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This paper proposed a collision avoidance strategy that take over the control of ego vehicle when faced with urgent collision risk. To improve the applicability of collision avoidance strategy in complex scenarios, the theory of ICS (Inevitable Collision State) is introduced to evaluate the collision risk and compute the trigger flag of the system, and vehicle dynamic is taken into account when modeling ego vehicle to predict ego vehicle’s following moving. Vehicle specific characteristics including reaction time of the braking system and the braking force increasing process are taken into account. In order to reduce injury caused by collision accidents and minimize disruption to drivers, slight steering is added on top of emergency braking. The direction of the steering angle is determined according to IM (Imitating Maneuvers) The flow chart of the strategy is presented in the paper.

A feasible method was developed to reconstruct the three-dimensional flame surface of SI combustion based on 2D images. A double-window constant volume vessel was designed to simultaneously obtain the side and bottom images of the flame. The flame front was reconstructed based on 2D images with a slicing model, in which the flame characteristics were derived by slicing flame contour modeling and flame-piston collision area analysis. The flame irregularity and anisotropy were also analyzed. Two different principles were used to build the slicing model, the ellipse hypothesis modeling and deep learning modeling, in which the ellipse hypothesis modeling was applied to reconstruct the flame in the optical SI engine. And the reconstruction results were analyzed and discussed. The reconstruction results show that part of the wrinkled and folded structure of the flame front in SI engines can be revealed based on the bottom view image.

Recent research has shown that butanol, instead of ethanol, has the potential of introducing a more suitable blend in diesel engines. This is because butanol has properties similar to current transportation fuels in comparison to ethanol. However, the main downside is the high cost of the butanol production process. Acetone-butanol-ethanol (ABE) is an intermediate product of the fermentation process of butanol production. By eliminating the separation and purification processes, using ABE directly in diesel blends has the potential of greatly decreasing the overall cost for fuel production. This could lead to a vast commercial use of ABE-diesel blends on the market. Much research has been done in the past five years concerning spray and combustion processes of both neat ABE and ABE-diesel mixtures. Additionally, different compositions of ABE mixtures had been characterized with a similar experimental approach.

Traffic congestions are increasingly severe in urban areas, especially at the merging areas of the ramps and the arterial roads. Because of the complex conflict relationship of the vehicles in ramps and arterial roads in terms of time-spatial constraints, it is challenging to coordinate the motion of these vehicles, which may easily cause congestions at the merging areas. The connected and automated vehicles (CAVs) provides potential opportunities to solve this problem. A centralized merging control method for CAVs is proposed in this paper, which can organize the traffic movements in merging areas efficiently and safely. In this method, the merging control model is built to formulate the vehicle coordination problem in merging areas, which is then transformed to the discrete nonlinear optimization form. A simulation model is built to verify the proposed method.

Lane-changing systems have been developed and applied to improve environmental adaptability of advanced driver assistant system (ADAS) and driver comfort. Lane-changing control consists of three steps: decision making, trajectory planning and trajectory tracking. Current methods are not perfect due to weaknesses such as high computation cost, low robustness to uncertainties, etc. In this paper, a novel lane changing control method is proposed, where lane-changing behavior is analogized to parallel parking behavior. In the perspective of host vehicle with lane-changing intention, the space between vehicles in the target adjacent lane can be regarded as dynamic parking space. A decision making and path planning algorithm of parallel parking is adapted to deal with lane change condition. The adopted algorithm based on rules checks lane-changing feasibility and generates desired path in the moving reference system at the same speed of vehicles in target lane.

In this paper, we focus on the active vehicular suspension controller design. A quarter-vehicle suspension system is employed in the system analysis and synthesis. Due to the difficulty and cost in the measuring of all the states, we only choose two variables to construct the feedback loop, that is, the control law is a static-output-feedback (SOF) control. However, the sensor reduction would induce challenges in the controller design. One of the main challenges is the NP-hard problem in the corresponding SOF controller design. In order to deal with this challenge, we propose a two-stage design method in which a state-feedback controller is firstly designed and then the state-feedback controller is used to decouple the nonlinear conditions. To better compensate for the varying vehicle load, a robust load-dependent control strategy is adopted. The proposed design methodology is applied to a suspension control example.

