Connected automated vehicles(CAVs)rely heavily on intelligent algorithms and remote sensors.If the control center or on-board sensors are under cyber-attack due to the security vulnerability of wireless communication,...Connected automated vehicles(CAVs)rely heavily on intelligent algorithms and remote sensors.If the control center or on-board sensors are under cyber-attack due to the security vulnerability of wireless communication,it can cause significant damage to CAVs or passengers.The primary objective of this study is to model cyberattacked traffic flow and evaluate the impacts of cyber-attack on the traffic system filled with CAVs in a connected environment.Based on the analysis on environmental perception system and possible cyber-attacks on sensors,a novel lane-changing model for CAVs is proposed and multiple traffic scenarios for cyber-attacks are designed.The impact of the proportion of cyber-attacked vehicles and the severity of the cyber-attack on the lanechanging process is then quantitatively analyzed.The evaluation indexes include spatio-temporal evolution of average speed,spatial distribution of selected lane-changing gaps,lane-changing rate distribution,lane-changing preparation search time,efficiency and safety.Finally,the numerical simulation results show that the freeway traffic near an off-ramp is more sensitive to the proportion of cyber-attacked vehicles than to the severity of the cyber-attack.Also,when the traffic system is under cyber-attack,more unsafe back gaps are chosen for lane-changing,especially in the center lane.Therefore,more lane-changing maneuvers are concentrated on approaching the off-ramp,causing severe congestions and potential rear-end collisions.In addition,as the number of cyber-attacked vehicles and the severity of cyber-attacks increase,the road capacity and safety level will rapidly decrease.The results of this study can provide a theoretical basis for accident avoidance and efficiency improvement for the design of CAVs and management of automated highway systems.展开更多
In this article,lane change models for mixed traffic flow under cooperative adaptive cruise control(CACC)platoon formation are established.The analysis begins by examining the impact of lane changes on traffic flow st...In this article,lane change models for mixed traffic flow under cooperative adaptive cruise control(CACC)platoon formation are established.The analysis begins by examining the impact of lane changes on traffic flow stability.The influences of various factors such as lane change locations,timing,and the current traffic state on stability are discussed.In this analysis,it is assumed that the lane change location and the entry position in the adjacent lane have already been selected,without considering the specific intention behind the lane change.The speeds of the involved vehicles are adjusted based on an existing lane change model,and various conditions are analyzed for traffic flow disturbances,including duration,shock amplitude,and driving delays.Numerical calculations are provided to illustrate these effects.Additionally,traffic flow stability is factored into the lane change decision-making process.By incorporating disturbances to the fleet into the lane change income model,both a lane change intention model and a lane change execution model are constructed.These models are then compared with a model that does not account for stability,leading to the corresponding conclusions.展开更多
Mandatory lane change(MLC)is likely to cause traffic oscillations,which have a negative impact on traffic efficiency and safety.There is a rapid increase in research on mandatory lane change decision(MLCD)prediction,w...Mandatory lane change(MLC)is likely to cause traffic oscillations,which have a negative impact on traffic efficiency and safety.There is a rapid increase in research on mandatory lane change decision(MLCD)prediction,which can be categorized into physics-based models and machine-learning models.Both types of models have their advantages and disadvantages.To obtain a more advanced MLCD prediction method,this study proposes a hybrid architecture,which combines the Evolutionary Game Theory(EGT)based model(considering data efficient and interpretable)and the Machine Learning(ML)based model(considering high prediction accuracy)to model the mandatory lane change decision of multi-style drivers(i.e.EGTML framework).Therefore,EGT is utilized to introduce physical information,which can describe the progressive cooperative interactions between drivers and predict the decision-making of multi-style drivers.The generalization of the EGTML method is further validated using four machine learning models:ANN,RF,LightGBM,and XGBoost.The superiority of EGTML is demonstrated using real-world data(i.e.,Next Generation SIMulation,NGSIM).The results of sensitivity analysis show that the EGTML model outperforms the general ML model,especially when the data is sparse.展开更多
This paper deals mainly with the influence of lane changing behaviours on the stability of two-lane traffic flow under a periodic boundary condition. Following the description of an optimal velocity model for two vehi...This paper deals mainly with the influence of lane changing behaviours on the stability of two-lane traffic flow under a periodic boundary condition. Following the description of an optimal velocity model for two vehicle groups and the derivation of their stability conditions, the feedback signals, which involve information about vehicles from both lanes acting on the two-lane traffic system, are introduced into the optimal velocity model. The control signals play a role in alleviating the traffic jam only if the traffic state is in congestion, and their role will vanish if the traffic state is in the steady state. The numerical simulations show that lane changing behaviours can break the steady state of two-lane traffic flow and aggravate the traffic disturbance, but the control method would successfully suppress the traffic jam eventually, which implies that the conclusions obtained here have certain theoretical and practical significance.展开更多
In this paper, a new car-following model is presented, taking into account the anticipation of potential lane changing by the leading vehicle. The stability condition of the model is obtained by using the linear stabi...In this paper, a new car-following model is presented, taking into account the anticipation of potential lane changing by the leading vehicle. The stability condition of the model is obtained by using the linear stability theory. The modified Korteweg-de Vries （KdV） equation is constructed and solved, and three types of traffic flow in the headway-sensitivity space, namely stable, metastable and unstable ones, are classified. Both the analytical and simu- lation results show that anxiety about lane changing does indeed have an influence on driving behavior and that a consideration of lane changing probability in the car-following model could stabilize traffic flows. The quantitative relationship between stability improvement and lane changing probability is also investigated.展开更多
Accidents are in rising mode and became the main problem all over the world especially in Malaysia as the reasons including the condition of the road, driver＇s reaction and the road environment. Actually, those condi...Accidents are in rising mode and became the main problem all over the world especially in Malaysia as the reasons including the condition of the road, driver＇s reaction and the road environment. Actually, those condition also factors to execute the lane changing which experienced by all drivers such as in U-turn road segment. In approaching U-turn segment, drivers needed to make a decision whenever any disruption in front of them such as merging vehicle because they have their own perspective and desire. For that purpose, this research is focusing on the reaction of the driver in approaching the U-turn facility road segment especially in speed （V）, reaction time （RT） and distance where from those parameters and their relationships, the statistical model was developed and used in estimating the safe distances to execute the lane changing from the merging vehicle. The data were taken from the field and driving simulator to come out with the raw data. The field data were from video recording that has been used to simulate the driving simulator. Therefore, through the relationship between the RT, speed （V） and distance of the subject vehicle to the merging vehicle, the statistical model has been developed with the equation D.4MVUT = （13.448 ＋ 1.410 RT- 0.075 V）.展开更多
Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,auton...Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.展开更多
In this paper, we study the effect of moving bottlenecks on traffic flow. The full velocity difference （FVD） model is extended to the traffic flow on a two-lane highway, and new lane changing rule is proposed to rep...In this paper, we study the effect of moving bottlenecks on traffic flow. The full velocity difference （FVD） model is extended to the traffic flow on a two-lane highway, and new lane changing rule is proposed to reproduce the vehicular lane changing behavior. Using this model, we derive the fundamental current-density diagrams for the traffic flow with the effect of moving bottleneck. Moreover, typical time-space diagram for a two-lane highway shows the formation and dissipation of a moving bottleneck. Results demonstrate that the effect of moving bottleneck enlarges with the increase of traffic density, but the effect can be reduced by increasing the maximum velocity of heavy truck. The effects of multiple moving bottlenecks under different conditions are investigated. The effect becomes more remarkable when the coupling effect of multiple moving bottlenecks occurs.展开更多
In a multi-lane area,the increasing randomness of lane changes contributes to traffic insecurity and local traffic flow instability.A study on safe lane shifting activity that focuses on threat assessment under real-t...In a multi-lane area,the increasing randomness of lane changes contributes to traffic insecurity and local traffic flow instability.A study on safe lane shifting activity that focuses on threat assessment under real-time knowledge is necessary to enhance smooth vehicle flow.This paper proposed amore comprehensive lane changing guidance rule to investigate the status of surrounding vehicles to accommodate future vehicle-on-road collaborative environments based on these parameters 1)lane change demand and 2)treat assessment function.The collaborative relationships between vehicles are analyzed using a cellular automata model based on their location,velocity,and acceleration.We analyze and examine the relationship between the number of lanes and traffic flow when the road capacity is heavily mined via intelligent lane changing.Our analysis can further provide theoretical guidance for the selection of road expansion mode.Our proposed STCA-L is compared based on the average speed,average flow,lane changing frequency,spatial and temporal pattern of STCA,STCA-I,and STCA-S,and STCA-M under different vehicle densities.The numerical simulation results show that our proposed STCA-L provides themost flexible lane changing guidance in the multi-lanes road.Moreover,the simulated results show that the exponential growth of physical space cannot provide the corresponding increase in the average flow of vehicles.展开更多
In this paper,it studies the problem of trajectory planning and tracking for lane changing behavior of vehicle in automatic highway systems. Based on the model of yaw angle acceleration with positive and negative trap...In this paper,it studies the problem of trajectory planning and tracking for lane changing behavior of vehicle in automatic highway systems. Based on the model of yaw angle acceleration with positive and negative trapezoid constraint,by analyzing the variation laws of yaw motion of vehicle during a lane changing maneuver,the reference model of desired yaw angle and yaw rate for lane changing is generated. According to the yaw angle model,the vertical and horizontal coordinates of trajectory for vehicle lane change are calculated. Assuming that the road curvature is a constant,the difference and associations between two scenarios are analyzed,the lane changing maneuvers occurred on curve road and straight road,respectively. On this basis,it deduces the calculation method of desired yaw angle for lane changing on circular road. Simulation result shows that,it is different from traditional lateral acceleration planning method with the trapezoid constraint,by applying the trapezoidal yaw acceleration reference model proposed in this paper, the resulting expected yaw angular acceleration is continuous,and the step tracking for steering angle is not needed to implement. Due to the desired yaw model is direct designed based on the variation laws of raw movement of vehicle during a lane changing maneuver, rather than indirectly calculated from the trajectory model for lane changing, the calculation steps are simplified.展开更多
This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed ra...This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed rapidly,moving from basic driver-assistance systems(Level 1)to fully autonomous capabilities(Level 5).Central to this advancement are two key functionalities:Lane-Change Maneuvers(LCM)and Adaptive Cruise Control(ACC).In this study,a detailed simulation environment is created to replicate the road network between Nantun andWuri on National Freeway No.1 in Taiwan.The MPC controller is deployed to optimize vehicle trajectories,ensuring safe and efficient navigation.Simulated onboard sensors,including vehicle cameras and millimeterwave radar,are used to detect and respond to dynamic changes in the surrounding environment,enabling real-time decision-making for LCM and ACC.The simulation resultshighlight the superiority of the MPC-based approach in maintaining safe distances,executing controlled lane changes,and optimizing fuel efficiency.Specifically,the MPC controller effectively manages collision avoidance,reduces travel time,and contributes to smoother traffic flow compared to traditional path planning methods.These findings underscore the potential of MPC to enhance the reliability and safety of autonomous driving in complex traffic scenarios.Future research will focus on validating these results through real-world testing,addressing computational challenges for real-time implementation,and exploring the adaptability of MPC under various environmental conditions.This study provides a significant step towards achieving safer and more efficient autonomous vehicle navigation,paving the way for broader adoption of MPC in AV systems.展开更多
Lane changing is common in driving.Thus,the possibility of traffic accidents occurring during lane changes is high given the complexity of this process.One of the primary objectives of intelligent driving is to increa...Lane changing is common in driving.Thus,the possibility of traffic accidents occurring during lane changes is high given the complexity of this process.One of the primary objectives of intelligent driving is to increase a vehicle’s behavior,making it more similar to that of a real driver.This study proposes a decision-making framework based on deep reinforcement learning(DRL)in a lane-changing scenario,which seeks to find a driving strategy that simultaneously considers the expected lane-changing risks and gains.First,a fuzzy logic lane-changing controller is designed.It outputs the corresponding safety and lane-change gain weights by inputting relevant driving parameters.Second,the obtained weights are brought into the constructed reward function of DRL.The model parameters are designed and trained on the basis of lane-changing behavior.Finally,we conducted experiments in a simulator to evaluate the performance of our developed algorithm in urban scenarios.To visualize and validate the estimated driving intentions,lane-changing strategies were tested under four scenarios.The results show that the average improvement in travel efficiency in the four scenarios is 19%.In addition,the average accident rate in the four scenarios increased by only 4%.We combine fuzzy logic and DRL reward functions to personify the lane-changing behavior of intelligent driving.Compared with conservative strategies that prioritize only safety,this method can considerably improve the number of lane changes and travel efficiency for autonomous vehicles(AVs)on the premise of ensuring safety.The approach provides an effective and explainable method designed for facilitating intelligent driving lane-changing behavior.展开更多
