Longitudinal Control Strategy for Vehicle Adaptive Cruise Control Systems

A new longitudinal control strategy for vehicle adaptive cruise control （ACC） systems is presented. The running relationship between the ACC vehicle and the detected target vehicle is described by the relative velocity and the deviation between the actual headway distance and the prescribed safety distance. Based on this, two state space models are built and the linear quadratic optimal control theory is used to yield desired velocity for the ACC-equipped vehicle when with the target vehicle detected. By switching among four control modes, the desired velocity profile is designed to deal with different running situations. A velocity controller, which includes a PID controller for throttle openness and a neural network controller for brake application, is developed to achieve the desired velocity profile. The proposed control strategy is applied to a non-linear vehicle model in a simulation environment and is shown to provide the ACC vehicle comfortable ride and satisfying safety.

Cooperative Adaptive Cruise Control Platoon Fleet Formation Model Considering Efficiency and Stability

In the existing formation model,vehicles in the same lane or adjacent lane are regarded as the structure,and the driving behavior of vehicles is studied from the perspectives of safety,speed consistency,and stability,and the speed control model is proposed from the perspective of vehicles themselves,to obtain a stable fleet with the same distance and speed.However,in this process,the initial condition of the vehicle,the traffic flow environment,and the efficiency of the fleet formation are less considered.Therefore,based on summarizing the existing fleet building model,this paper puts forward the rapid construction model and algorithm of a cooperative adaptive cruise control platoon fleet.One of the important goals of forming a team is to enter the team with the smoothest trajectory in the shortest time.Therefore,this chapter studies the trajectory optimization of the vehicle formation process from the perspective of vehicle dynamics.

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.

New Adaptive Cruise Control Method

A new adaptive cruise control (ACC) method based on the desired safety headway distance is investigated for improving the vehicle traffic safety at high speed by regulating the additional throttle opening and braking torque of driving wheels only. The selection of headway distance sensors, the determination of desired safety headway distance and desired deceleration are elaborated. The ACC flowchart and simulation, as well as signal misinformation and its resolutions are described. The simulation proves that the new ACC method is simpler and feasible. The new method is easily integrated ACC with ABS/ASR to form an organic ABS/ASR/ACC system.

Connect & Drive:design and evaluation of cooperative adaptive cruise control for congestion reduction

Road throughput can be increased by driving at small inter-vehicle time gaps. The amplification of velocity disturbances in upstream direction, however, poses limitations to the minimum feasible time gap. This effect is covered by the notion of string stability. String-stable behavior is thus considered an essential requirement for the design of automatic distance control systems, which are needed to allow for safe driving at time gaps well below 1 s. Using wireless inter-vehicle communications to provide real-time information of the preceding vehicle, in addition to the information obtained by common Adaptive Cruise Control （ACC） sensors, appears to significantly decrease the feasible time gap, which is shown by practical experiments with a test fleet consisting of six passenger vehicles. The large-scale deployment of this system, known as Cooperative ACC （CACC）, however, poses challenges with respect to the reliability of the wireless communication system. A solution for this scalability problem can be found in decreasing the transmission power and/or beaconing rate, or adapting the communications protocol. Although the main CACC objective is to increase road throughput, the first commercial application of CACC is foreseen to be in truck platooning, since short distance following is expected to yield significant fuel savings in this case.

Target Vehicle Selection Algorithm for Adaptive Cruise Control Based on Lane-changing Intention of Preceding Vehicle

To improve the ride comfort and safety of a traditional adaptive cruise control(ACC)system when the preceding vehicle changes lanes,it proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention for the preceding vehicle.First,the Next Generation Simulation dataset is used to train a lane-changing intention prediction algorithm based on a sliding window support vector machine,and the lane-changing intention of the preceding vehicle in the current lane is identified by lateral position offset.Second,according to the lane-changing intention and collision threat of the preceding vehicle,the target vehicle selection algorithm is studied under three different conditions:safe lane-changing,dangerous lane-changing,and lane-changing cancellation.Finally,the effectiveness of the proposed algorithm is verified in a co-simulation platform.The simulation results show that the target vehicle selection algorithm can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels their lane change maneuver.In the case of a dangerous lane change,the target vehicle selection algorithm proposed in this paper can respond more rapidly to a dangerous lane change than the target vehicle selection method of the traditional ACC system;thus,it can effectively avoid collisions and improve the safety of the subject vehicle.

