.64%,9.59%,9.43%,and 6.78%respectively for the four classes,outperforming all baseline models.The study concludes that the HAERC model effectively identifies occluded pedestrians in the complex environment of urban intersections without traffic signals,thereby enhancing safety for long-range driving at such intersections.展开更多
The steady-state or cyclic control problem for a simplified isolated traffic intersection is considered.The optimization problem for the green-red switching sequence is formulated with the help of a discrete-event max...The steady-state or cyclic control problem for a simplified isolated traffic intersection is considered.The optimization problem for the green-red switching sequence is formulated with the help of a discrete-event max-plus model.Two steady-state control problems are formulated:optimal steady-state with green duration constraints,and optimal steady-state control with lost time.In the case when the criterion is a strictly increasing,linear function of the queue lengths,the steady-state control problems can be solved analytically.The structure of constrained optimal steady-state traffic control is revealed,and the effect of the lost time on the optimal solution is illustrated.展开更多
Let X={X(t)∈Rd,t∈RN}be a centered space-time anisotropic Gaussian field with indices H=(H1,…,HN)∈(0,1)~N,where the components Xi(i=1,…,d)of X are independent,and the canonical metric√(E(Xi(t)-X...Let X={X(t)∈Rd,t∈RN}be a centered space-time anisotropic Gaussian field with indices H=(H1,…,HN)∈(0,1)~N,where the components Xi(i=1,…,d)of X are independent,and the canonical metric√(E(Xi(t)-Xi(s))2)1/2(i=1,…,d)is commensurate with■for s=(s1,…,sN),t=(t1,…,tN)∈R~N,αi∈(0,1],and with the continuous functionγ(·)satisfying certain conditions.First,the upper and lower bounds of the hitting probabilities of X can be derived from the corresponding generalized Hausdorff measure and capacity,which are based on the kernel functions depending explicitly onγ(·).Furthermore,the multiple intersections of the sample paths of two independent centered space-time anisotropic Gaussian fields with different distributions are considered.Our results extend the corresponding results for anisotropic Gaussian fields to a large class of space-time anisotropic Gaussian fields.展开更多
In deep underground mining,achieving stable support for roadways along with long service life is critical and the complex geological environment at such depths frequently presents a major challenge.Owing to the coupli...In deep underground mining,achieving stable support for roadways along with long service life is critical and the complex geological environment at such depths frequently presents a major challenge.Owing to the coupling action of multiple factors such as deep high stress,adjacent faults,cross-layer design,weak lithology,broken surrounding rock,variable cross-sections,wide sections up to 9.9 m,and clusters of nearby chambers,there was severe deformation and breakdown in the No.10 intersection of the roadway of large-scale variable cross-section at the−760 m level in a coal mine.As there are insufcient examples in engineering methods pertaining to the geological environment described above,the numerical calculation model was oversimplifed and support theory underdeveloped;therefore,it is imperative to develop an efective support system for the stability and sustenance of deep roadways.In this study,a quantitative analysis of the geological environment of the roadway through feld observations,borehole-scoping,and ground stress testing is carried out to establish the FLAC 3D variable cross-section crossing roadway model.This model is combined with the strain softening constitutive(surrounding rock)and Mohr–Coulomb constitutive(other deep rock formations)models to construct a compression arch mechanical model for deep soft rock,based on the quadratic parabolic Mohr criterion.An integrated control technology of bolting and grouting that is mainly composed of a high-strength hollow grouting cable bolt equipped with modifed cement grouting materials and a high-elongation cable bolt is developed by analyzing the strengthening properties of the surrounding rock before and after bolting,based on the Heok-Brown criterion.As a result of on-site practice,the following conclusions are drawn:(1)The plastic zone of the roof of the cross roadway is approximately 6 m deep in this environment,the tectonic stress is nearly 30 MPa,and the surrounding rock is severely fractured.(2)The deformation of the roadway progressively increases from small to large cross-sections,almost doubling at the largest cross-section.The plastic zone is concentrated at the top plate and shoulder and decreases progressively from the two sides to the bottom corner.The range of stress concentration at the sides of the intersection roadway close to the passageway is wider and higher.(3)The 7 m-thick reinforced compression arch constructed under the strengthening support scheme has a bearing capacity enhanced by 1.8 to 2.3 times and increase in thickness of the bearing structure by 1.76 times as compared to the original scheme.(4)The increase in the mechanical parameters c andφof the surrounding rock after anchoring causes a signifcant increase inσt;the pulling force of the cable bolt beneath the new grouting material is more than twice that of ordinary cement grout,and according to the test,the supporting stress feld shows that the 7.24 m surrounding rock is compacted and strengthened in addition to providing a strong foundation for the bolt(cable).On-site monitoring shows that the 60-days convergence is less than 30 mm,indicating that the stability control of the roadway is successful.展开更多
Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Cons...Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Considering that the motion trajectory of a vehicle at an intersection partly obeys the statistical law of historical data once its driving intention is determined,this paper proposes a long short-term memory based(LSTM-based)framework that combines intention prediction and trajectory prediction together.First,we build an intersection prior trajectories model(IPTM)by clustering and statistically analyzing a large number of prior traffic flow trajectories.The prior trajectories model with fitted probabilistic density is used to approximate the distribution of the predicted trajectory,and also serves as a reference for credibility evaluation.Second,we conduct the intention prediction through another LSTM model and regard it as a crucial cue for a trajectory forecast at the early stage.Furthermore,the predicted intention is also a key that is associated with the prior trajectories model.The proposed framework is validated on two publically released datasets,next generation simulation(NGSIM)and INTERACTION.Compared with other prediction methods,our framework is able to sample a trajectory from the estimated distribution,with its accuracy improved by about 20%.Finally,the credibility evaluation,which is based on the prior trajectories model,makes the framework more practical in the real-world applications.展开更多
Planning and decision-making technology at intersections is a comprehensive research problem in intelligent transportation systems due to the uncertainties caused by a variety of traffic participants.As wireless commu...Planning and decision-making technology at intersections is a comprehensive research problem in intelligent transportation systems due to the uncertainties caused by a variety of traffic participants.As wireless communication advances,vehicle infrastructure integrated algorithms designed for intersection planning and decision-making have received increasing attention.In this paper,the recent studies on the planning and decision-making technologies at intersections are primarily overviewed.The general planning and decision-making approaches are presented,which include graph-based approach,prediction base approach,optimization-based approach and machine learning based approach.Since connected autonomous vehicles(CAVs)is the future direction for the automated driving area,we summarized the evolving planning and decision-making methods based on vehicle infrastructure cooperative technologies.Both four-way signalized and unsignalized intersection(s)are investigated under purely automated driving traffic and mixed traffic.The study benefit from current strategies,protocols,and simulation tools to help researchers identify the presented approaches’challenges and determine the research gaps,and several remaining possible research problems that need to be solved in the future.展开更多
Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in Ind...Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system (ANFIS) to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections (in India, vehicles are driven on the left side of a road). Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver's decision (acceptedejected). ANFIS models are developed by using 80 % of the extracted data (total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles) and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.展开更多
Comparative analyses were conducted to compare the effects of the behavioral characteristics of the drivers of taxis and private cars on the capacity and safety of signalized intersections. Data were collected at sixt...Comparative analyses were conducted to compare the effects of the behavioral characteristics of the drivers of taxis and private cars on the capacity and safety of signalized intersections. Data were collected at sixteen signalized intersections in the Nanjing area in China. The risk-taking behaviors of the drivers of taxis and private cars were compared. The results suggest that 19.9% of taxi drivers have committed at least one of the identified risky behaviors, which is 2.37 times as high as that of the drivers of private cars(8.4%). The traffic conflicts technique was used to estimate the safety effects of taxis and private cars. The overall conflict rate for taxis is 21.4% higher than that for private cars, implying that taxis are more likely to be involved in conflicts. Almost all of the identified traffic conflicts can be attributed to certain levels of risk-taking behaviors committed by either taxi drivers or the drivers of private cars, and taxi drivers are more likely to be at fault in a conflict. Failure to yield to right-of-way and improper lane change is the leading causes of the conflicts in which taxis are at-fault. The research team further studied the effects of taxis on the queue discharge characteristics at signalized intersections. The results show that the presence of taxis significantly reduces both start-up lost time and saturation headways. The effects of taxis on saturation flow rates are dependent on the proportion of taxis in the discharge flow, and the saturation flow rates increase with the increase in the proportion of taxis. The adjustment factors for various proportions of taxis for different turning movements are then calculated to quantitatively evaluate the effects of taxis on the capacity of signalized intersections.展开更多