The lane changing decision model(LCDM)is a critical component in semi-and fully-automated driving systems.Recent research has found that the fuzzy inference system(FIS)is a promising approach to implementing LCDMs.To ...The lane changing decision model(LCDM)is a critical component in semi-and fully-automated driving systems.Recent research has found that the fuzzy inference system(FIS)is a promising approach to implementing LCDMs.To improve the FIS’s performance,this research reviewed the challenges in the development an FIS model to make the yes;nof g decisions in discretionary lane changes.The FIS model was revised to bring its fuzzy inference rules more consistent with the fuzzy membership functions,and its com-position and defuzzification methods more in line with the classical fuzzy logic theory.An equitable test data set with approximately equal number of yes;nof g data points was assembled from the same next generation simulation(NGSIM)data used in the past research.The test results proved that:(1)an LCDM’s performance was dependent on how the yes;nof g decisions in the test data set were manually labeled;(2)separating the fuzzy inference rules into a yesf g group and a nof g group and compute the results sep-arately yielded potentially better decision accuracy.Furthermore,The gene expression pro-gramming model(GEPM)performed better than the improved FIS-based model.The findings led the authors to suggest two possible research directions:(1)add the subject vehicle’s speed as an input to the LCDM and redesign the decision-making model;(2)con-struct models for congested and uncongested traffic separately.The authors further sug-gested the use of instrumented vehicles to collect a set of high-fidelity lane changing data in the naturalistic driving environment.展开更多
To remedy the empirical pitfalls of current chinese specifications and MUTCD 2009 guidelines in determining the placement distance of freeway exit advance guide signs,the driving maneuver of exiting traffic is analyze...To remedy the empirical pitfalls of current chinese specifications and MUTCD 2009 guidelines in determining the placement distance of freeway exit advance guide signs,the driving maneuver of exiting traffic is analyzed and the factors influencing placement distance are explored.Variables including the number of lanes,lane width,lane-changing time,driver＇s visual characteristics,sign installation methods and operating speeds on both freeway mainlines and exit ramps are found significant in explaining exit safety.Three different installation methods,namely ground installation,overhead installation and median installation,are introduced and their applicable conditions are given.Models,with the same structure among the three installation methods,are developed to compute the placement distance under different roadway geometric and traffic conditions.Taking overhead installation as an example,simulation results in TSIS-CORSIM show that the proposed distance reduces the number of lane changes in the area from the ramp nose to 500 m upstream by 58.93% compared with current Chinese specifications and 27.35% compared with MUTCD 2009 guidelines.Thus,the distances recommended in this paper have a better safety performance.展开更多
In the three-phase traffic flow studies, the traffic flow characteristic at the bottleneck section is a hot spot in the academic field. The controversy about the characteristics of the synchronized flow at bottleneck ...In the three-phase traffic flow studies, the traffic flow characteristic at the bottleneck section is a hot spot in the academic field. The controversy about the characteristics of the synchronized flow at bottleneck is also the main contradiction between the three-phase traffic flow theory and the traditional traffic flow theory. Under the framework of three-phase traffic flow theory, this paper takes the on-ramp as an example to discuss the traffic flow characteristics at the bottleneck section.In particular, this paper mainly conducts the micro-analysis to the effect of lane change under the two lane conditions, as well as the effect of the on-ramp on the main line traffic flow. It is found that when the main road flow is low, the greater the on-ramp inflow rate, the higher the average speed of the whole road section. As the probability of vehicles entering from the on-ramp increases, the flow and the average speed of the main road are gradually stabilized, and then the on-ramp inflow vehicles no longer have a significant impact on the traffic flow. In addition, this paper focuses on the velocity disturbance generated at the on-ramp, and proposes the corresponding on-ramp control strategy based on it, and the simulation verified that the control strategy can reasonably control the traffic flow by the on-ramp, which can meet the control strategy requirements to some extent.展开更多
This research aims to quantify driver ride comfort due to changes in damper characteristics between comfort mode and sport mode,considering the vehicle’s inertial behavior.The comfort of riding in an automobile has b...This research aims to quantify driver ride comfort due to changes in damper characteristics between comfort mode and sport mode,considering the vehicle’s inertial behavior.The comfort of riding in an automobile has been evaluated in recent years on the basis of a subjective sensory evaluation given by the driver.However,reflecting driving sensations in design work to improve ride comfort is abstract in nature and difficult to express theoretically.Therefore,we evaluated the human body’s effects while driving scientifically by quantifying the driver’s behavior while operating the steering wheel and the behavior of the automobile while in motion using physical quantities.To this end,we collected driver and vehicle data using amotion capture system and vehicle CAN and IMU sensors.We also constructed a three-dimensional musculoskeletal mathematical model to simulate driver movements and calculate the power and amount of energy per unit of time used for driving the joints and muscles of the human body.Here,we used comfort mode and sport mode to compare damper characteristics in terms of hardness.In comfort mode,damper characteristics are soft and steering stability is mild,but vibration from the road is not easily transmitted to the driver making for a lighter load on the driver.In sport mode,on the other hand,damper characteristics are hard and steering stability is comparatively better.Still,vibration from the road is easily transmitted to the driver,whichmakes it easy for a load to be placed on the driver.As a result of this comparison,it was found that a load was most likely to be applied to the driver’s neck.This result in relation to the neck joint can therefore be treated as an objective measure for quantifying ride comfort.展开更多
This research paper aims to identify the effect of tire size on the handling characteristics of a trailer attached to a vehicle. In various stability tests, different models with different tires from the market were t...This research paper aims to identify the effect of tire size on the handling characteristics of a trailer attached to a vehicle. In various stability tests, different models with different tires from the market were tested. A successful outcome of this research would generate an efficient tire selection process and improve the handling of a trailer attached to a vehicle while maximizing fuel efficiency. In this study, different accurate tire models using the magic formula were developed in vehicle dynamics modelling and simulation software. These models were then simulated on on-road conditions to predict vehicle and trailer behaviour under different conditions within the software. Two distinct tests were conducted, the J-Turn test and the Double Lane change test. The results of these tests were used to evaluate the handling characteristics and decide on a better tire size for the trailer attached to the vehicle.展开更多
