Evaluating impact of remote-access cyber-attack on lane changes for connected automated vehicles

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.

An evolutionary game theory-based machine learning framework for predicting mandatory lane change decision

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.

A Lane Change Model Considering the Stability of Cooperative Adaptive Cruise Control Platoon Fleet

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.

Influence of lane change on stability analysis for two-lane traffic flow

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.

LSTM-based lane change prediction using Waymo open motion dataset: The role of vehicle operating space

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.

Enhancing Safety in Autonomous Vehicle Navigation:An Optimized Path Planning Approach Leveraging Model Predictive Control

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.

Placement distance of freeway exit advance guide sign and its safety impacts

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.

A car-following model with the anticipation effect of potential lane changing

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.

The effect of moving bottlenecks on a two-lane traffic flow

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.

Traffic flow velocity disturbance characteristics and control strategy at the bottleneck of expressway

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.

Improved STCA Model for Multi-Lane Using Driving Guidance under CVIS

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.

Reference Modelof Desired Yaw Anglefor Automated Lane Changing Behavior of Vehicle

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.

Quantification of Ride Comfort Using Musculoskeletal Mathematical Model Considering Vehicle Behavior

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.

Analysis of the Effect of Trailer Tire Size on the Articulated Vehicle’s Stability

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.

Development of Vehicle Lane Changing Model in Approaching the U-Turn Facility Road Segment

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）.

Structured trajectory planning of collision-free lane change using the vehicle-driver integration data

In this paper, the structured trajectory planning of lane change in collision-free road environment is studied and validated using the vehicle-driver integration data, and a new trajectory planning model for lane change is proposed based on linear offset and sine function to balance driver comfort and vehicle dynamics. The trajectory curvature of the proposed model is continuous without mutation, and the zero-based curvature at the starting and end points during lane change assures the motion direction of end points in parallel with the lane line. The field experiment are designed to collect the vehicle-driver integration data, such as steering angle, brake pedal angel and accelerator pedal angel. The correction Correlation analysis of lane-changing maneuver and influencing variables is conducted to obtain the significant variables that can be used to calibrate and test the proposed model. The results demonstrate that vehicle velocity and Y-axis acceleration have significant effects on the lane-changing maneuver, so that the model recalibrated by the samples of different velocity ranges and Y-axis accelerations has better fitted performance compared with the model calibrated by the sample trajectory. In addition, the proposed model presents a decreasing tendency of the lane change trajectory fitted MAE with the increase of time span of calibrating samples at the starting stage.

Cooperative Lane-Change Maneuver for Multiple Automated Vehicles on a Highway

With the development of vehicle-to-vehicle(V2V)communication,it is possible to share information among multiple vehicles.However,the existing research on automated lane changes concentrates only on the single-vehicle lane change with self-detective information.Cooperative lane changes are still a new area with more complicated scenarios and can improve safety and lane-change efficiency.Therefore,a multi-vehicle cooperative automated lane-change maneuver based on V2V communication for scenarios of eight vehicles on three lanes was proposed.In these scenarios,same-direction and intersectant-direction cooperative lane changes were defined.The vehicle that made the cooperative decision obtained the information of surrounding vehicles that were used to cooperatively plan the trajectories,which was called cooperative trajectory planning.The cooperative safety spacing model was proposed to guarantee and improve the safety of all vehicles,and it essentially developed constraints for the trajectory-planning task.Trajectory planning was treated as an optimization problem with the objective of maximizing safety,comfort,and lane-change efficiency under the constraints of vehicle dynamics and the aforementioned safety spacing model.Trajectory tracking based on a model predictive control method was designed to minimize tracking errors and control increments.Finally,to verify the validity of the proposed maneuver,an integrated simulation platform combining MATLAB/Simulink with CarSim was established.Moreover,a hardware-in-the-loop test bench was performed for further verification.The results indicated that the proposed multi-vehicle cooperative automated lane-change maneuver can achieve lane changes of multiple vehicles and increase lane-change efficiency while guaranteeing safety and comfort.

A Trajectory Planning Method of Automatic Lane Change Based on Dynamic Safety Domain

Traditional research on automatic lane change has primarily focused on high-speed scenarios and has not considered the dynamic state changes of surrounding vehicles.This paper addresses this problem by proposing a trajectory planning method to enable automatic lane change at medium and low speeds.The method is based on a dynamic safety domain model,which takes into account the actual state change of surrounding vehicles,as well as the upper boundary of the safety domain for collision avoidance and the lower boundary of comfort for vehicle stability.The proposed method involves the quantification of the safety and comfort boundaries through parametric modeling of the vehicle.A quintic polynomial trajectory planning method is proposed and evaluated through simulation and testing,resulting in improved safety and comfort for automatic lane change.

Dynamic Trajectory Planning of Autonomous Lane Change at Medium and Low Speeds Based on Elastic Soft Constraint of the Safety Domain

Most current research on the trajectory planning of the autonomous lane change focuses on high-speed scenarios and assumes that the states of the surrounding vehicles keep stable during the lane change.The methods based on geometric-curve are mostly used for trajectory planning.In this paper,considering the inevitable development of the autonomous driving,the surrounding vehicles are assumed to be driven by human drivers,while the ego vehicles are able to autonomously change lanes.Representative local lane-change scenarios are then designed and analyzed in detail aiming at medium-and low-speed lane-change conditions.Additionally,in contrast with most research,dynamic trajectory planning which considers the possible state variations of the surrounding vehicles and the driver characteristics is studied and described by a fifth-order polynomial function.The safety and comfort of the dynamic trajectory planning are validated through simulation.Moreover,the elastic soft constraint of the safety domain is designed,whereby the sensitivity of the studied dynamic trajectory planning system is reduced under the premise of ensuring safety.The effectiveness of the elastic soft constraint in terms of improving comfort during the lane change is verified through simulation.The availability of the dynamic trajectory planning system with the elastic soft constraint is demonstrated with the addition of trajectory tracking based on model predictive control,showing its potential in practical applications.

Evaluation of Automatic Lane-Change Model Based on Vehicle Cluster Generalized Dynamic System

The lane-change transportation research usually focuses on the efficiency and stability of the macro traffic flow while ignoring the driving comfort of individual vehicles.And many studies of lane-change models are often limited to the performance of a single vehicle,which leads to a lack of macroscopic evaluation.To solve the above limitations,an automatic lane-change generalized dynamic model is adopted.In this model,the lane-change behavior of an individual vehicle is considered as the generalized excitation and the restraining force between vehicles is described with the car-following model.Macro and micro evaluation indexes are also adopted to evaluate the automatic lane-change behavior in traffic flow.Furthermore,this paper proposes a modified intelligent driver model(IDM)to describe the state change process during lane change.The hyperbolic tangent transition function is used to eliminate the vehicle state mutation.The simulation results show that the proposed automatic lane-change generalized dynamic model can reflect the macro and micro parameters of the traffic flow.And compared with the traditional IDM model,the proposed HC-IDM model achieves higher comfort performance and lower fluctuation of traffic flow.