Ensuring Secure Platooning of Constrained Intelligent and Connected Vehicles Against Byzantine Attacks:A Distributed MPC Framework

This study investigates resilient platoon control for constrained intelligent and connected vehicles(ICVs)against F-local Byzantine attacks.We introduce a resilient distributed model-predictive platooning control framework for such ICVs.This framework seamlessly integrates the predesigned optimal control with distributed model predictive control(DMPC)optimization and introduces a unique distributed attack detector to ensure the reliability of the transmitted information among vehicles.Notably,our strategy uses previously broadcasted information and a specialized convex set,termed the“resilience set”,to identify unreliable data.This approach significantly eases graph robustness prerequisites,requiring only an(F+1)-robust graph,in contrast to the established mean sequence reduced algorithms,which require a minimum(2F+1)-robust graph.Additionally,we introduce a verification algorithm to restore trust in vehicles under minor attacks,further reducing communication network robustness.Our analysis demonstrates the recursive feasibility of the DMPC optimization.Furthermore,the proposed method achieves exceptional control performance by minimizing the discrepancies between the DMPC control inputs and predesigned platoon control inputs,while ensuring constraint compliance and cybersecurity.Simulation results verify the effectiveness of our theoretical findings.

Stability of connected and automated vehicles platoon considering communications failures

As a form of a future traffic system,a connected and automated vehicle(CAV)platoon is a typical nonlinear physical system.CAVs can communicate with each other and exchange information.However,communication failures can change the platoon system status.To characterize this change,a dynamic topology-based car-following model and its generalized form are proposed in this work.Then,a stability analysis method is explored.Finally,taking the dynamic cooperative intelligent driver model(DC-IDM)for example,a series of numerical simulations is conducted to analyze the platoon stability in different communication topology scenarios.The results show that the communication failures reduce the stability,but information from vehicles that are farther ahead and the use of a larger desired time headway can improve stability.Moreover,the critical ratio of communication failures required to ensure stability for different driving parameters is studied in this work.

Energy-Optimal Braking Control Using a Double-Layer Scheme for Trajectory Planning and Tracking of Connected Electric Vehicles

Most researches focus on the regenerative braking system design in vehicle components control and braking torque distribution,few combine the connected vehicle technologies into braking velocity planning.If the braking intention is accessed by the vehicle-to-everything communication,the electric vehicles(EVs)could plan the braking velocity for recovering more vehicle kinetic energy.Therefore,this paper presents an energy-optimal braking strategy(EOBS)to improve the energy efficiency of EVs with the consideration of shared braking intention.First,a double-layer control scheme is formulated.In the upper-layer,an energy-optimal braking problem with accessed braking intention is formulated and solved by the distance-based dynamic programming algorithm,which could derive the energy-optimal braking trajectory.In the lower-layer,the nonlinear time-varying vehicle longitudinal dynamics is transformed to the linear time-varying system,then an efficient model predictive controller is designed and solved by quadratic programming algorithm to track the original energy-optimal braking trajectory while ensuring braking comfort and safety.Several simulations are conducted by jointing MATLAB and CarSim,the results demonstrated the proposed EOBS achieves prominent regeneration energy improvement than the regular constant deceleration braking strategy.Finally,the energy-optimal braking mechanism of EVs is investigated based on the analysis of braking deceleration,battery charging power,and motor efficiency,which could be a guide to real-time control.

Modeling the heterogeneous traffic flow considering the effect of self-stabilizing and autonomous vehicles

With the increasing maturity of automatic driving technology,the homogeneous traffic flow will gradually evolve into the heterogeneous traffic flow,which consists of human-driving and autonomous vehicles.To better study the characteristics of the heterogeneous traffic system,this paper proposes a new car-following model for autonomous vehicles and heterogeneous traffic flow,which considers the self-stabilizing effect of vehicles.Through linear and nonlinear methods,this paper deduces and analyzes the stability of such a car-following model with the self-stabilizing effect.Finally,the model is verified by numerical simulation.Numerical results show that the self-stabilizing effect can make the heterogeneous traffic flow more stable,and that increasing the self-stabilizing coefficient or historical time length can strengthen the stability of heterogeneous traffic flow and alleviate traffic congestion effectively.In addition,the heterogeneous traffic flow can also be stabilized with a higher proportion of autonomous vehicles.