The issue of car-to-pedestrian impact safety has received more and more attention. For leg protection, a legform impactor with 2 degrees-of-freedom (DOF) proposed by EEVC is required in current regulations for injury assessment, and the Japan Automobile Manufacturers Association Inc. (JAMA) and Japan Automobile Research Institute (JARI) have developed a more biofidelic pedestrian legform since 2000. However, studies show that those existing legforms may not be able to cover some car-to-pedestrian impact situations. This paper documents the development of a new pedestrian legform with 4 DOFs at the knee-joint. It can better represent the kinematics characteristics of human knee-joint, especially under loading conditions in omni-direction impacts. The design challenge is to solve the packaging problem, including design of the knee-joint mechanisms and layout of all the sensors in a limited space of the legform.

The recent proliferation of perception sensing and computing technologies has promoted the rapid development of automated driving. The design of the perception sensing system has nonnegligible influences both on the performances of various automated driving features and on the system costs. This paper proposes an automated driving feature oriented framework for automatic selection and arrangement of the sensors in the perception sensing system. An automated driving feature oriented optimization model is built considering the characteristics and requirements of the specific feature and a genetic algorithm based design method is provided to solve this optimization model. Furthermore, the Adaptive Cruise Control feature and the Automated Parking Assistance feature are selected as the simulation cases to verify the effectiveness of the proposed method.

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.

This article is concerned with identification of true stress-strain curve under biaxial tension of thermoplastic polymers. A new type of biaxial tension attachment was embedded first in a universal material test machine, which is able to transform unidirectional loading of the test machine to biaxial loading on the specimen with constant velocity. Cruciform specimen geometry was optimized via FE modeling. Three methods of calculating true stress in biaxial tension tests were compared, based on incompressibility assumption, linear elastic theory and inverse engineering method, respectively. The inverse engineering method is more appropriate for thermoplastic polymers since it considers the practical volume change of the material during biaxial tension deformation. The strategy of data processing was established to obtain biaxial tension true stress-strain curves of different thermoplastic polymers.

With the rapid advancement in intelligent vehicle technologies, comprehensive environmental perception has become crucial for achieving higher levels of autonomous driving. Among various perception tasks, monitoring road types and evenness is particularly significant. Different road categories imply varied surface adhesion coefficients, and the evenness of the road reflects distinct physical properties of the road surface. This paper introduces a two-stage road perception framework. Initially, the framework undergoes pre-training on a large annotated drivable area dataset, acquiring a set of pre-trained parameters with robust generalization capabilities, thereby endowing the model with the ability to locate road areas in complex regions.

This work presents a multi-objective adaptive cruise control (ACC) system via deep reinforcement learning (DRL). During the control period, it quantitatively considers three indexes: tracking accuracy, riding comfort, and fuel economy. The system balances contradictions between different indexes to achieve the best overall control results. First, a hierarchical control architecture is utilized, where the upper level controller is synthesized under DRL framework to give out the vehicle desired acceleration. The lower level controller executes the command and compensates vehicle dynamics. Then, four state variables that can comprehensively determine the car-following states are selected for better convergence. Multi-objective reward function is quantitatively designed referring to the evaluation indexes, in which safety constraints are considered by adding violation penalty. Thereafter, the training environment which excludes the disturbance of preceding car acceleration is built.

2, 5-Dimethylfuran (DMF) has been receiving increasing interest as a potential alternative fuel to fossil fuels, owing to the recent development of new production technology. However, the influence of DMF properties on the in-cylinder fuel spray and its evaporation, subsequent combustion processes as well as emission formation in current gasoline direct injection (GDI) engines is still not well understood, due to the lack of comprehensive understanding of its physical and chemical characteristics. To better understand the spray characteristics of DMF and its application to the IC engine, the fuel sprays of DMF and gasoline were investigated by experimental and computational methods. The shadowgraph and Phase Doppler Particle Analyzer (PDPA) techniques were used for measuring spray penetration, droplet velocity and size distribution of both fuels.