An Improved Cooperative Adaptive Cruise Control(CACC) Algorithm Considering Invalid Communication

For the Cooperative Adaptive Cruise Control （CACC） Algorithm, existing research studies mainly focus on how inter-vehicle communication can be used to develop CACC controller, the influence of the communication delays and lags of the actuators to the string stability. However, whether the string stability can be guaranteed when inter-vehicle communication is invalid partially has hardly been considered. This paper presents an improved CACC algorithm based on the sliding mode control theory and analyses the range of CACC controller parameters to maintain string stability. A dynamic model of vehicle spacing deviation in a platoon is then established, and the string stability conditions under improved CACC are analyzed. Unlike the traditional CACC algorithms, the proposed algorithm can ensure the functionality of the CACC system even if inter-vehicle communication is partially invalid. Finally, this paper establishes a platoon of five vehicles to simulate the improved CACC algorithm in MATLAB/Simulink, and the simulation results demonstrate that the improved CACC algorithm can maintain the string stability of a CACC platoon through adjusting the controller parameters and enlarging the spacing to prevent accidents. With guaranteed string stability, the proposed CACC algorithm can prevent oscillation of vehicle spacing and reduce chain collision accidents under real-world circumstances. This research proposes an improved CACC algorithm, which can guarantee the string stability when inter-vehicle communication is invalid.

Study on the Driving Style Adaptive Vehicle Longitudinal Control Strategy

This paper presents a fusion control strategy of adaptive cruise control(ACC) and collision avoidance(CA),which takes into account a driver’s behavioral style. First, a questionnaire survey was performed to identify driver type, and the corresponding driving behavioral data were collected via driving simulator experiments, which served as the template data for the online identification of driver type. Then, the driveradaptive ACC/CA fusion control strategy was designed, and its effect was verified by virtual experiments. The results indicate that the proposed control strategy could achieve the fusion control of ACC and CA successfully and improve driver adaptability and comfort.

Research on Directly Adaptive Fuzzy Algorithm Based ACC Controller

A directly adaptive fuzzy algorithm is applied in vehicle adaptive cruise control system. The basic principle of the adaptive fuzzy algorithm is analyzed. The initial value of the fuzzy based vector is given by the traditional fuzzy membership. Adaptive law of the adjustable parameters 6 is also determined. The directly adaptive fuzzy ACC controller is designed based on Matlab fuzzy toolbox. Matlab-Simulink is adopted to test the function of the adaptive fuzzy ACC controller. The control system is established using a 7 DOF vehicle dynamics model. Simulation results indicate that the principle of the method is correct and it performs well both in cruise and distance keeping.

Communication Resource-Efficient Vehicle Platooning Control With Various Spacing Policies

Platooning represents one of the key features that connected automated vehicles may possess as it allows multiple automated vehicles to be maneuvered cooperatively with small headways on roads. However, a critical challenge in accomplishing automated vehicle platoons is to deal with the effects of intermittent and sporadic vehicle-to-vehicle data transmissions caused by limited wireless communication resources. This paper addresses the co-design problem of dynamic event-triggered communication scheduling and cooperative adaptive cruise control for a convoy of automated vehicles with diverse spacing policies. The central aim is to achieve automated vehicle platooning under various gap references with desired platoon stability and spacing performance requirements, while simultaneously improving communication efficiency. Toward this aim, a dynamic event-triggered scheduling mechanism is developed such that the intervehicle data transmissions are scheduled dynamically and efficiently over time. Then, a tractable co-design criterion on the existence of both the admissible event-driven cooperative adaptive cruise control law and the desired scheduling mechanism is derived. Finally, comparative simulation results are presented to substantiate the effectiveness and merits of the obtained results.

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.

