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Technical Paper

A Braking Force Distribution Strategy in Integrated Braking System Based on Wear Control and Hitch Force Control

2018-04-03
2018-01-0827
A braking force distribution strategy in integrated braking system composed of the main braking system and the auxiliary braking system based on braking pad wear control and hitch force control under non-emergency braking condition is proposed based on the Electronically Controlled Braking System (EBS) to reduce the difference in braking pad wear between different axles and to decrease hitch force between tractors and trailers. The proposed strategy distributes the braking force based on the desired braking intensity, the degree of the braking pad wear and the limits of certain braking regulations to solve the coupling problems between braking safety, economical efficiency of braking and the comfort of drivers. Computer co-simulations of the proposed strategy are performed.
Technical Paper

A Driving Simulator Study of Young Driver’s Behavior under Angry Emotion

2019-04-02
2019-01-0398
The driving behaviors of young drivers under the influence of anger are analyzed by driving simulator in this paper. A total of 12 subjects are enrolled during the experiment. Standardized videos are utilized to induce the driver's anger emotion. And the driver's electrocardiogram (ECG) signal is collected synchronously and compared before and after emotional trigger, which prove the validity of emotional trigger. Based on the result, the driver's driving performance under the straight road and the curve under normal state and angry state are compared and analyzed. The results of independent sample t-test show that there are significant differences in the running time of straight sections and the standard deviation of steering wheel angle in curves between normal and angry states. In conclusion, the longitudinal and lateral operation of drivers is unstable in angry state and the driver will be more destructive to the regular driving behavior.
Technical Paper

A Fuzzy On-Line Self-Tuning Control Algorithm for Vehicle Adaptive Cruise Control System with the Simulation of Driver Behavior

2009-04-20
2009-01-1481
Research of Adaptive Cruise Control (ACC) is an important issue of intelligent vehicle (IV). As we all known, a real and experienced driver can control vehicle's speed very well under every traffic environment of ACC working. So a direct and feasible way for establishing ACC controller is to build a human-like longitudinal control algorithm with the simulation of driver behavior of speed control. In this paper, a novel fuzzy self-tuning control algorithm of ACC is established and this controller's parameters can be tuned on-line based on the evaluation indexes that can describe how the driver consider the quality of dynamical characteristic of vehicle longitudinal dynamics. With the advantage of the controller's parameter on-line self-tuning, the computational workload from matching design of ACC controller is also efficiently reduced.
Journal Article

A Lane-Changing Decision-Making Method for Intelligent Vehicle Based on Acceleration Field

2018-04-03
2018-01-0599
Taking full advantage of available traffic environment information, making control decisions, and then planning trajectory systematically under structured roads conditions is a critical part of intelligent vehicle. In this article, a lane-changing decision-making method for intelligent vehicle is proposed based on acceleration field. Firstly, an acceleration field related to relative velocity and relative distance was built based on the analysis of braking process, and acceleration was taken as an indicator of safety evaluation. Then, a lane-changing decision method was set up with acceleration field while considering driver’s habits, traffic efficiency and safety. Furthermore, velocity regulation was also introduced in the lane-changing decision method to make it more flexible.
Technical Paper

A Model-Based Mass Estimation and Optimal Braking Force Distribution Algorithm of Tractor and Semi-Trailer Combination

2013-04-08
2013-01-0418
Taking a good longitudinal braking performance on flat and level road of tractor and semi-trailer combination as a target, in order to achieve an ideal braking force distribution among axles, while the vehicle deceleration is just depend on the driver's intention, not affected by the variation of semi-trailer mass, the paper proposes a model based vehicle mass identification and braking force distribution strategy. The strategy identifies the driver's braking intention via braking pedal, estimates semi-trailer's mass during the building process of braking pressure in brake chamber, distributes braking force among axles by using the estimated mass. And a double closed-loop regulation of the vehicle deceleration and utilization adhesion coefficient of each axle is presented, in order to eliminate the bad effect of mass estimation error, and enhance the robustness of the whole algorithm. A simulation is conducted by utilizing MATLAB/Simulink and TruckSim.
Technical Paper

A Multi-mode Control Strategy for EV Based on Typical Situation

2017-03-28
2017-01-0438
A multitude of recent studies are suggestive of the EV as a paramount representative of the NEV, its development direction is transformed from “individuals adapt to vehicles” to “vehicles serve for occupants”. The multi-mode drive control technology is relatively mature in traditional auto control sphere, however, a host of EV continues to use a single control strategy, which lacks of flexibility and diversity, little if nothing interprets the vehicle performances. Furthermore, due to the complex road environment and peculiarity of vehicle occupants that different requirement has been made for vehicle performance. To solve above problems, this paper uses the key technology of mathematical statistics process in MATLAB, such as the mean, linear fitting and discrete algorithms to clean up, screening and classification the original data in general rules, and based on short trips in the segments of kinematics analysis method to establish a representative of quintessential driving cycle.
Technical Paper