As the essential of future driver assistance system, brake-by-wire system is capable of performing autonomous intervention to enhance vehicle safety significantly. Regenerative braking is the most effective technology of improving energy consumption of electrified vehicle. A novel brake-by-wire system scheme with integrated functions of active braking and regenerative braking, is proposed in this paper. Four pressure-difference-limit valves are added to conventional four-channel brake structure to fulfill more precise pressure modulation. Four independent isolating valves are adopted to cut off connections between brake pedal and wheel cylinders. Two stroke simulators are equipped to imitate conventional brake pedal feel. The operation principles of newly developed system are analyzed minutely according to different working modes. High fidelity models of subsystems are built in commercial software MATLAB and AMESim respectively.

In order to realize the series-parallel switching control of hybrid electric vehicle (HEV) with dual-motor hybrid configuration, a method of unpowered interrupt switching based on the coordinated control of three power sources was proposed by analyzing the series-parallel driving mode of the dual-motor hybrid configuration. The series to parallel switching process is divided into three stages: speed regulation stage, clutch combination and power source switching. The distribution control of speed regulating torque is carried out in the speed regulating stage. The speed adjustment torque is preferentially allocated to the power source of the input shaft (engine and P1) to carry out the lifting torque. Due to the high speed adjustment accuracy and fast response of the P1 motor, the input shaft is preferentially allocated to P1 for speed adjustment, that is, the torque intervention of P1.

The strategy for emission reduction in the P2.5 hybrid system involves the optimization of engine torque, engine speed, catalyst heat duration, and motor torque regulation in a coordinated manner. In addition to employing traditional engine control methods used in HEV models, unique approaches can be utilized to effectively manage emissions. The primary principle is to ensure that the engine operates predominantly under steady-state conditions or limits its load to regulate emissions levels. The main contributions of this paper are as follows: The first is the optimization of catalyst heating stage. During the catalyst heating stage, the system divides it into one or two stages. In the first stage, the vehicle is driven by the motor while keeping the engine idle. This approach stabilizes catalyst heating and prevents fluctuations in air-fuel ratio caused by speed and load changes that could potentially worsen emissions performance.

Special purpose flat-bed vehicle is commonly utilized to move heavily items such as containers in warehouse, port and other freight handling scene, the hydraulic steering system have be gradually replaced by electric ones. However, the cost of electric steering system is high for commercial activities. Thus, for some corporates, the differential braking steering strategy becomes an ideal alternative. The purpose of this paper is to present a steering control method for flat-bed electric vehicle based on differential braking system. There are two main components of the control method, steering while moving forward and pivot steering, and each of them was composed by upper layer and executive layer. To evaluate the practicability of the control methods, a 7-DOF flat-bed vehicle model was established in Simulink.

Based on the third generation of hydraulic engine mounts (HEMs), which has three types of hydraulic mechanisms such as inertia track, decoupler and disturbing plate, the influences of the three different hydraulic mechanisms on the dynamic properties were studied experimentally. The working principles of the three hydraulic mechanisms and the relationship between the dynamic properties of the three generations of HEMs were revealed clearly, these experimental results will be helpful for HEM design selection. It was discovered experimentally that the frequency-dependent dynamic properties of HEM with inertia track or orifice have fixed points under different excitation displacement amplitudes. Based on the facts that the analytical results matched well with the experimental ones, a new parameter-identification-method for HEM is presented, which is clear in theory and is time- and cost-saving, the identified results were reliable.

During the engaging process of sleeve and teeth ring in mechanical transmissions, their rotational speed and position differences cause multiple engaging ways and trajectories, and casual impacts between them will delay the engaging process and cause a long power off time for a gear shift. In order to reveal the engaging mechanism of the sleeve and the teeth ring, it is essential to build a high-fidelity model to cover all of their engaging ways and capture their speed changes for an impact. In this work, our contribution is that their impact process is modeled as a precise, continuous and nonlinear damping model, and then a hybrid automaton model is built to connect the system dynamics in different mechanical coupling relationships.