Resilient and Safe Platooning Control of Connected Automated Vehicles Against Intermittent Denial-of-Service Attacks

Connected automated vehicles(CAVs)serve as a promising enabler for future intelligent transportation systems because of their capabilities in improving traffic efficiency and driving safety,and reducing fuel consumption and vehicle emissions.A fundamental issue in CAVs is platooning control that empowers a convoy of CAVs to be cooperatively maneuvered with desired longitudinal spacings and identical velocities on roads.This paper addresses the issue of resilient and safe platooning control of CAVs subject to intermittent denial-of-service(DoS)attacks that disrupt vehicle-to-vehicle communications.First,a heterogeneous and uncertain vehicle longitudinal dynamic model is presented to accommodate a variety of uncertainties,including diverse vehicle masses and engine inertial delays,unknown and nonlinear resistance forces,and a dynamic platoon leader.Then,a resilient and safe distributed longitudinal platooning control law is constructed with an aim to preserve simultaneous individual vehicle stability,attack resilience,platoon safety and scalability.Furthermore,a numerically efficient offline design algorithm for determining the desired platoon control law is developed,under which the platoon resilience against DoS attacks can be maximized but the anticipated stability,safety and scalability requirements remain preserved.Finally,extensive numerical experiments are provided to substantiate the efficacy of the proposed platooning method.

Design of the pressure regulation algorithm for active braking in vehicle ACC system

To develop the pressure control algorithm for active braking of adaptive cruise control（ACC） system,a test bench with real parts of the tested vehicle is built.With the dynamic analysis of the active braking actuators,it is demonstrated that different duty of pulse-width modulation（PWM） signals could control the pressure changing rate of the wheel cylinder.To obtain that signal,a modified proportional-integral-differential（PID） control algorithm is developed using the variable parameter method,the control value reset method,the dead zone method and the integral saturation method.Experimental results show that the delay and overshoot of the pressure response could be reduced considerably using the modified PID algorithm compared with the conventional one.The proposed pressure control algorithm could be used for the further development of the ACC＇s controller.

Cooperative merging control strategy of connected and automated vehicles on highways

To improve traffic performance when on-ramp vehicles merge into the mainstream,a collaborative merging control strategy is proposed to determine the merging sequence and trajectory control of vehicles.Merging trajectory planning takes the minimization of vehicle acceleration as the optimization objective.Either the variational method or the quadratic programming method is utilized to determine arrival time,optimal time and control variables for each vehicle.As a supplement,the adaptive cruise control(ACC)model is used to calculate each control variable in each time interval on special occasions.Simulation results show that the cooperative merging control strategy outperforms the optimal control strategy.The root mean square(RMS)of acceleration and the root mean square error(RMSE)of time headway are significantly decreased,with the reductions up to 90.1%and 25.2%,respectively.Under the cooperative control strategy,the difference between the average speed and desired speed consistently approaches zero.In addition,few or no collisions occur.To conclude,the proposed strategy favours the improvements in passenger comfort,traffic efficiency,traffic stability and safety around highway on-ramps.

Stability analysis of traffic flow with extended CACC control models

To further investigate car-following behaviors in the cooperative adaptive cruise control（CACC） strategy,a comprehensive control system which can handle three traffic conditions to guarantee driving efficiency and safety is designed by using three CACC models.In this control system,some vital comprehensive information,such as multiple preceding cars’ speed differences and headway,variable safety distance（VSD） and time-delay effect on the traffic current and the jamming transition have been investigated via analytical or numerical methods.Local and string stability criterion for the velocity control（VC） model and gap control（GC） model are derived via linear stability theory.Numerical simulations are conducted to study the performance of the simulated traffic flow.The simulation results show that the VC model and GC model can improve driving efficiency and suppress traffic congestion.

A Progressive Deployment Strategy for Cooperative Adaptive Cruise Control to Improve Trafc Dynamics

Cooperative adaptive cruise control(CACC)vehicles are intelligent vehicles that use vehicular ad hoc networks(VANETs)to share trafc information in real time.Previous studies have shown that CACC could have an impact on increasing highway capacities at high market penetration.Since reaching a high CACC market penetration level is not occurring in the near future,this study presents a progressive deployment approach that demonstrates to have a great potential of reducing trafc congestions at low CACC penetration levels.Using a previously developed microscopic trafc simulation model of a freeway with an on-ramp—created to induce perturbations and trigger stop-and-go trafc,the CACC system s efect on the trafc performance is studied.The results show signifcance and indicate the potential of CACC systems to improve trafc characteristics which can be used to reduce trafc congestion.The study shows that the impact of CACC is positive and not only limited to a high market penetration.By giving CACC vehicles priority access to high-occupancy vehicle(HOV)lanes,the highway capacity could be signifcantly improved with a CACC penetration as low as 20%.