Aiming at prevalent violations of non-motorists at urban intersections in China, this paper intends to clarify the characteristics and risks of non-motorist violations at signalized intersections through questionnaire...Aiming at prevalent violations of non-motorists at urban intersections in China, this paper intends to clarify the characteristics and risks of non-motorist violations at signalized intersections through questionnaires and video recordings, which may serve as a basis for non-motorized vehicle management. It can help improve the traffic order and enhance the degree of safety at signalized intersections. To obtain the perception information, a questionaire survey on the Internet was conducted and 972 valid questionnaires were returned. It is found that academic degree contributes little to non-motorist violations, while electrical bicyclists have a relatively higher frequency of violations compared with bicyclists. The video data of 18 228 non-motorist behaviors indicate that the violation rate of all non-motorists is 26.5%; the number of conflicts reaches 1 938, among which violation conflicts account for 66.8%. The study shows that the violation rates and the violation behavior at three types of surveyed intersections are markedly different. It is also concluded that the conflict rates and the violation rates are positively correlated. Furthermore, signal violation, traveling in the wrong direction, and overspeeding to cross the intersection are the most dangerous among traffic violation behaviors.展开更多
Under deep and complex geological conditions,severe deformation occurs at intersection points of Y-type roadways with large cross sections during engineering projects in coal mines,especially at junction arches.Based ...Under deep and complex geological conditions,severe deformation occurs at intersection points of Y-type roadways with large cross sections during engineering projects in coal mines,especially at junction arches.Based on in-situ investigations and theoretical studies,we have summarized typical forms of destruction and identified high stress and unrestricted support at both sides of junction arch as its main causes.In this study,we also presented double-directional control bolt support technology for a large Y-type span intersection,applied to deep intersection engineering in the Jiahe Coal Mine,which has proved effective.展开更多
When the drivers approaching signalized intersections(onset of yellow signal),the drivers would enter into a zone,where they will be in uncertain mode assessing their capabilities to stop or cross the intersection.The...When the drivers approaching signalized intersections(onset of yellow signal),the drivers would enter into a zone,where they will be in uncertain mode assessing their capabilities to stop or cross the intersection.Therefore,any improper decision might lead to a right-angle or back-end crash.To avoid a right-angle collision,drivers apply the harsh brakes to stop just before the signalized intersection.But this may lead to a back-end crash when the following driver encounters the former's sudden stopping decision.This situation gets multifaceted when the traffic is heterogeneous,containing various types of vehicles.In order to reduce this issue,this study's primary objective is to identify the driving behaviour at signalized intersections based on the driving features(parameters).The secondary objective is to classify the outcome of driving behaviour(safe stopping and unsafe stopping)at the signalized intersection using a support vector machine(SVM)technique.Turning moments are used to identify the zones and label them accordingly for further classification.The classification of 50 instances is identified for training and testing using a 70%-30% rule resulted in an accuracy of 85% and 86%,respectively.Classification performance is further verified by random sampling using five cross-validation and 30 iterations,which gave an accuracy of 97% and 100% for training and testing.These results demonstrate that the proposed approach can help develop a pre-warning system to alert the drivers approaching signalized intersections,thus reducing back-end crash and accidents.展开更多
In order to improve the operational efficiency of heavy left-turn demand intersections,an optimal allocation model of an intersection with dynamic use of exit lanes for left turns(EFL)is proposed.The constraints of se...In order to improve the operational efficiency of heavy left-turn demand intersections,an optimal allocation model of an intersection with dynamic use of exit lanes for left turns(EFL)is proposed.The constraints of setting EFL are analyzed,including the number and length of reverse variable lanes,flow direction constraints,and signal constraints,etc.The constraints and control variables are combined in a unified framework for simultaneous optimization.The objective functions are defined as the average delay and left-turn capacity of an intersection.The model is solved by a non-dominated genetic algorithm(NSGA-Ⅱ).The results show that after the optimal allocation of EFL,the average vehicle delays of the intersection can be reduced by 14.9%and left-turn capacity can be increased by 19.3%.The effectiveness of the optimal allocation model of EFL is demonstrated.展开更多
基金The National Key Research and Development Program of China(No.2022YFB4300304).
摘要To address the challenge of distinguishing subjective aggressive driving(initiated by drivers)from hazardous behaviors caused by external cyberattacks,this study proposes an innovative intent recognition framework named Intent-Decipher.By integrating the information credibility outputted by an intrusion detection system(IDS)into a security-aware inverse reinforcement learning(SA-IRL)model,the framework infers the reward function behind vehicle behaviors and classifies three key driving intents:normal,aggressive,and malicious.Experiments were conducted on a semi-synthetic dataset containing 20000 trajectories.Results show that Intent-Decipher significantly outperforms baseline methods in classification accuracy,achieving a macro-average F1-score of 0.94.Notably,Intent-Decipher excels at differentiating subjective aggressive driving from attack-induced behaviors:its F1-score for identifying malicious attack-induced(MAI)intent reaches 0.90,an absolute improvement of 0.16 compared with the standard inverse reinforcement learning(IRL)model(which lacks security awareness and only achieves an F1-score of 0.74).
