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A new road feel feedback control design of steer-by-wire (SBW) is proposed, which is produce the steering feel of conventional vehicle with equipped electronic power steering (EPS) system, due to SBW system removes mechanical linkages between steering system and front wheels. A dynamic model is established to study the road feel generation and deal with the need of computed rack force of steer system. Based on the analysis of the assisting characteristic and the active damping control strategy of the EPS system, an integrated road feel algorithm is proposed. For rack force is difficult to measure, an estimator is presented to estimate rack force by Kalman filter (KF). The hardware-in-the-loop simulation (HILS) test bench results show that the proposed road feel control design make drivers get road feel information and SBW system can improve the vehicle maneuverability and comfortably.

This paper introduces the characteristics of the 4 wheel independent driving/4 wheel independent steering (4WID/4WIS) electric vehicle (EV). Models of Subsystems and the vehicle are constructed based on Matlab/simulink. The vehicle model allows the inputs of different drive torques and steer angles of four wheels. The dynamic characteristics of drive motors and steer motors are considered, and also it can reflect the vehicle longitudinal dynamics change due to the increase of the mass and inertia of the four wheels. Besides, drive mode selection function that is unique to this type vehicle is involved. Simulations and analyses of crab, oblique driving and zero radius turning which are the special conditions of 4WID/4WIS EV are conducted. The results show that the model can reflect the dynamic response characteristics. The model can be used to the simulation analyses of handling, stability, energy saving and control strategies verification of 4WID/4WIS EVs.

Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap.

Impact torque will be generated on the steering wheel when one tire suddenly blows out on high way, which may cause driver's psychological stress and result in driver's certain misoperations on the car. In this paper, the model of tire blowout vehicle was established; the tire blowout was detected based on the change rate of tire pressure, meanwhile, the rack force caused by tire blowout was estimated through a reduce observer; finally the compensation current was figured out to reduce the impact torque on the steering wheel. Results of simulation tests showed that the control strategy proposed in this paper can effectively reduce the impact torque on the steering wheel and reduce the driver's discomfort caused by tire blowout.

The research of driver behavior characteristics has been a focus of vehicle handling and stability performance. With the driver preview effort, many different driver preview models of direction control have been proposed and the simulations of driver-vehicle-road closed-loop system made. But in the simulation, most of the conventional models have the same precondition that the road was simply described as a pre-given preview course. How to simulate the driver dynamically deciding vehicle preview course based on the real road circumstance is the key to the further research of the driver model. In this paper, a new driver direction control model is established, which is called the Optimal Preview Lateral Acceleration (OPLA) Model and divided into three sub-models: driver’s information identification model, driver’s fuzzy decision model of vehicle preview course and driver’s performance first-order correction model.

To address the current situation of the limited driver-vehicle cooperative steering actuation structure, this paper proposes a feasible driver-vehicle shared steering control actuation architecture based on the differential steering. Firstly, a shared steering execution architecture is established, which contains traditional steering system controlled by human driver and differential steering system acting as the automatic execution system. In this paper, a specific driver-vehicle shared control architecture is established with the front-wheel hub motor-based differential steering system and a single-view angle based human driver model. Then, an upper-level sliding mode controller for path tracking is developed and implemented as the automatic steering system, and the driver-vehicle shared control is achieved by the proposed non-cooperative game model.

Advanced driver assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This paper presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modeled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models.

The conventional radar modeling methods for automotive applications were either function-based or physics-based. The former approach was mainly abstracted as a solution of the intersection between geometric representations of radar beam and targets, while the latter one took radar detection mechanism into consideration by means of “ray tracing”. Although they each has its unique advantages, they were often unrealistic or time-consuming to meet actual simulation requirements. This paper presents a combined geometric and physical modeling method on millimeter-wave radar systems for Frequency Modulated Continuous Wave (FMCW) modulation format under a 3D simulation environment. With the geometric approach, a link between the virtual radar and 3D environment is established. With the physical approach, on the other hand, the ideal target detection and measurement are contaminated with noise and clutters aimed to produce the signals as close to the real ones as possible.