Real-time optimization of energy consumption under adaptive cruise control for connected HEVs

This paper presents a real-time energy optimization algorithm for a hybrid electric vehicle(HEV)that operates with adaptive cruise control(ACC).Real-time energy optimization is an essential ssue such that the HEV powertrain system is as efficient as possible.With connected vehice technique,ACC system shows considerable potential of high energy eficiency.Combining a classical ACC algorithm,a two-level cooperative control scheme is constructed to realize real-time power distribution for the host HEV that operates in a vehicle platoon.The proposed control strategy actually provides a solution for an optimal control problem with multi objectives in terms of string stable of vehicle platoon and energy consumption minimization of the individual following vehicle.The string stability and the real-time optimization performance of the cooperative control system are confirmed by simulations with respect to several operating scenarios.

Model predictive control for adaptive cruise control with multi-objectives: comfort,fuel-economy,safety and car-following

For automated vehicles,comfortable driving will improve passengers’ satisfaction.Reducing fuel consumption brings economic profits for car owners,decreases the impact on the environment and increases energy sustainability.In addition to comfort and fuel-economy,automated vehicles also have the basic requirements of safety and car-following.For this purpose,an adaptive cruise control (ACC) algorithm with multi-objectives is proposed based on a model predictive control (MPC) framework.In the proposed ACC algorithm,safety is guaranteed by constraining the inter-distance within a safe range; the requirements of comfort and car-following are considered to be the performance criteria and some optimal reference trajectories are introduced to increase fuel-economy.The performances of the proposed ACC algorithm are simulated and analyzed in five representative traffic scenarios and multiple experiments.The results show that not only are safety and car-following objectives satisfied,but also driving comfort and fuel-economy are improved significantly.

Vehicle adaptive cruise control design with optimal switching between throttle and brake

For vehicle adaptive cruise control （ACC） systems, the switching performance between throttle and brake determines the driving comfort, fuel consumption and service lives of vehicle mechanical components. In this paper, an ACC algorithm with the optimal switching control between throttle and brake is designed in model predictive control （MPC） framework. By introducing the binary integer variables, the dynamics of throttle and brake are integrated in one model expression for the controller design. Then the ACC algorithm is designed to satisfy not only safe car following, but also the optimal switching between throttle and brake, which leads to an online mixed integer quadratic programming solved by the nested two-loop method. The simulation results show that the proposed ACC algorithm meets the requirements of safe car following, outperforms the traditional algorithms by performing smoother responses, reducing the switching times between throttle and brake, and therefore improves driving comfort and fuel efficiency significantly.

Cooperative Adaptive Cruise Control Using Delay-Based Spacing Policy:A Robust Adaptive Non-Singular Terminal Sliding Mode Approach

This study proposes two speed controllers based on a robust adaptive non-singular terminal sliding mode control approach for the cooperative adaptive cruise control problem in a connected and automated vehicular platoon.The delay-based spacing policy is adopted to guarantee that all vehicles in the platoon track the same target velocity profile at the same position while maintaining a predefined time gap.Factors such as nonlinear vehicle longitudinal dynamics,engine dynamics with time delay,undulating road profiles,parameter uncertainties,and external disturbances are considered in the system modeling and controller design.Different control objectives are assigned to the leading and following vehicles.Then,controllers consisting of a sliding mode controller with parameter adaptive laws based on the ego vehicle’s state deviation and linear coupled state errors,and a Smith predictor for time delay compensation are designed.Both inner stability and strong string stability are guaranteed in the case of nonlinear sliding manifolds.Finally,the effectiveness of the proposed controllers and the benefits of 44.73%shorter stabilization time,11.20%less speed overshoot,and virtually zero steady-state inner vehicle distance deviation are illustrated in a simulation study of a seven-vehicle platoon cooperative adaptive cruise control and comparison experiments with a coupled sliding mode control approach.