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Modelling of disc in brake squeal analysis is complicated because of the rotation of disc and the sliding contact between disc and pads. Many analytical or analytical numerical combined modeling methods have been developed considering the disc brake vibration and squeal as a moving load problem. Yet in the most common used complex eigenvalue analysis method, the moving load nature normally has been ignored. In this paper, a new modelling method for rotating disc from the point of view of modal is presented. First finite element model of stationary disc is built and modal parameters are calculated. Then the dynamic response of rotating disc which is excited and observed at spatial fixed positions is studied. The frequency response function is derived through space and time transformations. The equivalent modal parameter is extracted and expressed as the function of rotation speed and original stationary status modal parameters.

Transport vehicles consume a large amount of fuel with low efficiency, which is significantly affected by drivers' behaviors. An assessment system of eco-driving pattern for buses could identify the deficiencies of driver operation as well as assist transportation enterprises in driver management. This paper proposes an assessment method regarding drivers' economic efficiency, considering driving conditions. To this end, assessment indexes are extracted from driving economy theories and ranked according to their effect on fuel consumption, derived from a database of 135 buses using multiple regression. A layered structure of assessment indexes is developed with application of AHP, and the weight of each index is estimated. The driving pattern score could be calculated with these weights.

The interactions between automatic controls, physics, and driver is an important step towards highly automated driving. This study investigates the dynamical interactions between human-selected driving modes, vehicle controller and physical plant parameters, to determine how to optimally adapt powertrain control to different human-like driving requirements. A cyber-physical system (CPS) based framework is proposed for co-design optimization of the physical plant parameters and controller variables for an electric powertrain, in view of vehicle’s dynamic performance, ride comfort, and energy efficiency under different driving modes. System structure, performance requirements and constraints, optimization goals and methodology are investigated. Intelligent powertrain control algorithms are synthesized for three driving modes, namely sport, eco, and normal modes, with appropriate protocol selections. The performance exploration methodology is presented.

Threat assessment (TA) method is vital in the decision-making process of intelligent vehicles (IVs), especially for ADAS systems. In the research of TA, the probabilistic threat assessment (PTA) method is acting an increasing role, which can reduce the uncertainties of driver’s maneuvers. However, the driver behavior model (DBM) used in present PTA methods was mainly constructed by limited data or simple functions, which is not entirely reasonable and may affect the performance of the TA process. This work aims to utilize crash data extracted from Event Data Recorder (EDR) to establish more accurate DBM and improve the current PTA method in rear-end situations. EDR data with responsive maneuvers were firstly collected, which were then employed to construct the initial DBM (I-DBM) model by using the multivariate Gaussian distribution (MGD) framework. Besides, the model was further subdivided into six parts by two important risk indicators, Time-to-collision (TTC) and velocity.

Automotive safety is always the focus of consumers, the selling point of products, the focus of technology. In order to achieve automatic driving, interconnection with the outside world, human-automatic system interaction, the security connotation of intelligent and connected vehicles (ICV) changes: information security is the basis of its security. Functional safety ensures that the system is operating properly. Behavioral safety guarantees a secure interaction between people and vehicles. Passive security should not be weakened, but should be strengthened based on new constraints. In terms of information safety, the threshold for attacking cloud, pipe, and vehicle information should be raised to ensure that ICV system does not fail due to malicious attacks. The cloud is divided into three cloud platforms according to functions: ICVs private cloud, TSP cloud, public cloud.

Generally, noise will occur during steering with the hydraulic power steering system (hereinafter HPS). The noise producing in the rotary valve takes up a big proportion of the total one. To study the noise in the control valve, 2-D meshes of the flow field between the sleeve and the rotor were set up and a general CFD code-Fluent was used to analyze the flow inside the valve. The areas where the noise may be occurred were shown and some suggestions to silence the noise were given.

An energy management strategy is needed to optimally allocate the driver's power demands to different power sources in the fuel cell hybrid vehicles. The driver's power demand is modelled as a Markov process in which the transition probabilities are estimated on the basis of the observed sample paths. The Markov Decision Process (MDP) theory is applied to design a stochastic energy management strategy for fuel cell hybrid vehicles. This obtained control strategy was then tested on a real time simulation platform of the fuel cell hybrid vehicles. In comparison to the other 3 strategies, the constant bus voltage strategy, the static optimization strategy and the dynamic programming strategy, simulations in the Beijing bus driving cycle demonstrate that the obtained stochastic energy management strategy can achieve better performance in fuel economy in the same demand of dynamic.