This research proposes a predictive lane-changing control system for platoon based on cloud control system(CPPLC),Which is designed to improve the safety,economy,and driving efficiency of a platoon.The system construc...This research proposes a predictive lane-changing control system for platoon based on cloud control system(CPPLC),Which is designed to improve the safety,economy,and driving efficiency of a platoon.The system constructs a vehicle-cloud hierarchical control architecture,with the cloud as the decision-making layer,which collaboratively optimizes the longitudinal acceleration and lateral lane-changing decisions of the platoon based on a model predictive control framework to improve the comprehensive performance of platoon driving.The vehicle is the execution layer,which cooperates with the decision-making in the cloud to generate the platoon driving trajectory and carry out tracking control to ensure the safety of platoon driving.The proposed system is evaluated based on a joint simulation platform consisting of Sumo,Matlab/Simulink,and Trucksim,and the results show that the system can realize the improvement of the economy and driving efficiency while ensuring the safety compared with the conventional microscopic driving model.展开更多
Freeway work zone forms as a result of traffic crash or road rehabilitation.To ascertain the effects of work zone with lane II completely blocked on vehicular flow on ring freeways with a tunnel,a three-lane continuum...Freeway work zone forms as a result of traffic crash or road rehabilitation.To ascertain the effects of work zone with lane II completely blocked on vehicular flow on ring freeways with a tunnel,a three-lane continuum model is put forward.The mandatory net lanechanging rate from lane II to lane I or III just upstream of the work zone is described by a random number model,with the random number being produced within a small range around a median based on a golden section analysis.The net-changing rate between adjacent lanes is described using a lane-changing time on the basis of an assumption:the time ratio to relaxation time equals infinity when the absolute value of traffic densities between the two adjacent lanes is less than 1 veh/km,implying that the net-changing rate is zero;otherwise,the time ratio is inversely proportional to the vehicular spatial headway,which is equal to unity for traffic flow at saturation state,but infinity when the traffic flow is completely jammed.It is assumed that the freeway is a three lane ring with a total length of 100 km,and has a tunnel with a speed limit of 60 km/h and a length of 1.6 km located downstream the work zone with a length of 0.16 km.The free flow speeds on lanes I,II,and III are 120 km/h,100 km/h,and 85 km/h,respectively.For the vehicular flow on the ring freeway with a tunnel,numerical simulations based on the three-lane continuum model are carried out with a reliable numerical method of high accuracy.It is found that the vehicular flow has two thresholds of traffic jam formation,one depending upon the tunnel and the other upon the work zone.The tunnel triggers a traffic jam when the initial density normalized by jam density is equal to the first threshold 0.15,and the work zone originates another traffic jam when the normalized initial density equals the second threshold 0.19.The freeway tunnel plays a dominant role in the prediction of mean travel time as soon as the tunnel has generated a traffic jam at the tunnel entrance.For the vehicular flow at unsaturated state,the average speed through the tunnel is about 26.67 km/h.When the normalized initial density exceeds the second threshold 0.19,the mean travel time through every lane increases with the initial density linearly.Vehicle fuel consumption can be estimated by interpolation with the time averaged grid traffic speed and an assumed vehicle performance curve.It is found that the vehicle fuel consumption is lane number dependent,and distributes with the initial density concavely,as well as has a value in the range of 6.5 to 8.3 l.展开更多
This paper develops a three lane continuum model to analyze the effects of a work zone on vehicular flow on an annular freeway with a tunnel.The model expresses the mandatory lane changing rate just upstream of the wo...This paper develops a three lane continuum model to analyze the effects of a work zone on vehicular flow on an annular freeway with a tunnel.The model expresses the mandatory lane changing rate just upstream of the work zone in an explicit algebraic form with the relevant random parameter generated from golden section analysis,and describes the discretionary lane changing rate between adjacent lanes with a lane changing time depending on local traffic flow density and relaxation time.It is assumed that the annular freeway has three lanes,a work zone with a length of 0.2 km and lane II completely blocked,an upstream tunnel of 1.5 km long,and an initial jam between the tunnel and work zone.The three lane continuum model is applied in vehicular flow simulation with a 3rd order accuracy numerical scheme.Numerical results also indicate that golden section application in the analysis of work zone effects is helpful in obtaining density thresholds of traffic jam formation,the time averaged traffic speed through the tunnel,dependencies of mean travel time,and vehicle fuel consumption on the initial density normalized by jam density.Numerical results reveal that there are two density thresholds of traffic jam formation,if both density thresholds are normalized by traffic jam density,the first threshold relating to the work zone is 0.14,while the second depending on the tunnel is 0.21.In the absence of a work zone,the mean travel time through lane I is slightly longer than that estimated for cases with a work zone.As soon as initial density is above the second threshold,the time averaged speed through the tunnel is 31.91 km/h,which agrees well with published data.展开更多
基金jointly supported by the National Key Research and Development Program of China(No.2022ZD0115600)National Natural Science Foundation of China(No.52072067)+3 种基金Natural Science Foundation of Jiangsu Province(No.BK20210249)China Postdoctoral Science Foundation(No.2020M681466)Jiangsu Planned Projects for Postdoctoral Research Funds(No.SBK2021041144)Jiangsu Planned Projects for Postdoctoral Research Funds(No.2021K094A)。
文摘Connected automated vehicles(CAVs)rely heavily on intelligent algorithms and remote sensors.If the control center or on-board sensors are under cyber-attack due to the security vulnerability of wireless communication,it can cause significant damage to CAVs or passengers.The primary objective of this study is to model cyberattacked traffic flow and evaluate the impacts of cyber-attack on the traffic system filled with CAVs in a connected environment.Based on the analysis on environmental perception system and possible cyber-attacks on sensors,a novel lane-changing model for CAVs is proposed and multiple traffic scenarios for cyber-attacks are designed.The impact of the proportion of cyber-attacked vehicles and the severity of the cyber-attack on the lanechanging process is then quantitatively analyzed.The evaluation indexes include spatio-temporal evolution of average speed,spatial distribution of selected lane-changing gaps,lane-changing rate distribution,lane-changing preparation search time,efficiency and safety.Finally,the numerical simulation results show that the freeway traffic near an off-ramp is more sensitive to the proportion of cyber-attacked vehicles than to the severity of the cyber-attack.Also,when the traffic system is under cyber-attack,more unsafe back gaps are chosen for lane-changing,especially in the center lane.Therefore,more lane-changing maneuvers are concentrated on approaching the off-ramp,causing severe congestions and potential rear-end collisions.In addition,as the number of cyber-attacked vehicles and the severity of cyber-attacks increase,the road capacity and safety level will rapidly decrease.The results of this study can provide a theoretical basis for accident avoidance and efficiency improvement for the design of CAVs and management of automated highway systems.