MULTI-AXLE VEHICLE STABILITY BASED ON WHOLE VEHICLE MODEL

From the analysis of experiment data of the multi-axle vehicle chassis searching process, it is less accurate to predict multi-axle vehicle dynamic characteristic with simplified two-axle vehicle model. So it is important to find out a more effective modeling method in the study of multi-vehicle stability. In the development of heat transfer fluid（HTF） six-axle vehicle, a whole vehicle multi-body dynamic model is built through collaborate flowchart using Teamcenter Engineering, UG NX3 and MSC.Adams. The modeling method of connected hydragas spring suspension is validated by running test results. Based on this whole vehicle model, a kinematical analysis of suspension is implemented to achieve optimized suspension geometry parameters according to the stable requirement. Then, different handling simulations are carried out with regard to various tire characteristics, driving con- figurations, and equipments. According to the evaluation of whole vehicle handling characteristic, some design rules are summarized to improve the stability of multi-axle vehicle.

Calibration of Car-Following Models Considering the Impacts of Warning Messages from Tablet/Smartphone Application

The phenomenon of car-following is special in traffic operations. Traditional car-following models can well describe the reactions of the movements between two concessive vehicles in the same lane within a certain distance. With the invention of connected vehicle technologies, more and more advisory messages are in development and applied in our daily lives, some of which are related to the measures and warnings of speed and headway distance between the two concessive vehicles. Such warnings may change the conventional car-following mechanisms. This paper intends to consider the possible impacts of in-vehicle warning messages to improve the traditional car-following models, including the General Motor (GM) Model and the Linear (Helly) Model, by calibrating model parameters using field data from an arterial road in Houston, Texas, U.S.A. The safety messages were provided by a tablet/smartphone application. One exponent was applied to the GM model, while another one applied to the Linear (Helly) model, both were on the stimuli term “difference in velocity between two concessive vehicles”. The calibration and validation were separately conducted for deceleration and acceleration conditions. Results showed that, the parameters of the traditional GM model failed to be properly calibrated with the interference of in-vehicle safety messages, and the parameters calibrated from the traditional Linear (Helly) Model with no in-vehicle messages could not be directly used in the case with such messages. However, both updated models can be well calibrated even if those messages were provided. The entire research process, as well as the calibrated models and parameters could be a reference in the on-going connected vehicle program and micro/macroscopic traffic simulations.

Continuum modeling of freeway traffic flows:State-of-the-art,challenges and future directions in the era of connected and automated vehicles

Connected and automated vehicles(CAVs)are expected to reshape traffic flow dynamics and present new challenges and opportunities for traffic flow modeling.While numerous studies have proposed optimal modeling and control strategies for CAVs with various objectives(e.g.,traffic efficiency and safety),there are uncertainties about the flow dynamics of CAVs in real-world traffic.The uncertainties are especially amplified for mixed traffic flows,consisting of CAVs and human-driven vehicles,where the implications can be significant from the continuum-modeling perspective,which aims to capture macroscopic traffic flow dynamics based on hyperbolic systems of partial differential equations.This paper aims to highlight and discuss some essential problems in continuum modeling of real-world freeway traffic flows in the era of CAVs.We first provide a select review of some existing continuum models for conventional human-driven traffic as well as the recent attempts for incorporating CAVs into the continuum-modeling framework.Wherever applicable,we provide new insights about the properties of existing models and revisit their implications for traffic flows of CAVs using recent empirical observations with CAVs and the previous discussions and debates in the literature.The paper then discusses some major problems inherent to continuum modeling of real-world(mixed)CAV traffic flows modeling by distinguishing between two major research directions:(a)modeling for explaining purposes,where making reproducible inferences about the physical aspects of macroscopic properties is of the primary interest,and(b)modeling for practical purposes,in which the focus is on the reliable predictions for operation and control.The paper proposes some potential solutions in each research direction and recommends some future research topics.

