Optimal Spacing Policy for Vehicle Platoon Control with Road-Friction Coefficient

This paper investigates the vehicle platoon control problems, in which the road-friction coefficient is taken into consideration. In order to improve the vehicle platoon safety in various road-friction conditions, an optimal spacing policy is proposed for the vehicle platoon. In detail, an intervehicle space optimization framework is developed by using a safety cost function and the gradient decent method. In this way, the optimal intervehicle spacing headway is presented such that the vehicle can be safely driven to the desired platoon under various road-friction conditions. Then, based on the proposed optimal spacing policy, we transform this optimal spacing vehicle platoon control problem into a moving target tracking problem. An adaptive distributed integrated sliding mode (DISM)-based vehicle platoon control scheme is proposed such that the vehicles can effectively follow the presented optimal spacing platoon. Moreover, the stability of the proposed vehicle platoon system is strictly analyzed and numerical simulations are provided to verify the proposed approaches.

Vehicle Lateral Velocity Estimation Based on Long Short-Term Memory Network

Lateral velocity is an important parameter to characterize vehicle stability. The acquisition of lateral velocity is of great significance to vehicle stability control and the trajectory following control of autonomous vehicles. Aiming to resolve the problems of poor estimation accuracy caused by the insufficient modeling of traditional model-based methods and significant decline in performance in the case of a change in road friction coefficient, a deep learning method for lateral velocity estimation using an LSTM, long-term and short-term memory network, is designed. LSTM can well reflect the inertial characteristics of vehicles. The training data set contains sensor data under various working conditions and roads. The simulation results show that the prediction model has high accuracy in general and robustness to the change of road friction coefficient.

Study on Road Friction Database for Automated Driving - Fundamental Consideration of Measuring Device for Road Friction Database -

This research deals with the possibility for construction of the database on the braking friction coefficient for actual roads from the viewpoint of traffic safety especially for automated driving such as level 4 or higher. In an automated driving such levels, the controller needs to control the vehicle, but the road surface condition, especially the road friction coefficient on wet roads, snowy or icy roads, changes greatly, and in some cases, changes by almost one order. Therefore, it is necessary for the controller to constantly collect environment information such as the road friction coefficients and prepare for emergencies such as obstacle avoidance. However, at present, the measurement of the road friction coefficients is not systemically performed, and a method for accurately measuring has not been established. In order to improve this situation, this study examines a method for continuously measurement for the road friction characteristics such as μ-s characteristics.

Robust Vehicle Dynamics Control for a Sharp Curve With Uncertain Road Condition

Recently, more and more research has been conducted to develop Connected Autonomous Vehicles (CAVs) applications that ensures the safety driving of CAVs under some extreme situations. This brief presents a robust control strategy for CAVs to preserve a precise tracking performance and maintain the stability of lateral dynamics when passing a sharp curve with uncertain road friction coefficient changes. In the proposed robust lateral dynamics control, robust optimization-based lateral dynamics controller is designed to achieve the stability of the lateral dynamics with the consideration of the road friction coefficient uncertainty. Simulation validations are carried out to evaluate the proposed control strategy. The results show that the robust optimization-based lateral dynamics can improve the robustness even with the uncertainty of the road friction coefficient.

A simulation based large bus side slip and rollover threshold study in slope-curve section under adverse weathers

To study the side slip and rollover threshold of large bus in slope–curve section under adverse weather, factors that affect the safety of large buses that run in slope–curve section, such as rain, snow, cross-wind environmental factors, and road geometry, were analyzed to obtain the friction coefficient of the road surface under different rainfall and snowfall intensities through field measurements and to determine the six-component force coefficient of wind that acts on large buses through wind tunnel tests. The force analysis of large bus in slope-curve section was carried out, and the mechanical equations of large bus under the limit conditions of sideslip and rollover in slope-curve section were established. TruckSim simulation test platform was used to establish a three-dimensional road model and large bus mechanical model at a design speed of 100 km/h. Input parameters, such as cross-wind speed and road friction coefficient, simulate the impact of wind-rain/snow coupling. Under the combined action of wind-rain/snow, the operation test of large bus in slope-curve section was carried out, and the key parameters and indicators of the sideslip and rollover of large bus in slope-curve section were outputted and analyzed. The sudden change point of lateral acceleration is the judging condition for sideslip of large bus in slope-curve section under different road friction coefficient (0.2–0.7), changing from 0.15m/s2 and stabilizing to 0.52 m/s2, and a 0N vertical reaction force of the inner tire is the critical judging condition for rollover under road friction coefficient0.8, and the operating speed thresholds were proposed under different road friction coefficient. This study is expected to provide theoretical support for the speed limit of large bus in slope-curve section under adverse weather.

Handling Enhancement of Autonomous Emergency Steering for Reduced Road Friction Using Steering and Differential Braking

Steering has more potential than braking to prevent rear-end collisions at higher relative velocities. A path tracking controller based on multi-input multi-output (MIMO) model predictive control (MPC) is proposed to enhance the handling performance of autonomous emergency steering in this paper. A six-state MIMO bicycle model including actuator dynamics of steering and differential braking is used for model prediction. Two control inputs are front wheel steering angle and direct yaw moment. Two model outputs are lateral displacement and heading angle. According to the work load ratios at four wheels, control allocation is used to determine the optimal braking force distribution to prevent tire force saturation. The performance of a single-input single-output (SISO) MPC that uses only steering angle control to track the lateral displacement of the desired path is employed to benchmark the performance of the proposed algorithm. Simulation results show that both SISO MPC and MIMO MPC can track the path on nominal road surface with high road friction coefficient of 0.9. For a road surface with medium road friction coefficient of 0.7, the SISO MPC is unable to track the path and loses directional stability. However, the MIMO MPC can still track the path and demonstrate robust path tracking and handling enhancement against model uncertainty due to reduced road friction.

A review on identification methods of road friction coefficient

Background: The development of the tire/road friction coefficient measurement and estimation system has far-reaching significance for the active electronic control safety system of automobiles and is one of the core technologies for autonomous driving in the future. Objective: Estimating the road friction coefficient accurately and in real-time has become the leading research direction. Researchers have used different tools and proposed different algorithms and patents. These methods are widely used to estimate the road friction coefficient or other related parameters. This paper gives a comprehensive description of the research status in the field of road friction coefficient estimation. Method: According to the current research status of Chinese and foreign scholars in the field of road friction coefficient recognition, the recognition methods are mainly divided into two categories: Cause-based and Effect-based. Results: This literature review will discuss the existing two types of identification methods (Cause-based and Effect-based), and the applicable characteristics of each algorithm are analyzed. Conclusion: The two recognition methods are analyzed synthetically, and the development direction of road friction coefficient recognition technology is discussed.