文摘In this article,lane change models for mixed traffic flow under cooperative adaptive cruise control(CACC)platoon formation are established.The analysis begins by examining the impact of lane changes on traffic flow stability.The influences of various factors such as lane change locations,timing,and the current traffic state on stability are discussed.In this analysis,it is assumed that the lane change location and the entry position in the adjacent lane have already been selected,without considering the specific intention behind the lane change.The speeds of the involved vehicles are adjusted based on an existing lane change model,and various conditions are analyzed for traffic flow disturbances,including duration,shock amplitude,and driving delays.Numerical calculations are provided to illustrate these effects.Additionally,traffic flow stability is factored into the lane change decision-making process.By incorporating disturbances to the fleet into the lane change income model,both a lane change intention model and a lane change execution model are constructed.These models are then compared with a model that does not account for stability,leading to the corresponding conclusions.
基金supported by the National Key R&D Program of China(2023YFE0106800)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(SJCX24_0100).
文摘Mandatory lane change(MLC)is likely to cause traffic oscillations,which have a negative impact on traffic efficiency and safety.There is a rapid increase in research on mandatory lane change decision(MLCD)prediction,which can be categorized into physics-based models and machine-learning models.Both types of models have their advantages and disadvantages.To obtain a more advanced MLCD prediction method,this study proposes a hybrid architecture,which combines the Evolutionary Game Theory(EGT)based model(considering data efficient and interpretable)and the Machine Learning(ML)based model(considering high prediction accuracy)to model the mandatory lane change decision of multi-style drivers(i.e.EGTML framework).Therefore,EGT is utilized to introduce physical information,which can describe the progressive cooperative interactions between drivers and predict the decision-making of multi-style drivers.The generalization of the EGTML method is further validated using four machine learning models:ANN,RF,LightGBM,and XGBoost.The superiority of EGTML is demonstrated using real-world data(i.e.,Next Generation SIMulation,NGSIM).The results of sensitivity analysis show that the EGTML model outperforms the general ML model,especially when the data is sparse.
基金Project supported by the National Natural Science Foundation of China (Grant No. 70971094)the National Natural Science Youth Foundation of China (Grant No. 50908155)the Key Project of Tianjin Municipal Science and Technology Support Program,China (Grant No. 08ZCKFSF01000)
文摘This paper deals mainly with the influence of lane changing behaviours on the stability of two-lane traffic flow under a periodic boundary condition. Following the description of an optimal velocity model for two vehicle groups and the derivation of their stability conditions, the feedback signals, which involve information about vehicles from both lanes acting on the two-lane traffic system, are introduced into the optimal velocity model. The control signals play a role in alleviating the traffic jam only if the traffic state is in congestion, and their role will vanish if the traffic state is in the steady state. The numerical simulations show that lane changing behaviours can break the steady state of two-lane traffic flow and aggravate the traffic disturbance, but the control method would successfully suppress the traffic jam eventually, which implies that the conclusions obtained here have certain theoretical and practical significance.
基金the National Natural Science Foundation of China (70701002,70521001)the National Basic Research Program of China (2006CB705503)the Research Grants Council of the Hong Kong Special Administrative Region (HKU7187/05E)
文摘In this paper, a new car-following model is presented, taking into account the anticipation of potential lane changing by the leading vehicle. The stability condition of the model is obtained by using the linear stability theory. The modified Korteweg-de Vries （KdV） equation is constructed and solved, and three types of traffic flow in the headway-sensitivity space, namely stable, metastable and unstable ones, are classified. Both the analytical and simu- lation results show that anxiety about lane changing does indeed have an influence on driving behavior and that a consideration of lane changing probability in the car-following model could stabilize traffic flows. The quantitative relationship between stability improvement and lane changing probability is also investigated.
文摘Accidents are in rising mode and became the main problem all over the world especially in Malaysia as the reasons including the condition of the road, driver＇s reaction and the road environment. Actually, those condition also factors to execute the lane changing which experienced by all drivers such as in U-turn road segment. In approaching U-turn segment, drivers needed to make a decision whenever any disruption in front of them such as merging vehicle because they have their own perspective and desire. For that purpose, this research is focusing on the reaction of the driver in approaching the U-turn facility road segment especially in speed （V）, reaction time （RT） and distance where from those parameters and their relationships, the statistical model was developed and used in estimating the safe distances to execute the lane changing from the merging vehicle. The data were taken from the field and driving simulator to come out with the raw data. The field data were from video recording that has been used to simulate the driving simulator. Therefore, through the relationship between the RT, speed （V） and distance of the subject vehicle to the merging vehicle, the statistical model has been developed with the equation D.4MVUT = （13.448 ＋ 1.410 RT- 0.075 V）.