Studying traffic accidents by using naturalistic driving data has become increasingly appealing for its potential benefits in improving road safety. This paper presents findings from a field test which has been conducted on 50 taxis in the urban areas of Beijing for 10 months using Video Drive Recorders (VDRs). The VDR used in this study could record the information of vehicle front view video, vehicle states, as well as driver operations immediately before and after an event. The drivers were given no specific instructions during the test, and the instrumentation for data collection was unobtrusive. Important safety-relevant parameters, such as vehicle speed, pre-event maneuver, time headway, time-to-collision, and driver reaction time, were calculated with precision. Based on these parameters, an analysis into features and causes of rear-end conflicts is performed.

Hydraulically damped rubber mount (HDM) can effectively attenuate vibrations transmitting between automotive powertrain and body/chassis, and reduce interior noise of car compartment. This paper involves an analytical qualitative analysis approach of dynamics characteristics of HDM. Analysis of experimental results verifies the effectiveness of the qualitative analysis approach. Frequency- and amplitude-dependent dynamic characteristic of HDM are investigated to clarify working mechanism of HDM. The presented qualitative analysis approach provides a convenient performance adjustment guideline of HDM to meet vibration isolation requirements of powertrain mount system.

Modelling of disc is crucial in analyzing brake squeal since the disc rotates past the non-rotating pads and the pads are coupled with different areas of the disc at different times. However, in most of the complex eigenvalue analysis of brake squeal, the effect of disc rotation was ignored. This paper proposes a closed-loop coupling model for brake squeal analysis. A modal parameter-based rotating disc model, whose dynamic behavior is represented by rotation speed-dependent equivalent modal parameters, is built through space and time-frequency transformation between reference and moving coordinate systems. The orthogonality of the equivalent modal parameters in state-space is derived. By performing modal synthesis in state-space, the rotating disc is incorporated into brake squeal closed-loop coupling model with other stationary components. Dynamic instability of the system is solved through complex eigenvalue analysis in state-space.

Neutral-idle strategy has been applied for years to improve the fuel consumption of automatic transmission cars. The updated demand is the use of expanded slipping control strategy for further improvement of the transmission efficiency and response speed. However, one major drawback of the continuous slipping clutches is the high tendency to produce shudder or low frequency variation. In this research, a special neutral-idle shudder phenomenon is presented. This special shudder is not only related to slipping clutches but also related to the vibration and structure of the powertrain system. Simulations and experiments are conducted to give an insight view of this phenomenon. The analysis reveals that this special shudder is caused by both torsional vibration of the driveline and rigid-body vibration of the powertrain system. A positive feedback loop between those two kinds of vibrations leads to this special neutral-idle shudder.

Highway traffic safety has been the most serious problem in current society, statistics show that about 70% to 90% of accidents are caused by driver operational errors. The autonomous emergency braking (AEB) is one of important vehicle intelligent safety technologies to avoid or mitigate collision. The AEB system applies the vehicle brakes when a collision is eminent in spite of any reaction by the driver. In some technologies, the system forewarns the driver with an acoustic signal when a collision is still avoidable, but subsequently applies the brakes automatically if the driver fails to respond. This paper presents the development and implementation of a rear-end collision avoidance system based on hierarchical control framework which consists of threat assessment layer, wheel slip ratio control layer and integrated-electro-hydraulic brake (IEHB) actuator control layer.

Vehicle automation is a fundamental approach to reduce traffic accidents and driver workload. However, there is a notable risk of pushing human drivers out of the control loop before automation technology fully matures. Cooperative driving (or vehicle co-piloting) is a novel paradigm which is defined as the vehicle being jointly navigated by a human driver and an automatic controller through shared control technology. Indirect shared control is an emerging shared control method, which is able to realize cooperative driving through input complementation instead of haptic guidance. In this paper we first establish an indirect shared control method, in which the driver’s commanded input and the controller’s desired input are balanced with a weighted summation. Thereafter, we propose a predictive model to capture driver adaptation and trust in indirect shared control.

Occupant restraint systems are developed based on some baseline experiments. While these experiments can only represent small part of various accident modes, the current procedure for utilizing the restraint systems may not provide the optimum protection in the majority of accident modes. This study presents an approach to predict occupant injury responses before the collision happens, so that the occupant restraint system, equipped with a motorized pretensioner, can be adjusted to the optimal parameters aiming at the imminent vehicle-to-vehicle frontal crash. The approach in this study takes advantage of the information from pre-crash systems, such as the time to collision, the relative velocity, the frontal overlap, the size of the vehicle in the front and so on. In this paper, the vehicle containing these pre-crash features will be referred to as ego vehicle. The information acquired and the basic crash test results can be integrated to predict a simplified crash pulse.