Vision-based Advanced Driver Assistance Systems (Vi-ADAS) has achieved rapid growth in recent years. Since vehicle field testing under various driving scenarios can be costly, tedious, unrepeatable, and often dangerous, simulation has thus become an effective means that reduces or partially replaces the conventional field testing in the early development stage. This paper proposes a quantitative assessment framework for model quality evaluation of 3D scene under simulation platform. An imaging model is first built. The problem of solving the imaging model is then transformed into the problem of intrinsic image decomposition. Based on Retinex theory and Non-local texture analyses, a superior intrinsic image decomposition method is adopted to evaluate the fidelity of the 3D scene model through the degree of deviation to the Reflectance and Shading intrinsic maps respectively.

This paper presents a novel real-time virtual simulation environment for advanced driver assistance systems (ADAS). The proposed environment mainly includes a 3D high-fidelity virtual driving environment developed with computer graphics technologies, a virtual camera model and a real-time hardware-in-the-loop (HIL) system with a driver simulator. Some preliminary simulation and experiment have been conducted to verify that the proposed virtual environment along with the image generated by a virtual camera model is valid with sufficient fidelity, and the real-time HIL development system with driver in the loop is effective in the early design, test and verification of ADAS systems.

This paper presents a novel approach of developing a vision-based forward collision warning system (FCW) under a virtual and real-time driving environment. The proposed environment mainly includes a 3D high-fidelity virtual driving environment developed with computer graphics technologies, a virtual camera model and a real-time hardware-in-the-loop (HIL) system with a driver simulator. Some preliminary simulation has been conducted to verify that the proposed virtual environment along with the image generated by a virtual camera model is valid with sufficient fidelity, and the real-time HIL development system with driver in the loop is effective in the early design, test and verification of the FCW and other similar ADAS systems.

A fault detection and diagnosis (FDD) algorithm of 4WID/4WIS Electric Vehicles has been proposed in this study aiming to find the actuator faults. The 4WID/4WIS EV is one of the promising architectures for electric vehicle designs which is driven independently by four in-wheel motors and steered independently by four steering motors. The 4WID/4WIS EVs have many potential abilities in advanced vehicle control technologies, but diagnosis and accommodation of the actuator faults becomes a significant issue. The proposed FDD approach is an important part of the active fault tolerant control (AFTC) algorithm. The main objective of the FDD approach is to monitor vehicle states, find the faulty driving motor and then feedback fault information to the controller which would adopt appropriate control laws to accommodate the post-fault vehicle control system.

This paper proposes a novel allocation-based control method for four-wheel independently actuated electric vehicles. In the proposed method, both actuator dynamics and input/output constraints are fully taken into consideration in the control design. First, the actuators are modeled as first-order dynamic systems with delay. Then, the control allocation is formulated as an optimization problem, with the primary objective of minimizing errors between the actual and desired control outputs. Other objectives include minimizing the power consumption and the slew rate of the actuator outputs. As a result, this leads to frequency-dependent allocation that reflects the bandwidth of each actuator. To solve the optimization problem, an efficient numerical algorithm is employed. Finally the proposed control allocation method is implemented to control a four-wheel independently actuated electric vehicle.

This paper proposed a novel fault-tolerant control method based on control allocation via dynamic constrained optimization for electric vehicles with XBW systems. The total vehicle control command is first derived based on interpretation on driver's intention as a set of desired vehicle body forces, which is further dynamically distributed to the control command of each actuator among vehicle four corners. A dynamic constrained optimization method is proposed with the cost function set to be a linear combination of multiple control objectives, such that the control allocation problem is transformed into a linear programming formulation. An analytical yet explicit solution is then derived, which not only provides a systematic approach in handling the actuation faults, but also is efficient and real-time feasible for in-vehicle implementation. The simulation results show that the proposed method is valid and effective in maintaining vehicle operation as expected even with faults.