基金National Science and Technology Council,Taiwan,for financially supporting this research(grant No.NSTC 114-2221-E-018-003)the Ministry of Education’s Teaching Practice Research Program,Taiwan(PSK1142780).
摘要Urban intersections contain severe blind zones where buildings and roadside obstacles block lineof-sight sensing,limiting the ability of autonomous vehicles to anticipate hidden hazards.This paper presents an urban-intersection-oriented non-line-of-sight(NLOS)perception framework that exploits specular reflections from building surfaces using 77 GHz frequency-modulated continuous-wave(FMCW)automotive radar.All evaluations are conducted in a MATLAB-based simulation environment that models intersection geometry,building-induced occlusions,and specular reflection-assisted propagation,and generates 77-GHz FMCW radar echoes under controllable interference;real-world validation with measured radar data and richer multipath/material modeling is planned as future work.To improve robustness under noisy intersection interference,we propose a deep-learning-based mitigation module that restores corrupted radar echoes at the chirp level using a compact AlexNet-derived 1D regression backbone,with minimal architectural changes that insert a residual block after conv2 and apply batch normalization to enhance training stability and suppress interference while preserving informative echo characteristics.The restored echoes are then processed by conventional estimation steps to obtain range and azimuth-related angles.Under severe interference(Noise Factor=3.0),unmitigated measurements exhibit large errors(root-mean-square error(RMSE)=5.48 m/18.95°/10.77°for range/angle/azimuth deviation).Conventional AlexNet-based mitigation reduces these errors to 0.75 m/0.83°/0.93°,while the proposed improved AlexNet further reduces them to 0.56 m/0.46°/0.73°.The results demonstrate improved signal stability and measurement accuracy,supporting the potential practicality of low-cost NLOS perception in simulation for safety-critical autonomous driving at occluded urban intersections,subject to future real-world validation.
基金supported by the Japan Society for the Promotion of Science(JSPS)Grants-in-Aid for Scientific Research(C)23K03898.
摘要Traffic at urban intersections frequently encounters unexpected obstructions,resulting in congestion due to uncooperative and priority-based driving behavior.This paper presents an optimal right-turn coordination system for Connected and Automated Vehicles(CAVs)at single-lane intersections,particularly in the context of left-hand side driving on roads.The goal is to facilitate smooth right turns for certain vehicles without creating bottlenecks.We consider that all approaching vehicles share relevant information through vehicular communications.The Intersection Coordination Unit(ICU)processes this information and communicates the optimal crossing or turning times to the vehicles.The primary objective of this coordination is to minimize overall traffic delays,which also helps improve the fuel consumption of vehicles.By considering information from upcoming vehicles at the intersection,the coordination system solves an optimization problem to determine the best timing for executing right turns,ultimately minimizing the total delay for all vehicles.The proposed coordination system is evaluated at a typical urban intersection,and its performance is compared to traditional traffic systems.Numerical simulation results indicate that the proposed coordination system significantly enhances the average traffic speed and fuel consumption compared to the traditional traffic system in various scenarios.
摘要This paper aims to enhance highway traffic efficiency by integrating a project focused on signal timing optimization at highway intersections.Supported by intelligent technologies,a reasonable optimization system is constructed.Practical application demonstrates that the signal timing optimization at highway intersections under this system yields significant results,substantially improving traffic efficiency.This provides a reference for subsequent signal timing optimization at highway intersections,aligning with the development needs of the intelligent transportation context.
摘要The control of traffic flows on urban roads intersections through the traffic control signals is very important,not only does the jammed traffic statement valuably relieve and the ratio of the traffic availability increase,but also the traffic accidents evidently decrease.In this paper,an adaptive algorithm of traffic control signals on the urban roads intersections is designed in,this new algorithm can actively adjust the concrete control times of the traffic control signals based on the perceiving information of the waiting vehicles in real time,then the dynamic balance between the traffic control signals and the traffic flows can be realized.Furthermore,through experiment testing and demonstrating,this adaptive algorithm expresses some fine performances,it also shows good application prospect in the field of smart city.
基金funded by Sichuan International Studies University within the framework of the research project“Oulipian Experimentalism and Spatial Structure in the Travel Narratives of Jacques Roubaud”(sisu202008).