As the restraint technologies for front-seat occupant protection advance, such as seatbelt pre-tensioner, seatbelt load limiter and airbag, relative effectiveness of rear-seat occupant protection decreases, especially for the elderly. Some occupant protection systems for front-seat have been proved to be effective for rear-seat occupant protection as well, but they also have some drawbacks. Seatbelt could generate unwanted local penetrations to the chest and abdomen. And for rear-seat occupants, it might be difficult to install airbag and set deployment time. For crash protection, it is desirable that the restraint loads are spread to the sturdy parts of human body such as head, shoulders, rib cage, pelvis and femurs, as uniformly as possible. This paper explores a uniform restraint concept aiming at providing protection in wide range of impact severity for rear-seat occupants.

The coordinated control of stability and steering systems in collision avoidance steering evasion has been widely studied in vehicle active safety area, but the studies are mainly aimed at autonomous vehicle without driver or conventional combustion engine vehicle. This paper focuses on the control of hybrid vehicle integrated with rear hub in emergency steering evasion situation, and considering the driver’s characteristics. First, the mathematics model of vehicle dynamics and driver has been given. Second, based on the planned steering evasion path, the model predictive control method is presented for achieving higher evasion path tracking accuracy under driver’s steering input. The prediction model includes an adaptive preview distance driver model and a vehicle dynamics model to predict the driver input and the vehicle trajectory.

Accurate identification of driver’s braking intention is essential in advanced driver assistance system and can make the driving process more comfortable and trustworthy. In this paper, a novel method for driver braking intention identification in cut-in scenarios was proposed by using driver’s gaze information and motion information of cut-in vehicles. Firstly, a "looking in and looking out" experimental platform including three eye-tracking cameras and one front-view camera was built to collect driver's gaze information and the vehicle motion information. Secondly, driver’s gaze features and motion features of cut-in vehicles were selected and the braking intention identification performance of several decision tree-based ensemble learning algorithms was compared. Thirdly, the feature importance was analyzed by using SHAP (SHapley Additive exPlanations) values. This novel method of braking intention identification makes full use of in-vehicle camera sensors.

An autonomous emergency braking (AEB) system can detect emergency conditions using sensors (e.g., radar and camera) to automatically activate the braking actuator without driver input. However, during the hard braking phase, crash conditions for the restraint system can easily change (e.g., vehicle velocity and occupant position), causing an out-of-position (OOP) phenomenon, especially for unbelted occupants entering the airbag deployment range, which may lead to more severe injuries than in a normal position. A critical step in reducing the injury of unbelted occupants would be to design an AEB system while considering the effect of deployed airbags on the occupants. Thus far, few studies have paid attention to the compatibility between AEB and airbag systems for unbelted occupants. This study aims to provide a method that combines AEB and airbag systems to explore the potential injury reduction capabilities for unbelted occupants.

Safety of buses is crucial because of the large proportion of the public transportation sector they constitute. To improve bus safety levels, especially to avoid driver error, which is a key factor in traffic accidents, we designed and implemented an intelligent bus called iBus. A robust system architecture is crucial to iBus. Thus, in this paper, a novel self-driving system architecture with improved robustness, such as to failure of hardware (including sensors and controllers), is proposed. Unlike other self-driving vehicles that operate either in manual driving mode or in self-driving mode, iBus offers a dual-control mode. More specifically, an online hot standby mechanism is incorporated to enhance the reliability of the control system, and a software monitor is implemented to ensure that all software modules function appropriately. The results of real-world road tests conducted to validate the feasibility of the overall system confirm that iBus is reliable and robust.

Seatbelt and airbags provide effective occupant restraint, but are also potential to induce intrusive deformation and submarining injuries in motor vehicle crashes. To address these issues, this study puts forward a new restraint concept that applies restraint loads on shoulders and knees/femurs, i.e., the sturdiest regions of human body, via a combined use of shoulder bolster and knee bolster based on biomechanical computational analysis. The load characteristics of the two bolsters were optimized to obtain protection effectiveness superior to conventional use of seatbelt and airbag. Occupant kinematics and kinetics were taken into account, including the excursions of head, shoulders and knees, the accelerations of head and chest, and the compressions of thorax on several locations on the ribcage. The injury risk of rib fractures was monitored based on the strain levels of ribcage.