###### Abstract  
Focusing on safety, comfort and with an overall aim of the comprehensive improvement of a vision-based intelligent vehicle, a novel Advanced Emergency Braking System (AEBS) is proposed based on Nonlinear Model Predictive Algorithm. Considering the nonlinearities of vehicle dynamics, a vision-based longitudinal vehicle dynamics model is established. On account of the nonlinear coupling characteristics of the driver, surroundings, and vehicle itself, a hierarchical control structure is proposed to decouple and coordinate the system. To avoid or reduce the collision risk between the intelligent vehicle and collision objects, a coordinated cost function of tracking safety, comfort, and fuel economy is formulated. Based on the terminal constraints of stable tracking, a multi-objective optimization controller is proposed using the theory of non-linear model predictive control. To quickly and precisely track control target in a finite time, an electronic brake controller for AEBS is designed based on the Nonsingular Fast Terminal Sliding Mode (NFTSM) control theory. To validate the performance and advantages of the proposed algorithm, simulations are implemented. According to the simulation results, the proposed algorithm has better integrated performance in reducing the collision risk and improving the driving comfort and fuel economy of the smart car compared with the existing single AEBS. intelligent vehicle; Advanced Emergency Braking System; nonlinear model predictive control; hierarchical control; Nonsingular Fast Terminal Sliding Mode +
Footnote †: journal: Applied  
force and lateral stability force of the vehicle [1; 2; 3]. Four Wheel Steering (4 WS) is used to improve the handling stability performance of the vehicle using the two rear wheels as the steering wheel, in addition to the traditional front wheel [4; 5]. Electronic Stability Program (ESP) or Electronic Stability Control (ESC) uses differential braking to improve vehicle stability, extending the existing ABS system [6; 7; 8]. However, most of those systems mainly focus on a single function and cannot solve the increasing conflict between functions; hence, an integrated control system is gradually becoming a research hotspot that can effectively coordinate these conflicts [9; 10]. Examples include a combined system of active suspension system and ESP, an active front steer angle control system, and a direct yaw moment control system [11; 12; 13]. An integrated ABS and ESP system is one of the most commonly used integrated systems; it assists drivers in controlling the vehicle to avoid road accidents in complex braking maneuvers based on different control algorithms, such as the fuzzy logic theory [14]. Furthermore, advanced driver assistance and unmanned intelligent vehicle technology have been popular in solving the interaction between driver and surroundings and promoting vehicle handling safety and comfort [15; 16; 17; 18; 19]. During the last decade, Intelligent Vehicles and Transportation Systems have achieved several significant developments [20; 21; 22], which has improved the vehicle safety, comfort, efficiency, and intelligence [23; 24; 25]. By vehicle-to-vehicle (V2V) communication technology such as Dedicated Short Range Communications (DSRC), the vehicle gets information not only from itself, but preview information from the vehicle in front, which can drastically reduce collisions and fuel consumption due to changing speed [25; 26]. Based on adaptive cruise control (ACC), cooperative adaptive cruise control (CACC) has been developing rapidly, and can effectively improve the traffic capacity, efficiency, and fluency [27; 28]. The combined information from front onboard sensors is used to control the lateral movement of autonomous vehicles [29; 30; 31; 32]. The combined solution of one-dimensional and two-dimensional information is applied to collision avoidance via steering assistance, automatic braking, and warning of collisions for urban vehicles [33].