摘要This article explores the intersections of Buddhism,Daoism,and contemporary French literary practice in the study of the everyday(quotidien).Since the 1980s,French literature has increasingly shifted its focus from the exotic to the mundane,engaging with theoretical frameworks developed by scholars such as Henri Lefebvre and Michel de Certeau.Drawing on Buddhist notions of emptiness and dependent arising,as well as Daoist principles of yin-yang interdependence,the article bridges Eastern and Western philosophies to demonstrate the everyday not as a static or trivial backdrop,but as a dynamic and transformative space.It further examines how representations of daily life in the works of Georges Perec and Jacques Roubaud employ the meticulous documentation of mundane details to uncover hidden patterns,rhythms,and structures of human experience.Through literary fieldwork,Perec and Roubaud challenge conventional perceptions of the everyday,unveiling its depth,complexity,and potential for reinvention.
基金supported by the National Basic Research Program of China(973 Program)(2010CB428801,2010CB428804)National High-tech R&D Program of China(863 Program)(2011AA050105)+1 种基金National Science Foundation of China(40972166)National Science and Technology Major Project of China(2011ZX 05060-005).
摘要The discrete fracture network model is a powerful tool for fractured rock mass fluid flow simulations and supports safety assessments of coal mine hazards such as water inrush.Intersection analysis,which identifies all pairs of intersected fractures(the basic components composing the connectivity of a network),is one of its crucial procedures.This paper attempts to improve intersection analysis through parallel computing.Considering a seamless interfacing with other procedures in modeling,two algorithms are designed and presented,of which one is a completely independent parallel procedure with some redundant computations and the other is an optimized version with reduced redundancy.A numerical study indicates that both of the algorithms are practical and can significantly improve the computational performance of intersection analysis for large-scale simulations.Moreover,the preferred application conditions for the two algorithms are also discussed.
基金supported by National Key Research and Development Program of China(No.2020 YFC1807100,No.2019YFC1806205)National Natural Science Foundation of China(No.41572240)。
摘要Discrete fracture models are used for investigating precise processes of groundwater flow in fractured rocks,while a disc-shaped parallel-plates model for a single fracture is more reasonable and efficient for computational treatments.The flow velocity has a large spatial differentiation which is more likely to produce non-linear flow and additional head losses on and nearby intersections in such shaped fractures,therefore it is necessary to understand and quantify them.In this study,both laboratory experiments and numerical simulations were performed to investigate the total head loss on and nearby the intersections as well as the local head loss exactly on the intersections,which were not usually paid sufficient attention or even ignored.The investigation results show that these two losses account for 29.17%-84.97%and 0-73.57%of the entire total head loss in a fracture,respectively.As a result,they should be necessarily considered for groundwater modeling in fractured rocks.Furthermore,both head losses become larger when aperture and flow rate increase and intersection length decreases.Particularly,the ratios of these two head losses to the entire total head loss in a fracture could be well statistically explained by power regression equations with variables of aperture,intersection length,and flow rates,both of which achieved high coefficients of determination.It could be feasible through this type of study to provide a way on how to adjust the groundwater head from those obtained by numerical simulations based on the traditional linear flow model.Finally,it is practicable and effective to implement the investigation approach combining laboratory experiments with numerical simulations for quantifying the head losses on and nearby the intersections between disc-shaped fractures.
基金Beijing Natural Science Foundation(9234025)National Social Science Fund Project of China(21FGLB014)Humanity and Social Science Youth Foundation of Ministry of Education of China(21YJC630094).
摘要Urban intersections without traffic signals are prone to accidents involving motor vehicles and pedestrians.Utilizing computer vision technology to detect pedestrians crossing the street can effectively mitigate the occurrence of such accidents.Faced with the complex issue of pedestrian occlusion at signal-free intersections,this paper proposes a target detection model called Head feature And ENMS fusion Residual connection For CNN(HAERC).Specifically,the model includes a head feature module that detects occluded pedestrians by integrating their head features with the overall target.Additionally,to address the misselection caused by overlapping candidate boxes in two-stage target detection models,an Extended Non-Maximum Suppression classifier(ENMS)with expanded IoU thresholds is proposed.Finally,leveraging the CityPersons dataset and categorizing it into four classes based on occlusion levels(heavy,reasonable,partial,bare),the HAERC model is experimented on these classes and compared with baseline models.Experimental results demonstrate that HAERC achieves superior False Positives Per Image(FPPI)values of 46.64%,9.59%,9.43%,and 6.78%respectively for the four classes,outperforming all baseline models.The study concludes that the HAERC model effectively identifies occluded pedestrians in the complex environment of urban intersections without traffic signals,thereby enhancing safety for long-range driving at such intersections.
摘要The steady-state or cyclic control problem for a simplified isolated traffic intersection is considered.The optimization problem for the green-red switching sequence is formulated with the help of a discrete-event max-plus model.Two steady-state control problems are formulated:optimal steady-state with green duration constraints,and optimal steady-state control with lost time.In the case when the criterion is a strictly increasing,linear function of the queue lengths,the steady-state control problems can be solved analytically.The structure of constrained optimal steady-state traffic control is revealed,and the effect of the lost time on the optimal solution is illustrated.