Fuzzy Unknown Input Observer for Estimating Sensor and Actuator Cyber‑Attacks in Intelligent Connected Vehicles

The detection and mitigation of cyber-attacks in connected vehicle systems(CVSs)are critical for ensuring the security of intelligent connected vehicles.This paper presents a solution to estimate sensor and actuator cyber-attacks in CVSs.A novel method is proposed that utilizes an augmented system representation technique and a nonlinear unknown input observer(UIO)to achieve asymptotic estimation of both CVS dynamics and cyber-attacks.The nonlinear CVS dynamics is represented in a Takagi–Sugeno(TS)fuzzy form with nonlinear consequents,which allows for the effective use of the differential mean value theorem to handle unmeasured premise variables.Furthermore,via Lyapunov stability theory sufficient conditions are proposed,expressed in terms of linear matrix inequalities,to design TS fuzzy UIO.Several test scenarios are performed with high-fidelity Simulink-CarSim co-simulations to show the effectiveness of the proposed cyber-attack estimation method.

网联车辆编队的信号灯路口通行控制策略

为提高信号灯路口场景下车辆编队的安全性和通行效率,提出V2X环境下网联车辆编队的信号灯路口通行控制策略。在信号灯路口上游设置一段控制区,以车辆编队领航车在信号灯路口排队疏散后到达信号灯路口为目标,对进入控制区的车辆编队速度进行优化。考虑速度变化对车辆编队纵向安全距离的影响,引入分布式模型预测控制理论,建立固定跟车时距控制策略下编队车辆的速度跟随控制模型,并采用加权二次型性能泛函将速度跟随控制问题转化为易于在线求解的凸二次规划问题。通过PreScan/Simulink软件仿真将信号灯路口通行控制策略与固定跟车时距控制策略进行对比,以验证速度跟随控制模型的有效性,结果表明:信号灯路口通行控制策略能够避免车辆间碰撞冲突,并可以减少编队车辆在信号灯路口的通行耗时,在保证安全性的同时提高了通行效率。

基于鱼群效应的智能网联车队形成与演化机理研究

随着智能网联车的快速发展,智能网联车与人工驾驶车辆混行下的交通特性分析和协同控制研究已成为热点。本文构建多车道混合交通流元胞自动机仿真模型,对智能网联车队的形成及状态演化过程进行仿真刻画。首先,基于智能网联车的网联化特征,引入鱼群效应来描述4种智能网联车队的形成过程;其次,从车队角度,利用马尔可夫性计算车队规模转移概率,阐述车队状态演化过程;再次,引入Gipps安全距离原则对NaSch模型进行改进,并对智能网联车和智能网联车队进行速度引导;最后,基于实测的车辆到达率,对建立的基于鱼群效应的混合车流元胞自动机模型进行仿真实验。结果表明:智能网联车队可以有效改善混合交通流的运行状态,缓解交通拥堵;在渗透率60%的条件下,智能网联车队规模为3时,与不存在车队相比,拥堵率可减少43.9%,交通流速度约提升43%,并且随着车队规模的增大,交通流平均速度趋于平稳。

Fuel efficient model predictive control strategies for a group of connected vehicles incorporating vertical vibration

This paper presents a decentralized fuel efficient model predictive control(MPC) strategy for a group of connected vehicles incorporating vertical vibration. To capture the vehicle vibration dynamics, the dynamics of the suspension system is integrated with the longitudinal dynamics of the vehicle. Furthermore, a MPC framework with finite time horizon is formulated to calculate the optimal velocity profile that compromises fuel economy, mobility and ride comfort for every individual vehicle with the safety and physical constraints considered. In the MPC framework, the target velocity is calculated using signal phase and timing(SPAT)information to reduce the number of stoppage at red lights, and the vertical acceleration is calculated parallel to the calculation of the fuel consumption. The MPC optimal problem is solved with fast-MPC approach which enhances the computational efficiency via exploiting the structure of the control system and approximate methods. Simulation studies are conducted over different SPATs and connectivity penetration rates and the results validate the advantages of the proposed control architecture.

On the impact of connected automated vehicles in freeway work zones:a cooperative cellular automata model based approach

Purpose–Freeway work zones have been traffic bottlenecks that lead to a series of problems,including long travel time,high-speed variation,driver’s dissatisfaction and traffic congestion.This research aims to develop a collaborative component of connected and automated vehicles(CAVs)to alleviate negative effects caused by work zones.Design/methodology/approach–The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations.Findings–Simulation results show that,with the proposed component and penetration of CAVs,the average performances(travel time,safety and emission)can all be improved and the stochasticity of performances will be minimized too.Originality/value–To the best of the authors’knowledge,this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.