An Integrated Method for Evaluation of Seat Comfort Based on Virtual Simulation of the Interface Pressures of Driver with Different Body Sizes

2017-03-28
2017-01-0406
This paper presents an integrated method for rapid modeling, simulation and virtual evaluation of the interface pressure between driver human body and seat. For simulation of the body-seat interaction and for calculation of the interface pressure, besides body dimensions and material characteristics an important aspect is the posture and position of the driver body with respect to seat. In addition, to ensure accommodation of the results to the target population usually several individuals are simulated, whose body anthropometries cover the scope of the whole population. The multivariate distribution of the body anthropometry and the sampling techniques are usually adopted to generate the individuals and to predict the detailed body dimensions. In biomechanical modeling of human body and seat, the correct element type, the rational settings of the contacts between different parts, the correct exertion of the loads to the calculation field, etc., are also crucial.
Technical Paper

Assessment Approaches of Automobile Frontal Crash Pulse

2018-07-09
2018-01-5024
This article presents three assessment approaches of automobile frontal crash pulse by using data from the National Highway Traffic Safety Administration (NHTSA) database (56 km/h frontal crash tests). A direct relationship between structural characteristics and automobile safety is established in the study. In the first approach, the crash pulse criterion is improved in the form of a spider diagram based on the star rating. In the second approach, the crash pulse comprehensive evaluation index (PI) is built by weighting function and correlation analysis between pulse parameters and occupant injury risk indexes. In the final approach, a prediction model for major occupant injury risks and indexes which can be regard as an additional evaluation method of crash pulse quality is built by the multiple linear regression method.
Technical Paper

Design and Control of Torque Feedback Device for Driving Simulator Based on MR Fluid and Coil Spring Structure

2018-04-03
2018-01-0689
Since steering wheel torque feedback is one of the crucial factors for drivers to gain road feel and ensure driving safety, it is especially important to simulate the steering torque feedback for a driving simulator. At present, steering wheel feedback torque is mainly simulated by an electric motor with gear transmission. The torque response is typically slow, which can result in drivers’ discomfort and poor driving maneuverability. This paper presents a novel torque feedback device with magnetorheological (MR) fluid and coil spring. A phase separation control method is also proposed to control its feedback torque, including spring and damping torques respectively. The spring torque is generated by coil spring, the angle of coil spring can be adjusted by controlling a brushless DC motor. The damping torque is generated by MR fluid, the damping coefficient of MR fluid can be adjusted by controlling the current of excitation coil.
Technical Paper

Developmental Driver Model for Long Vehicles Based on Preview-Follower Theory

2018-08-07
2018-01-1629
A long vehicle is more difficult to drive than a short one, but the mechanism of this phenomenon is still ambiguous. This paper will devote main effort to elaborate this phenomenon based on the theory of preview-follower driver model. Drivers always hope that the vehicle center can travel according to a predetermined trajectory. However, there is often a deviation between the vehicle center predicted by the driver and the actual center. As for this phenomenon, a conception of driver preview eccentricity is proposed. In order to analyze the influence of the proposed conception on vehicle driving track, a multi-axle steering vehicle model is built and some basic expressions of important parameters are deduced from this model firstly. Then, the developmental driver model with the factor of preview eccentricity based on preview-follower theory is established in the state of low velocity quasi-static. Subsequently, this model for long vehicles is extended to a dynamic driver model.
Technical Paper

Driver Behavior Characteristics Identification Strategy for Adaptive Cruise Control System with Lane Change Assistance

2017-03-28
2017-01-0432
Adaptive cruise control system with lane change assistance (LCACC) is a novel advanced driver assistance system (ADAS), which enables dual-target tracking, safe lane change, and longitudinal ride comfort. To design the personalized LCACC system, one of the most important prerequisites is to identify the driver’s individualities. This paper presents a real-time driver behavior characteristics identification strategy for LCACC system. Firstly, a driver behavior data acquisition system was established based on the driver-in-the-loop simulator, and the behavior data of different types of drivers were collected under the typical test condition. Then, the driver behavior characteristics factor Ks we proposed, which combined the longitudinal and lateral control behaviors, was used to identify the driver behavior characteristics. And an individual safe inter-vehicle distances field (ISIDF) was established according to the identification results.
Technical Paper

Driving Behavior Prediction at Roundabouts Based on Integrated Simulation Platform