文摘Lane change prediction is critical for crash avoidance but challenging as it requires the understanding of the instantaneous driving environment.With cutting-edge artificial intelligence and sensing technologies,autonomous vehicles(AVs)are expected to have exceptional perception systems to capture instantaneously their driving environments for predicting lane changes.By exploring the Waymo open motion dataset,this study proposes a framework to explore autonomous driving data and investigate lane change behaviors.In the framework,this study develops a Long Short-Term Memory(LSTM)model to predict lane changing behaviors.The concept of Vehicle Operating Space(VOS)is introduced to quantify a vehicle's instantaneous driving environment as an important indicator used to predict vehicle lane changes.To examine the robustness of the model,a series of sensitivity analysis are conducted by varying the feature selection,prediction horizon,and training data balancing ratios.The test results show that including VOS into modeling can speed up the loss decay in the training process and lead to higher accuracy and recall for predicting lane-change behaviors.This study offers an example along with a methodological framework for transportation researchers to use emerging autonomous driving data to investigate driving behaviors and traffic environments.
基金Project supported by the National Natural Science Foundation of China (Grant No.11102165)the Natural Science Basis Research Plan in Shaanxi Province,China (Grant No.2012JM1001)the Foundation for Fundamental Research of Northwestern Polytechnical University,China (Grant No.NPU-FFR-JC201254)
文摘In this paper, we study the effect of moving bottlenecks on traffic flow. The full velocity difference （FVD） model is extended to the traffic flow on a two-lane highway, and new lane changing rule is proposed to reproduce the vehicular lane changing behavior. Using this model, we derive the fundamental current-density diagrams for the traffic flow with the effect of moving bottleneck. Moreover, typical time-space diagram for a two-lane highway shows the formation and dissipation of a moving bottleneck. Results demonstrate that the effect of moving bottleneck enlarges with the increase of traffic density, but the effect can be reduced by increasing the maximum velocity of heavy truck. The effects of multiple moving bottlenecks under different conditions are investigated. The effect becomes more remarkable when the coupling effect of multiple moving bottlenecks occurs.
基金supported in part by the National Natural Science Foundation of China(No.51905405)Basic Research Program of Natural Science of Shaanxi Province(No.2022JM-407)Guiding Program of Science and Technology of China Textile Industry Federation(No.2020106).
文摘In a multi-lane area,the increasing randomness of lane changes contributes to traffic insecurity and local traffic flow instability.A study on safe lane shifting activity that focuses on threat assessment under real-time knowledge is necessary to enhance smooth vehicle flow.This paper proposed amore comprehensive lane changing guidance rule to investigate the status of surrounding vehicles to accommodate future vehicle-on-road collaborative environments based on these parameters 1)lane change demand and 2)treat assessment function.The collaborative relationships between vehicles are analyzed using a cellular automata model based on their location,velocity,and acceleration.We analyze and examine the relationship between the number of lanes and traffic flow when the road capacity is heavily mined via intelligent lane changing.Our analysis can further provide theoretical guidance for the selection of road expansion mode.Our proposed STCA-L is compared based on the average speed,average flow,lane changing frequency,spatial and temporal pattern of STCA,STCA-I,and STCA-S,and STCA-M under different vehicle densities.The numerical simulation results show that our proposed STCA-L provides themost flexible lane changing guidance in the multi-lanes road.Moreover,the simulated results show that the exponential growth of physical space cannot provide the corresponding increase in the average flow of vehicles.
基金Sponsored by the Natural Science Foundation of Shandong Province(Grant No.ZR2010FM008ZR2015FM024)the Natural Scientific Research Innovation Foundation in Harbin Institute of Technology(Grant No.HIT.NSRIF.2011117)
文摘In this paper,it studies the problem of trajectory planning and tracking for lane changing behavior of vehicle in automatic highway systems. Based on the model of yaw angle acceleration with positive and negative trapezoid constraint,by analyzing the variation laws of yaw motion of vehicle during a lane changing maneuver,the reference model of desired yaw angle and yaw rate for lane changing is generated. According to the yaw angle model,the vertical and horizontal coordinates of trajectory for vehicle lane change are calculated. Assuming that the road curvature is a constant,the difference and associations between two scenarios are analyzed,the lane changing maneuvers occurred on curve road and straight road,respectively. On this basis,it deduces the calculation method of desired yaw angle for lane changing on circular road. Simulation result shows that,it is different from traditional lateral acceleration planning method with the trapezoid constraint,by applying the trapezoidal yaw acceleration reference model proposed in this paper, the resulting expected yaw angular acceleration is continuous,and the step tracking for steering angle is not needed to implement. Due to the desired yaw model is direct designed based on the variation laws of raw movement of vehicle during a lane changing maneuver, rather than indirectly calculated from the trajectory model for lane changing, the calculation steps are simplified.
基金National Science and Technology Council,Taiwan,for financially supporting this research(Grant No.NSTC 113-2221-E-018-011)Ministry of Education’s Teaching Practice Research Program,Taiwan(PSK1120797 and PSK1134099).
文摘This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed rapidly,moving from basic driver-assistance systems(Level 1)to fully autonomous capabilities(Level 5).Central to this advancement are two key functionalities:Lane-Change Maneuvers(LCM)and Adaptive Cruise Control(ACC).In this study,a detailed simulation environment is created to replicate the road network between Nantun andWuri on National Freeway No.1 in Taiwan.The MPC controller is deployed to optimize vehicle trajectories,ensuring safe and efficient navigation.Simulated onboard sensors,including vehicle cameras and millimeterwave radar,are used to detect and respond to dynamic changes in the surrounding environment,enabling real-time decision-making for LCM and ACC.The simulation resultshighlight the superiority of the MPC-based approach in maintaining safe distances,executing controlled lane changes,and optimizing fuel efficiency.Specifically,the MPC controller effectively manages collision avoidance,reduces travel time,and contributes to smoother traffic flow compared to traditional path planning methods.These findings underscore the potential of MPC to enhance the reliability and safety of autonomous driving in complex traffic scenarios.Future research will focus on validating these results through real-world testing,addressing computational challenges for real-time implementation,and exploring the adaptability of MPC under various environmental conditions.This study provides a significant step towards achieving safer and more efficient autonomous vehicle navigation,paving the way for broader adoption of MPC in AV systems.