智能网联汽车网络架构分析及安全检测

全球新一轮科技革命和产业变革蓬勃发展,汽车与信息通信技术加速融合,已成为汽车行业未来发展的主要方向,智能网联汽车网络架构是在传统汽车网络架构的基础上,融合现代网络通信技术的复杂网络架构体系。以车与外界的信息交换场景为重点,分析智能网联汽车的网络体系架构和网络运行场景指标,总结智能网联汽车面临的安全风险,并给出防范应对方法。在风险分析的基础上,针对控制器局域网总线检测,利用生成对抗网络设计一种实时入侵检测模型,可提高智能网联汽车的安全性。

智能网联车辆节能自适应巡航控制研究

现有车辆自适应巡航控制多专注于单一的轨迹跟踪目标,而决定控制技术实际应用效益的关键是系统的节能性能.为了能够同时保证跟踪误差收敛性与燃油经济性,研究了一种车辆节能自适应巡航控制器设计方法:首先以轨迹跟踪为目标,设计了具有时变反馈增益的状态反馈控制律;其次,以反馈增益为优化变量,以整个预测时域内各采样时刻自身车辆单位位移燃油消耗量的累加为代价函数,基于经济模型预测控制方法设计了节能控制算法,并通过构建共同Lyapunov函数,给出了保证跟踪误差以指数速度收敛的反馈增益选取范围;最后,通过数值仿真验证了控制器设计的有效性,定量展示了本文所提出的方法在降低燃油消耗量方面的有效性.

Model calibration concerning risk coefficients of driving safety field model

Driving safety field(DSF) model has been proposed to represent comprehensive driving risk formed by interactions of driver-vehicle-road in mixed traffic environment. In this work, we establish an optimization model based on grey relation degree analysis to calibrate risk coefficients of DSF model. To solve the optimum solution, a genetic algorithm is employed. Finally, the DSF model is verified through a real-world driving experiment. Results show that the DSF model is consistent with driver's hazard perception and more sensitive than TTC. Moreover, the proposed DSF model offers a novel way for criticality assessment and decision-making of advanced driver assistance systems and intelligent connected vehicles.

Engine-Map-Based Predictive Fuel-Efficient Control Strategies for a Group of Connected Vehicles

An engine-map-based predictive fuel-efficient control strategy for a group of connected vehicles is presented. A decentralizedmodel predictive control framework is formulated to predict the optimal velocity profile that compromises fuel economy andmobility while guaranteeing the safety of each vehicle. In the model predictive control framework, an engine-map-based fuelconsumption model is established by implementing a backward conventional vehicle model in the cost function. Moreover,the cost function is normalized by dividing each term by its reference value. An extra cost is added to the safety term when thedistance between adjacent vehicles drops to a critical value to guarantee vehicle safety, while another extra cost is consideredfor the velocity tracking term to prevent the violation of traffic rules. The results of simulation show the effectiveness of theproposed control method.

Pro-social control of connected automated vehicles in mixed-autonomy multi-lane highway traffic

We propose pro-social control strategies for connected automated vehicles(CAVs)to mitigate jamming waves in mixed-autonomy multi-lane traffic,resulting from car-following dynamics of human-driven vehicles(HDVs).Different from existing studies,which focus mostly on ego vehicle objectives to control CAVs in an individualistic manner,we devise a pro-social control algorithm.The latter takes into account the objectives(i.e.,driving comfort and traffic efficiency)of both the ego vehicle and surrounding HDVs to improve smoothness of the entire observable traffic.Under a model predictive control(MPC)framework that uses acceleration and lane change sequences of CAVs as optimization variables,the problem of individualistic,altruistic,and pro-social control is formulated as a non-convex mixed-integer nonlinear program(MINLP)and relaxed to a convex quadratic program through converting the piece-wise-linear constraints due to the optimal velocity with relative velocity(OVRV)car-following model into linear constraints by introducing slack variables.Low-fidelity simulations using the OVRV model and high-fidelity simulations using PTV VISSIM simulator show that pro-social and altruistic control can provide significant performance gains over individualistic driving in terms of efficiency and comfort on both single-and multi-lane roads.

