Detection and Mitigation of Sensor and CAN Bus Attacks in Vehicle Anti-Lock Braking Systems

For a modern vehicle, if the sensor in a vehicle anti-lock braking system (ABS) or controller area network (CAN) bus is attacked during a brake process, the vehicle will lose driving direction control and the driver’s life will be highly threatened. However, current methods for detecting attacks are not sufficiently accurate, and no method can provide attack mitigation. To ensure vehicle ABS security, we propose an attack detection method to accurately detect both sensor attack (SA) and CAN bus attack in a vehicle ABS, and an attack mitigation strategy to mitigate their negative effects on the vehicle ABS. In our attack detection method, we build a vehicle state space equation that considers the real-time road friction coefficient to predict vehicle states (i.e., wheel speed and longitudinal brake force) with their previous values. Based on sets of historical measured vehicle states, we develop a search algorithm to find out attack changes (vehicle state changes because of attack) by minimizing errors between the predicted vehicle states and the measured vehicle states. In our attack mitigation strategy, attack changes are subtracted from the measured vehicle states to generate correct vehicle states for a vehicle ABS. We conducted the first real SA experiments to show how a magnet affects sensor readings. Our simulation results demonstrate that our attack detection method can detect SA and CAN bus attack more accurately compared with existing methods, and also that our attack mitigation strategy almost eliminates the attack’s effects on a vehicle ABS.

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.

Permitted speed decision of single-unit trucks with emergency braking maneuver on horizontal curves under rainy weather

Under adverse weather conditions, visibility and the available pavement friction are reduced. The improper selection of speed on curved road sections leads to an unreasonable distribution of longitudinal and lateral friction, which is likely to cause rear-end collisions and lateral instability accidents. This study considers the combined braking and turning maneuvers to obtain the permitted vehicle speed under rainy conditions. First, a braking distance computation model was established by simplifying the relationship curve between brake pedal force, vehicle braking deceleration, and braking time. Different from the visibility commonly used in the meteorological field, this paper defines "driver’s sight distance based on real road scenarios" as a threshold to measure the longitudinal safety of the vehicle. Furthermore, the lateral friction and rollover margin is defined to characterize the vehicle’s lateral stability. The corresponding relationship between rainfall intensity-water film thickness-road friction is established to better predict the safe speed based on the information issued by the weather station. It should be noted that since the road friction factor of the wet pavement not only determined the safe vehicle speed but also be determined by the vehicle speed, so we adopt Ferrari’s method to solve the quartic equation about permitted vehicle speed. Finally, the braking and turning maneuvers are considered comprehensively based on the principle of friction ellipse. The results of the TruckSim simulation show that for a single-unit truck, running at the computed permitted speed, both lateral and longitudinal stability meet the requirements. The proposed permitted vehicle speed model on horizontal curves can provide driving guidance for drivers on curves under rainy weather or as a decision-making basis for road managers.

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 the Road Friction Database for Automated Driving: Fundamental Consideration of the Measuring Device for the Road Friction Database

This study deals with the possibility of construction of a 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. At these levels of automated driving, the controller needs to control the vehicle. However, the road surface condition, especially the road friction coefficient on wet roads and 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 continuous measurement of the road friction characteristics, such as the μ-s characteristics. It is shown that the μ-s characteristics are continuously measured using the MF generally used in tire engineering, and the friction characteristics identified from the results are sufficiently satisfactory.

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.