An integrated control strategy for vehicle active suspension system which combines linear quadratic optimum control law with fuzzy control algorithm is designed to improve both ride and handling. The performance of this control strategy is then examined and assessed in an open-loop J-turn driving scenario on a random-rough road by means of computer simulation. Comparisons to a passive suspension system in terms of vehicle sprung mass vertical acceleration, body roll angle and yaw rate is conducted. Simulation results indicate that the integrated control strategy proposed in this paper could effectively enhance vehicle ride comfort meanwhile benefit handling quality and driving safety.

Intelligent driving, aimed for collision avoidance and self-navigation, is mainly based on environmental sensing via radar, lidar and/or camera. While each of the sensors has its own unique pros and cons, camera is especially good at object detection, recognition and tracking. However, unpredictable environmental illumination can potentially cause misdetection or false detection. To investigate the influence of illumination conditions on detection algorithms, we reproduced various illumination intensities in a photo-realistic virtual world, which leverages recent progress in computer graphics, and verified vehicle detection effect there. In the virtual world, the environmental illumination is controlled precisely from low to high to simulate different illumination conditions in the driving scenarios (with relative luminous intensity from 0.01 to 400). Sedan cars with different colors are modelled in the virtual world and used for detection task.

Electro-hydraulic power steering system (EHPS) maintains the advantages of Hydraulic power steering system (HPS) and Electric power steering system (EPS).It is even more superior than this two. In the foreseeable future, this system will have a certain development space. Assistant characters analysis was carried out in this paper. Control strategy based on steering states and feedback control strategy were designed too. Besides, aiming at the emergency steering conditions, steering angular velocity additional controlling strategy was brought out. Under emergency steering conditions, steering angular velocity additional controlling strategy will be applied. Additional steering moment will be calculated to ensure the assistant follow steering rapidly.

The slip ratio of vehicle driving wheels is easily beyond a reasonable range in the complex and changeable driving conditions. In order to achieve the adaptive acceleration slip regulation of four-wheel driving (4WD) vehicle, a fuzzy control strategy of Automatic Drive Train Management (ADM) system based on road situation identification was proposed in this paper. Firstly, the influence on the control strategy of ADM system was analyzed from two aspects, which included the different road adhesion coefficients and the vehicle’s ramp driving state. In the meantime several quantitative expressions of relevant control parameters were derived. Secondly, the fuzzy logic control algorithm was adopted to design a road situation identification subsystem and a ramp driving state identification subsystem respectively. The former was based on the μ-S curve model, and the latter was based on the vehicle driving equilibrium equation.

As a new form of electric vehicle, Four-wheel-independent electric vehicle with X-By-Wire (XBW) inherits all the advantages of in-wheel motor drive electric vehicles. The vehicle steering system is liberated from traditional mechanical steering mechanism and forms an advanced vehicle with all- wheel independent driving, braking and steering. Compared with conventional vehicles, it has more controllable degrees of freedom. The design of the integrated vehicle dynamics control systems helps to achieve the steering, driving and braking coordinated control and improves the vehicle's handling stability. In order to solve the problem of lacking of vehicle state information in the integrated control, some methods are used to estimate the vehicle state of four-wheel-independent electric vehicles with XBW. In order to improve the estimation accuracy, unscented Kalman filter (UKF) is used to estimate the vehicle state variables in this paper.

In order to improve the braking energy recovery and ensure the braking comfort, a new type of regenerative braking coordinated control algorithm is designed in this paper. The hierarchical control theory is used to the regenerative braking control algorithm. First, the front axle braking force and rear axle braking force are distributed. Then the rear axle motor braking force and mechanical braking force are distributed. Finally, the dynamic coordinated control strategy is designed to control pneumatic braking system and motor braking system. Aimed at keeping the fluctuation of the total braking force of friction and the regenerative braking force small during braking modes switch, a coordinated controller was designed to control the pneumatic braking system to compensate the error of the motor braking force. Based on Matlab/Simulink platform, a parallel hybrid electric bus simulation model with electric braking system (EBS) was established.