Abstract Many surveys on vehicle traffic safety have shown that the tire road friction coefficient (TRFC) is correlated with probability of an accident. The accidents increases sharply slippery surfaces. Therefore, accurate knowledge TRFC contributes to optimization driver maneuvers for further improving intelligent vehicles. A large number researchers employed different tools and proposed algorithms obtain TRFC. This work investigates these methods been widely utilized estimate These are...

Long queues of vehicles are often found at signalized intersections, which increases the energy consumption all involved. This paper proposes an enhanced eco-approach control (EEAC) strategy with consideration queue ahead for connected electric (EVs) a intersection. The discharge movement vehicle is predicted by improved prediction method (IQDP), takes both and driver dynamics into account. Based on queue, EEAC designed hierarchical framework: upper-stage uses dynamic programming to find...

Preceding vehicles typically dominate the movement of following in traffic systems, thereby significantly influencing efficacy eco-driving control that concentrates on vehicle speed optimization. To potentially mitigate negative effect preceding at signalized intersection, this study proposes an overtaking-enabled eco-approach (OEAC) strategy. It combines driving lane planning and optimization for connected automated to relax first-in-first-out queuing policy minimizing host vehicle's energy...

Data-driven cooperative control of connected and automated vehicles (CAVs) has gained extensive research interest as it can utilize collected data to generate actions without relying on parametric system models that are generally challenging obtain. Existing methods mainly focused improving traffic safety stability, while less emphasis been placed energy efficiency in the presence uncertainties diversities human-driven (HDVs). In this brief, we employ a Data-EnablEd Predictive Control...

The accurate information of sideslip angle (SA) and tire cornering stiffness (TCS) is essential for advanced chassis control systems. However, SA TCS cannot be directly measured by in-vehicle sensors. Thus, it a hot topic to estimate with only sensors an effective estimation method. In this article, we propose novel fuzzy adaptive robust cubature Kalman filter (FARCKF) accurately TCS. model parameters the FARCKF are dynamically updated using recursive least squares. A Takagi–Sugeno system...

Some vehicle state information that cannot be measured by in-vehicle sensors is quite important for the active safety control of intelligent vehicles. To obtain these key in real-time, many advanced estimation algorithms are proposed. However, existing studies focus on effect sensor measurement noise accuracy and rarely consider impact data loss. In this article, a novel adaptive fault-tolerant extended Kalman filter proposed to estimate case partial loss data. The randomness first defined...

Eco-cruising control of vehicles is a potential approach for improving vehicle energy efficiency and reducing travel time. However, many eco-cruising studies merely focused on longitudinal speed optimization but overlooked the lane change maneuvers, which may impair benefits when encounters slowly moving preceding (PV). This study proposes flexible strategy (FECS) with efficient driving planning capabilities simultaneously connected automated (CAVs). The FECS designed hierarchical framework,...

This paper presents an adaptive leading cruise control strategy for the automated vehicle (AV) and first considers its impact on following human-driven (HDV) with diverse driving characteristics in unified optimization framework improved holistic energy efficiency. The car-following behaviors of HDV are statistically calibrated using Next Generation Simulation dataset. In a typical single-lane scenario where AVs HDVs share road, longitudinal speed can substantially reduce consumption by...

The traffic light in urban areas dominates the flow, resulting variation of energy consumption vehicles involved. To mitigate impact bias on efficiency electric (EVs), this article proposes an event-driven energy-efficient driving control (EEDC) strategy based a receding horizon two-stage framework, which harnesses Internet Vehicles to incorporate and preceding vehicle for adaption different scenarios. At core first stage are event classification rules, classified scenarios into four events....

Abstract Most researches focus on the regenerative braking system design in vehicle components control and torque distribution, few combine connected technologies into velocity planning. If intention is accessed by vehicle-to-everything communication, electric vehicles (EVs) could plan for recovering more kinetic energy. Therefore, this paper presents an energy-optimal strategy (EOBS) to improve energy efficiency of EVs with consideration shared intention. First, a double-layer scheme...

Optimizing speed profiles at urban signalized intersections, commonly referred to as an eco-driving strategy, is acknowledged a promising approach improving vehicle energy efficiency. However, the unpredictable nature of traffic signals and flow can reduce effectiveness such strategies. This paper proposes strategy based on constraint-enforced reinforcement learning (CE-RL) for connected automated vehicles (CAVs) between multiple taking into account influence preceding vehicles. First,...

Precise localization is critical to safety for connected and automated vehicles (CAV). The global navigation satellite system the most common vehicle positioning method has been widely studied improve accuracy. In addition single-vehicle localization, some recently developed CAV applications require accurate measurement of inter-vehicle distance (IVD). Thus, this paper proposes a cooperative framework that shares absolute position or pseudorange by using V2X communication devices estimate...

Accurate estimation of the vehicle state is quite significant for efficacy advanced active safety systems. To improve vehicles, this paper focuses on state, in which a robust cubature Kalman algorithm proposed to estimate yaw rate, sideslip angle, and speed. A three-degree-of-freedom (TDOF) dynamics model first established. Based developed model, filter used state. Finally, both simulation experimental tests are carried out demonstrate effectiveness method. The test results indicate that...

The researches on eco-driving at signalized intersection usually ignores the waiting queue. However, host vehicle (HV) may be blocked by queue, and introduces superfluous energy consumption emission. Thus, this paper presents an strategy a with consideration of First, improved queue prediction method is developed to predict movement, for providing green window that ensures HV can pass through energy-savingly efficiently. Second, energy-optimal control problem formulated combining passing...

摘要: 针对车辆高速紧急工况下的主动避撞问题,提出一种基于工况辨识的自适应避撞控制策略。以实时交通环境信息与车辆状态信息为基础构建一种紧急工况避撞模式分类方法,该方法把紧急工况避撞模式分为制动避撞、转向避撞、协调避撞三种模式。对于制动避撞模式,设计一种考虑路面附着条件和驾乘人员舒适度的纵向制动避撞策略;对于转向操纵避撞模式,构建基于多项式路径规划的避撞策略;对于制动和转向协调避撞模式,设计一种基于数据驱动的自学习协调控制策略。不同控制策略的期望输出通过比例积分微分(Proportional integral differentiation, PID)下层控制器对期望值进行跟踪来完成避撞。在Matlab/Simulink环境中搭建Simulink-Carsim汽车紧急避撞控制联合仿真平台,基于该平台进行多种工况的虚拟试验来验证控制系统的实时性和有效性。结果表明,控制系统能自动有效识别当前紧急工况该采取何种避撞操纵,在完成避撞的同时也能保证车辆的稳定性。