基金supported in part by the National Natural Science Foundation of China(No.52372407)the Jilin Provincial Science and Technology Development Plan Project(No.20230402064GH).
文摘Lane changing is common in driving.Thus,the possibility of traffic accidents occurring during lane changes is high given the complexity of this process.One of the primary objectives of intelligent driving is to increase a vehicle’s behavior,making it more similar to that of a real driver.This study proposes a decision-making framework based on deep reinforcement learning(DRL)in a lane-changing scenario,which seeks to find a driving strategy that simultaneously considers the expected lane-changing risks and gains.First,a fuzzy logic lane-changing controller is designed.It outputs the corresponding safety and lane-change gain weights by inputting relevant driving parameters.Second,the obtained weights are brought into the constructed reward function of DRL.The model parameters are designed and trained on the basis of lane-changing behavior.Finally,we conducted experiments in a simulator to evaluate the performance of our developed algorithm in urban scenarios.To visualize and validate the estimated driving intentions,lane-changing strategies were tested under four scenarios.The results show that the average improvement in travel efficiency in the four scenarios is 19%.In addition,the average accident rate in the four scenarios increased by only 4%.We combine fuzzy logic and DRL reward functions to personify the lane-changing behavior of intelligent driving.Compared with conservative strategies that prioritize only safety,this method can considerably improve the number of lane changes and travel efficiency for autonomous vehicles(AVs)on the premise of ensuring safety.The approach provides an effective and explainable method designed for facilitating intelligent driving lane-changing behavior.
文摘The lane changing decision model(LCDM)is a critical component in semi-and fully-automated driving systems.Recent research has found that the fuzzy inference system(FIS)is a promising approach to implementing LCDMs.To improve the FIS’s performance,this research reviewed the challenges in the development an FIS model to make the yes;nof g decisions in discretionary lane changes.The FIS model was revised to bring its fuzzy inference rules more consistent with the fuzzy membership functions,and its com-position and defuzzification methods more in line with the classical fuzzy logic theory.An equitable test data set with approximately equal number of yes;nof g data points was assembled from the same next generation simulation(NGSIM)data used in the past research.The test results proved that:(1)an LCDM’s performance was dependent on how the yes;nof g decisions in the test data set were manually labeled;(2)separating the fuzzy inference rules into a yesf g group and a nof g group and compute the results sep-arately yielded potentially better decision accuracy.Furthermore,The gene expression pro-gramming model(GEPM)performed better than the improved FIS-based model.The findings led the authors to suggest two possible research directions:(1)add the subject vehicle’s speed as an input to the LCDM and redesign the decision-making model;(2)con-struct models for congested and uncongested traffic separately.The authors further sug-gested the use of instrumented vehicles to collect a set of high-fidelity lane changing data in the naturalistic driving environment.
基金Project of Florida Department of Transportation(No.BD54438)the National Key Technology R&D Program of China during the 11th Five-Year Plan Period(No.2006BAJ18B03)
文摘To remedy the empirical pitfalls of current chinese specifications and MUTCD 2009 guidelines in determining the placement distance of freeway exit advance guide signs,the driving maneuver of exiting traffic is analyzed and the factors influencing placement distance are explored.Variables including the number of lanes,lane width,lane-changing time,driver＇s visual characteristics,sign installation methods and operating speeds on both freeway mainlines and exit ramps are found significant in explaining exit safety.Three different installation methods,namely ground installation,overhead installation and median installation,are introduced and their applicable conditions are given.Models,with the same structure among the three installation methods,are developed to compute the placement distance under different roadway geometric and traffic conditions.Taking overhead installation as an example,simulation results in TSIS-CORSIM show that the proposed distance reduces the number of lane changes in the area from the ramp nose to 500 m upstream by 58.93% compared with current Chinese specifications and 27.35% compared with MUTCD 2009 guidelines.Thus,the distances recommended in this paper have a better safety performance.
基金Project supported by the National Natural Science Foundation of China(Grant No.51468034)the Colleges and Universities Fundamental Scientific Research Expenses Project of Gansu Province,China(Grant No.214148)+1 种基金the Natural Science Foundation of Gansu Province,China(Grant No.1606RJZA017)the Universities Scientific Research Project of Gansu Provincial Educational Department,China(Grant No.2015A-051)
文摘In the three-phase traffic flow studies, the traffic flow characteristic at the bottleneck section is a hot spot in the academic field. The controversy about the characteristics of the synchronized flow at bottleneck is also the main contradiction between the three-phase traffic flow theory and the traditional traffic flow theory. Under the framework of three-phase traffic flow theory, this paper takes the on-ramp as an example to discuss the traffic flow characteristics at the bottleneck section.In particular, this paper mainly conducts the micro-analysis to the effect of lane change under the two lane conditions, as well as the effect of the on-ramp on the main line traffic flow. It is found that when the main road flow is low, the greater the on-ramp inflow rate, the higher the average speed of the whole road section. As the probability of vehicles entering from the on-ramp increases, the flow and the average speed of the main road are gradually stabilized, and then the on-ramp inflow vehicles no longer have a significant impact on the traffic flow. In addition, this paper focuses on the velocity disturbance generated at the on-ramp, and proposes the corresponding on-ramp control strategy based on it, and the simulation verified that the control strategy can reasonably control the traffic flow by the on-ramp, which can meet the control strategy requirements to some extent.