Performance evaluation framework of Wyoming connected vehicle pilot deployment program: summary of Phase 2 pre-deployment efforts and lessons learned

Purpose–This paper aims to present a summary of the performance measurement and evaluation plan of the Wyoming connected vehicle(CV)Pilot Deployment Program(WYDOT Pilot).Design/methodology/approach–This paper identified 21 specific performance measures as well as approaches to measure the benefits of the WYDOT Pilot.An overview of the expected challenges that might introduce confounding factors to the evaluation effort was outlined in the performance management plan to guide the collection of system performance data.Findings–This paper presented the data collection approaches and analytical methods that have been established for the real-life deployment of the WYDOT CV applications.Five methodologies for assessing 21 specific performance measures contained within eight performance categories for the operational and safety-related aspects.Analyses were conducted on data collected during the baseline period,and pre-deployment conditions were established for 1 performance measures.Additionally,microsimulation modeling was recommended to aid in evaluating the mobility and safety benefits of the WYDOT CV system,particularly when evaluating system performance under various CV penetration rates and/or CV strategies.Practical implications–The proposed performance evaluation framework can guide other researchers and practitioners identifying the best performance measures and evaluation methodologies when conducting similar research activities.Originality/value–To the best of the authors’knowledge,this is thefirst research that develops performance measures and evaluation plan for low-volume rural freeway CV system under adverse weather conditions.This paper raised some early insights into how CV technology might achieve the goal of improving safety and mobility and has the potential to guide similar research activities conducted by other agencies.

基于多车状态变化特征的网联车跟驰模型

针对前车速度单双向突变引起的交通流不稳定问题,提出一种基于多车状态变化特征的网联车跟驰模型(MVSCF)。首先引入多前车加速度差变化特征和优化的速度期望估计改进MVCM模型;然后利用微小扰动法和约化摄动法求解MVSCF模型的临界稳定条件,同时结合环形道路场景推导多前车加速度差系数k、多前车数q和多前车最优速度权重ε的相对最优值;最后利用直行道路场景对比分析MVSCF模型在前车速度非平稳变化作用下的交通流稳定效果。仿真结果表明:前车速度单双向突变时,MVSCF模型能够较好吸收前车扰动,速度波动峰谷差值和加速度波动幅度均有所减小,有利于提升交通流的稳定性。

Technology acceptance comparison between on-road dynamic message sign and on-board human machine interface for connected vehicle-based variable speed limit in fog area

Purpose–Connected vehicle-based variable speed limit(CV-VSL)systems in fog area use multi-source detection data to indicate drivers to make uniform change in speed when low visibility conditions suddenly occur.The purpose of the speed limit is to make the driver’s driving behavior more consistent,so as to improve traffic safety and relieve traffic congestion.The on-road dynamic message sign(DMS)and on-board human–machine interface(HMI)are two types of warning technologies for CV-VSL systems.This study aims to analyze drivers’acceptance of the two types of warning technologies in fog area and its influencing factors.Design/methodology/approach–This study developed DMS and on-board HMI for the CV-VSL system in fog area on a driving simulator.The DMS and on-board HMI provided the driver with weather and speed limit information.In all,38 participants participated in the experiment and completed questionnaires on drivers’basic information,perceived usefulness and ease of use of the CV-VSL systems.Technology acceptance model(TAM)was developed to evaluate the drivers’acceptance of CV-VSL systems.A variance analysis method was used to study the influencing factors of drivers’acceptance including drivers’characteristics,technology types and fog density.Findings–The results showed that drivers’acceptance of on-road DMS was significantly higher than that of on-board HMI.The fog density had no significant effect on drivers’acceptance of on-road DMS or on-board HMI.Drivers’gender,age,driving year and driving personality were associated with the acceptance of the two CV-VSL technologies differently.This study is beneficial to the functional improvement of on-road DMS,on-board HMI and their market prospects.Originality/value–Previous studies have been conducted to evaluate the effectiveness of CV-VSL systems.However,there were rare studies focused on the drivers’attitude toward using which was also called as acceptance of the CV-VSL systems.Therefore,this research calculated the drivers’acceptance of two normally used CV-VSL systems including on-road DMS and on-board HMI using TAM.Furthermore,variance analysis was conducted to explore whether the factors such as drivers’characteristics(gender,age,driving year and driving personality),technology types and fog density affected the drivers’acceptance of the CV-VSL systems.