基金supported by the National Natural Science Foundation of China(12371150,11971432)the Natural Science Foundation of Zhejiang Province(LY21G010003)+2 种基金the Management Project of"Digital+"Discipline Construction of Zhejiang Gongshang University(SZJ2022A012,SZJ2022B017)the Characteristic&Preponderant Discipline of Key Construction Universities in Zhejiang Province(Zhejiang Gongshang University-Statistics)the Scientific Research Projects of Universities in Anhui Province(2022AH050955)。
摘要Let X={X(t)∈Rd,t∈RN}be a centered space-time anisotropic Gaussian field with indices H=(H1,…,HN)∈(0,1)~N,where the components Xi(i=1,…,d)of X are independent,and the canonical metric√(E(Xi(t)-Xi(s))2)1/2(i=1,…,d)is commensurate with■for s=(s1,…,sN),t=(t1,…,tN)∈R~N,αi∈(0,1],and with the continuous functionγ(·)satisfying certain conditions.First,the upper and lower bounds of the hitting probabilities of X can be derived from the corresponding generalized Hausdorff measure and capacity,which are based on the kernel functions depending explicitly onγ(·).Furthermore,the multiple intersections of the sample paths of two independent centered space-time anisotropic Gaussian fields with different distributions are considered.Our results extend the corresponding results for anisotropic Gaussian fields to a large class of space-time anisotropic Gaussian fields.
基金supported by the National Natural Science Foundation of China(Grant Nos.52074296,52004286)the China Postdoctoral Science Foundation(Grant Nos.2020T130701,2019M650895).
摘要In deep underground mining,achieving stable support for roadways along with long service life is critical and the complex geological environment at such depths frequently presents a major challenge.Owing to the coupling action of multiple factors such as deep high stress,adjacent faults,cross-layer design,weak lithology,broken surrounding rock,variable cross-sections,wide sections up to 9.9 m,and clusters of nearby chambers,there was severe deformation and breakdown in the No.10 intersection of the roadway of large-scale variable cross-section at the−760 m level in a coal mine.As there are insufcient examples in engineering methods pertaining to the geological environment described above,the numerical calculation model was oversimplifed and support theory underdeveloped;therefore,it is imperative to develop an efective support system for the stability and sustenance of deep roadways.In this study,a quantitative analysis of the geological environment of the roadway through feld observations,borehole-scoping,and ground stress testing is carried out to establish the FLAC 3D variable cross-section crossing roadway model.This model is combined with the strain softening constitutive(surrounding rock)and Mohr–Coulomb constitutive(other deep rock formations)models to construct a compression arch mechanical model for deep soft rock,based on the quadratic parabolic Mohr criterion.An integrated control technology of bolting and grouting that is mainly composed of a high-strength hollow grouting cable bolt equipped with modifed cement grouting materials and a high-elongation cable bolt is developed by analyzing the strengthening properties of the surrounding rock before and after bolting,based on the Heok-Brown criterion.As a result of on-site practice,the following conclusions are drawn:(1)The plastic zone of the roof of the cross roadway is approximately 6 m deep in this environment,the tectonic stress is nearly 30 MPa,and the surrounding rock is severely fractured.(2)The deformation of the roadway progressively increases from small to large cross-sections,almost doubling at the largest cross-section.The plastic zone is concentrated at the top plate and shoulder and decreases progressively from the two sides to the bottom corner.The range of stress concentration at the sides of the intersection roadway close to the passageway is wider and higher.(3)The 7 m-thick reinforced compression arch constructed under the strengthening support scheme has a bearing capacity enhanced by 1.8 to 2.3 times and increase in thickness of the bearing structure by 1.76 times as compared to the original scheme.(4)The increase in the mechanical parameters c andφof the surrounding rock after anchoring causes a signifcant increase inσt;the pulling force of the cable bolt beneath the new grouting material is more than twice that of ordinary cement grout,and according to the test,the supporting stress feld shows that the 7.24 m surrounding rock is compacted and strengthened in addition to providing a strong foundation for the bolt(cable).On-site monitoring shows that the 60-days convergence is less than 30 mm,indicating that the stability control of the roadway is successful.