文摘This research aims to quantify driver ride comfort due to changes in damper characteristics between comfort mode and sport mode,considering the vehicle’s inertial behavior.The comfort of riding in an automobile has been evaluated in recent years on the basis of a subjective sensory evaluation given by the driver.However,reflecting driving sensations in design work to improve ride comfort is abstract in nature and difficult to express theoretically.Therefore,we evaluated the human body’s effects while driving scientifically by quantifying the driver’s behavior while operating the steering wheel and the behavior of the automobile while in motion using physical quantities.To this end,we collected driver and vehicle data using amotion capture system and vehicle CAN and IMU sensors.We also constructed a three-dimensional musculoskeletal mathematical model to simulate driver movements and calculate the power and amount of energy per unit of time used for driving the joints and muscles of the human body.Here,we used comfort mode and sport mode to compare damper characteristics in terms of hardness.In comfort mode,damper characteristics are soft and steering stability is mild,but vibration from the road is not easily transmitted to the driver making for a lighter load on the driver.In sport mode,on the other hand,damper characteristics are hard and steering stability is comparatively better.Still,vibration from the road is easily transmitted to the driver,whichmakes it easy for a load to be placed on the driver.As a result of this comparison,it was found that a load was most likely to be applied to the driver’s neck.This result in relation to the neck joint can therefore be treated as an objective measure for quantifying ride comfort.
文摘This research paper aims to identify the effect of tire size on the handling characteristics of a trailer attached to a vehicle. In various stability tests, different models with different tires from the market were tested. A successful outcome of this research would generate an efficient tire selection process and improve the handling of a trailer attached to a vehicle while maximizing fuel efficiency. In this study, different accurate tire models using the magic formula were developed in vehicle dynamics modelling and simulation software. These models were then simulated on on-road conditions to predict vehicle and trailer behaviour under different conditions within the software. Two distinct tests were conducted, the J-Turn test and the Double Lane change test. The results of these tests were used to evaluate the handling characteristics and decide on a better tire size for the trailer attached to the vehicle.
基金supported by the National Key R&D Program of China(2021YFB2501000)and the Joint R&D Project with Weichai Power Co.,Ltd.
文摘This research proposes a predictive lane-changing control system for platoon based on cloud control system(CPPLC),Which is designed to improve the safety,economy,and driving efficiency of a platoon.The system constructs a vehicle-cloud hierarchical control architecture,with the cloud as the decision-making layer,which collaboratively optimizes the longitudinal acceleration and lateral lane-changing decisions of the platoon based on a model predictive control framework to improve the comprehensive performance of platoon driving.The vehicle is the execution layer,which cooperates with the decision-making in the cloud to generate the platoon driving trajectory and carry out tracking control to ensure the safety of platoon driving.The proposed system is evaluated based on a joint simulation platform consisting of Sumo,Matlab/Simulink,and Trucksim,and the results show that the system can realize the improvement of the economy and driving efficiency while ensuring the safety compared with the conventional microscopic driving model.
基金supported by the National Natural Science Foundation of China(No.11972341)the fundamental research project of Lomonosov Moscow State University‘Mathematical models for multi-phase media and wave processes in natural,technical and social systems’.
文摘Freeway work zone forms as a result of traffic crash or road rehabilitation.To ascertain the effects of work zone with lane II completely blocked on vehicular flow on ring freeways with a tunnel,a three-lane continuum model is put forward.The mandatory net lanechanging rate from lane II to lane I or III just upstream of the work zone is described by a random number model,with the random number being produced within a small range around a median based on a golden section analysis.The net-changing rate between adjacent lanes is described using a lane-changing time on the basis of an assumption:the time ratio to relaxation time equals infinity when the absolute value of traffic densities between the two adjacent lanes is less than 1 veh/km,implying that the net-changing rate is zero;otherwise,the time ratio is inversely proportional to the vehicular spatial headway,which is equal to unity for traffic flow at saturation state,but infinity when the traffic flow is completely jammed.It is assumed that the freeway is a three lane ring with a total length of 100 km,and has a tunnel with a speed limit of 60 km/h and a length of 1.6 km located downstream the work zone with a length of 0.16 km.The free flow speeds on lanes I,II,and III are 120 km/h,100 km/h,and 85 km/h,respectively.For the vehicular flow on the ring freeway with a tunnel,numerical simulations based on the three-lane continuum model are carried out with a reliable numerical method of high accuracy.It is found that the vehicular flow has two thresholds of traffic jam formation,one depending upon the tunnel and the other upon the work zone.The tunnel triggers a traffic jam when the initial density normalized by jam density is equal to the first threshold 0.15,and the work zone originates another traffic jam when the normalized initial density equals the second threshold 0.19.The freeway tunnel plays a dominant role in the prediction of mean travel time as soon as the tunnel has generated a traffic jam at the tunnel entrance.For the vehicular flow at unsaturated state,the average speed through the tunnel is about 26.67 km/h.When the normalized initial density exceeds the second threshold 0.19,the mean travel time through every lane increases with the initial density linearly.Vehicle fuel consumption can be estimated by interpolation with the time averaged grid traffic speed and an assumed vehicle performance curve.It is found that the vehicle fuel consumption is lane number dependent,and distributes with the initial density concavely,as well as has a value in the range of 6.5 to 8.3 l.
基金supported by National Natural Science Foundation of China(11972341)fundamental research project of Lomonosov Moscow State University‘Mathematical models for multi-phase media and wave processes in natural,technical and social systems’.
文摘This paper develops a three lane continuum model to analyze the effects of a work zone on vehicular flow on an annular freeway with a tunnel.The model expresses the mandatory lane changing rate just upstream of the work zone in an explicit algebraic form with the relevant random parameter generated from golden section analysis,and describes the discretionary lane changing rate between adjacent lanes with a lane changing time depending on local traffic flow density and relaxation time.It is assumed that the annular freeway has three lanes,a work zone with a length of 0.2 km and lane II completely blocked,an upstream tunnel of 1.5 km long,and an initial jam between the tunnel and work zone.The three lane continuum model is applied in vehicular flow simulation with a 3rd order accuracy numerical scheme.Numerical results also indicate that golden section application in the analysis of work zone effects is helpful in obtaining density thresholds of traffic jam formation,the time averaged traffic speed through the tunnel,dependencies of mean travel time,and vehicle fuel consumption on the initial density normalized by jam density.Numerical results reveal that there are two density thresholds of traffic jam formation,if both density thresholds are normalized by traffic jam density,the first threshold relating to the work zone is 0.14,while the second depending on the tunnel is 0.21.In the absence of a work zone,the mean travel time through lane I is slightly longer than that estimated for cases with a work zone.As soon as initial density is above the second threshold,the time averaged speed through the tunnel is 31.91 km/h,which agrees well with published data.