基金partly supported by the National Natural Science Foundation of China(61903034,U1913203,61973034,91120003)the Program for Changjiang Scholars and Innovative Research Team in University(IRT-16R06,T2014224)+1 种基金China Postdoctoral Science Foundation funded project(2019TQ0035)Beijing Institute of Technology Research Fund Program for Young Scholars。
摘要Intersections are quite important and complex traffic scenarios,where the future motion of surrounding vehicles is an indispensable reference factor for the decision-making or path planning of autonomous vehicles.Considering that the motion trajectory of a vehicle at an intersection partly obeys the statistical law of historical data once its driving intention is determined,this paper proposes a long short-term memory based(LSTM-based)framework that combines intention prediction and trajectory prediction together.First,we build an intersection prior trajectories model(IPTM)by clustering and statistically analyzing a large number of prior traffic flow trajectories.The prior trajectories model with fitted probabilistic density is used to approximate the distribution of the predicted trajectory,and also serves as a reference for credibility evaluation.Second,we conduct the intention prediction through another LSTM model and regard it as a crucial cue for a trajectory forecast at the early stage.Furthermore,the predicted intention is also a key that is associated with the prior trajectories model.The proposed framework is validated on two publically released datasets,next generation simulation(NGSIM)and INTERACTION.Compared with other prediction methods,our framework is able to sample a trajectory from the estimated distribution,with its accuracy improved by about 20%.Finally,the credibility evaluation,which is based on the prior trajectories model,makes the framework more practical in the real-world applications.
摘要Planning and decision-making technology at intersections is a comprehensive research problem in intelligent transportation systems due to the uncertainties caused by a variety of traffic participants.As wireless communication advances,vehicle infrastructure integrated algorithms designed for intersection planning and decision-making have received increasing attention.In this paper,the recent studies on the planning and decision-making technologies at intersections are primarily overviewed.The general planning and decision-making approaches are presented,which include graph-based approach,prediction base approach,optimization-based approach and machine learning based approach.Since connected autonomous vehicles(CAVs)is the future direction for the automated driving area,we summarized the evolving planning and decision-making methods based on vehicle infrastructure cooperative technologies.Both four-way signalized and unsignalized intersection(s)are investigated under purely automated driving traffic and mixed traffic.The study benefit from current strategies,protocols,and simulation tools to help researchers identify the presented approaches’challenges and determine the research gaps,and several remaining possible research problems that need to be solved in the future.
基金partially funded by Department of Science and Technology (DST), Govt. of Indiaproject SR/ FTP/ETA-61/2010
摘要Gap acceptance theory is broadly used for evaluating unsignalized intersections in developed coun tries. Intersections with no specific priority to any move ment, known as uncontrolled intersections, are common in India. Limited priority is observed at a few intersections, where priorities are perceived by drivers based on geom etry, traffic volume, and speed on the approaches of intersection. Analyzing such intersections is complex because the overall traffic behavior is the result of drivers, vehicles, and traffic flow characteristics. Fuzzy theory has been widely used to analyze similar situations. This paper describes the application of adaptive neurofuzzy interface system (ANFIS) to the modeling of gap acceptance behavior of rightturning vehicles at limited priority Tintersections (in India, vehicles are driven on the left side of a road). Field data are collected using video cameras at four Tintersections having limited priority. The data extracted include gap/lag, subject vehicle type, conflicting vehicle type, and driver's decision (acceptedejected). ANFIS models are developed by using 80 % of the extracted data (total data observations for major road right turning vehicles are 722 and 1,066 for minor road right turning vehicles) and remaining are used for model vali dation. Four different combinations of input variables are considered for major and minor road right turnings sepa rately. Correct prediction by ANFIS models ranges from 75.17 % to 82.16 % for major road right turning and 87.20 % to 88.62 % for minor road right turning. Themodels developed in this paper can be used in the dynamic estimation of gap acceptance in traffic simulation models.
基金Projects(51322810,50908050)supported by the National Natural Science Foundation of China
摘要Comparative analyses were conducted to compare the effects of the behavioral characteristics of the drivers of taxis and private cars on the capacity and safety of signalized intersections. Data were collected at sixteen signalized intersections in the Nanjing area in China. The risk-taking behaviors of the drivers of taxis and private cars were compared. The results suggest that 19.9% of taxi drivers have committed at least one of the identified risky behaviors, which is 2.37 times as high as that of the drivers of private cars(8.4%). The traffic conflicts technique was used to estimate the safety effects of taxis and private cars. The overall conflict rate for taxis is 21.4% higher than that for private cars, implying that taxis are more likely to be involved in conflicts. Almost all of the identified traffic conflicts can be attributed to certain levels of risk-taking behaviors committed by either taxi drivers or the drivers of private cars, and taxi drivers are more likely to be at fault in a conflict. Failure to yield to right-of-way and improper lane change is the leading causes of the conflicts in which taxis are at-fault. The research team further studied the effects of taxis on the queue discharge characteristics at signalized intersections. The results show that the presence of taxis significantly reduces both start-up lost time and saturation headways. The effects of taxis on saturation flow rates are dependent on the proportion of taxis in the discharge flow, and the saturation flow rates increase with the increase in the proportion of taxis. The adjustment factors for various proportions of taxis for different turning movements are then calculated to quantitatively evaluate the effects of taxis on the capacity of signalized intersections.
基金The National Key Technology R&D Program during the 11th Five-Year Plan Period(No.2009BAG13A05)the National Natural Science Foundation of China(No.51078086)
摘要Aiming at prevalent violations of non-motorists at urban intersections in China, this paper intends to clarify the characteristics and risks of non-motorist violations at signalized intersections through questionnaires and video recordings, which may serve as a basis for non-motorized vehicle management. It can help improve the traffic order and enhance the degree of safety at signalized intersections. To obtain the perception information, a questionaire survey on the Internet was conducted and 972 valid questionnaires were returned. It is found that academic degree contributes little to non-motorist violations, while electrical bicyclists have a relatively higher frequency of violations compared with bicyclists. The video data of 18 228 non-motorist behaviors indicate that the violation rate of all non-motorists is 26.5%; the number of conflicts reaches 1 938, among which violation conflicts account for 66.8%. The study shows that the violation rates and the violation behavior at three types of surveyed intersections are markedly different. It is also concluded that the conflict rates and the violation rates are positively correlated. Furthermore, signal violation, traveling in the wrong direction, and overspeeding to cross the intersection are the most dangerous among traffic violation behaviors.
基金supported by the National Basic Research Program of China (No.2006CB202200)the Major Program of the National Natural Science Foundation of China (No.50490270)the Innovative Team Development Project of the Ministry of Education of China (No.IRT0656)
摘要Under deep and complex geological conditions,severe deformation occurs at intersection points of Y-type roadways with large cross sections during engineering projects in coal mines,especially at junction arches.Based on in-situ investigations and theoretical studies,we have summarized typical forms of destruction and identified high stress and unrestricted support at both sides of junction arch as its main causes.In this study,we also presented double-directional control bolt support technology for a large Y-type span intersection,applied to deep intersection engineering in the Jiahe Coal Mine,which has proved effective.
基金supported by Universiti Brunei Darussalam under the University Bursary ScholarshipUniversiti Brunei Darussalam's Research Grants(Nos,UBD/PNC2/2/RG/1(311)and UBD/RSCH/1.11/FICBF/2018/002)。
摘要When the drivers approaching signalized intersections(onset of yellow signal),the drivers would enter into a zone,where they will be in uncertain mode assessing their capabilities to stop or cross the intersection.Therefore,any improper decision might lead to a right-angle or back-end crash.To avoid a right-angle collision,drivers apply the harsh brakes to stop just before the signalized intersection.But this may lead to a back-end crash when the following driver encounters the former's sudden stopping decision.This situation gets multifaceted when the traffic is heterogeneous,containing various types of vehicles.In order to reduce this issue,this study's primary objective is to identify the driving behaviour at signalized intersections based on the driving features(parameters).The secondary objective is to classify the outcome of driving behaviour(safe stopping and unsafe stopping)at the signalized intersection using a support vector machine(SVM)technique.Turning moments are used to identify the zones and label them accordingly for further classification.The classification of 50 instances is identified for training and testing using a 70%-30% rule resulted in an accuracy of 85% and 86%,respectively.Classification performance is further verified by random sampling using five cross-validation and 30 iterations,which gave an accuracy of 97% and 100% for training and testing.These results demonstrate that the proposed approach can help develop a pre-warning system to alert the drivers approaching signalized intersections,thus reducing back-end crash and accidents.
基金The Natural Science Foundation of Jilin Province(No.20190201107JC)the National Key Research and Development Program of China(No.2019YFB1600500)。
摘要In order to improve the operational efficiency of heavy left-turn demand intersections,an optimal allocation model of an intersection with dynamic use of exit lanes for left turns(EFL)is proposed.The constraints of setting EFL are analyzed,including the number and length of reverse variable lanes,flow direction constraints,and signal constraints,etc.The constraints and control variables are combined in a unified framework for simultaneous optimization.The objective functions are defined as the average delay and left-turn capacity of an intersection.The model is solved by a non-dominated genetic algorithm(NSGA-Ⅱ).The results show that after the optimal allocation of EFL,the average vehicle delays of the intersection can be reduced by 14.9%and left-turn capacity can be increased by 19.3%.The effectiveness of the optimal allocation model of EFL is demonstrated.