2018-04-03
2018-01-0033
Due to growing interest in automated driving, the need for better understanding of human driving behavior in uncertain environment, such as driving behavior at un-signalized crossroad and roundabout, has further increased. Driving behavior at roundabout is greatly influenced by different dynamic factors such as speed, distance and circulating flow of the potentially conflicting vehicles, and drivers should choose whether to leave or wait at the upcoming exit according to these factors. In this paper, the influential dynamic factors and driving behavior characteristics at the roundabout is analyzed in detail, random forest method is then deployed to predict the driving behavior. For training the driving behavior model, four typical roundabout layouts were created under a real-time driving simulator with PanoSim-RT and dSPACE. Traffic participants with different motion style were also set in the simulation platform to mimic real driving conditions.
Technical Paper

Emergency Steering Evasion Torque Assistance Based on Optimized Trajectory

2019-04-02
2019-01-0888
When automobile is at the threat of collisions, steering usually needs a shorter longitudinal distance than braking to avoid collision, especially at a high speed. In emergency steering evasion, the vehicle may be out of the road or colliding with obstacles ahead when the driver’s steering torque is excessive or insufficient. In view of the above problems, this paper presents an emergency steering evasion torque assistance system based on optimized trajectory. First, a feasible steering evasion area is established which treats the paths of excessive and insufficient steering as boundary conditions in this paper. An optimized trajectory is derived from the lateral acceleration of the vehicle and the time to the adjacent lane as optimization conditions. Second, a two degree of freedom vehicle model is used to represent dynamics of the vehicle.
Technical Paper

Identification of Driver Individualities Using Random Forest Model

2017-09-23
2017-01-1981
Driver individualities is crucial for the development of the Advanced Driver Assistant System (ADAS). Due to the mechanism that specific driving operation action of individual driver under typical conditions is convergent and differentiated, a novel driver individualities recognition method is constructed in this paper using random forest model. A driver behavior data acquisition system was built using dSPACE real-time simulation platform. Based on that, the driving data of the tested drivers were collected in real time. Then, we extracted main driving data by principal component analysis method. The fuzzy clustering analysis was carried out on the main driving data, and the fuzzy matrix was constructed according to the intrinsic attribute of the driving data. The drivers’ driving data were divided into multiple clusters.
Technical Paper

Multi-Objective Optimization of Interior Noise of an Automotive Body Based on Different Surrogate Models and NSGA-II

2018-04-03
2018-01-0146
This paper studies a multi-objective optimization design of interior noise for an automotive body. An acoustic-structure coupled model with materials and properties was established to predict the interior noise based on a passenger car. Moreover, three kinds of approximation models related damping thickness and the root mean square of the driver’s ear sound pressure level were established through Latin hypercube method and the corresponding experiments. The prediction accuracy was analyzed and compared for the approximate response surface model, Kriging model and Radial Basis Function neural network model. On this basis, multi-objective optimization of the vehicle interior noise was conducted by using NSGA-II. According to the optimization results, the damping composite structure was applied on the car body structure. Then, the comparison of sound pressure level response at driver’s ear location before and after optimization was performed at speed of 60 km/h on a smooth road.
Technical Paper

Personalized Adaptive Cruise Control Considering Drivers’ Characteristics

2018-04-03
2018-01-0591
In order to improve drivers’ acceptance to advanced driver assistance systems (ADAS) with better adaptation, drivers’ driving behavior should play key role in the design of control strategy. Adaptive cruise control systems (ACC) have many factors that can be influenced by different driving behavior. It is important to recognize drivers’ driving behavior and take human-like parameters to the adaptive cruise control systems to assist different drivers effectively via their driving characteristics. The paper proposed a method to recognize drivers’ behavior and intention based on Gaussian Mixture Model. By means of a fuzzy PID control method, a personalized ACC control strategy was designed for different kinds of drivers to improve the adaptabilities of the systems. Several typical testing scenarios of longitudinal case were created with a host vehicle and a traffic vehicle.
Technical Paper

Research on Steering Performance of Steer-By- Wire Vehicle

2018-04-03
2018-01-0823
With the popularity of electrification and driver assistance systems on vehicle dynamics and controls, the steering performance of the vehicle put forward higher requirements. Thus, the steer-by-wire technology is becoming particularly important. Through specific control algorithm, the steer-by-wire system electronic control unit can receive signals from other sensors on the vehicle, realize the personalized vehicle dynamics control on the basis of understanding the driver’s intention, and grasp the vehicle movement state. At the same time, to make these driver assistance systems better cooperate with human drivers, reduce system frequent false warning, full consideration of mutual adaptation for the systems and the driver’s characteristics is critical. This paper focuses on the steering performance of steer-by-wire vehicle. Feature parameters are obtained from the virtual turning experiment designed on the driving simulator experimental platform.
Technical Paper

Research on the Classification and Identification for Personalized Driving Styles

2018-04-03
2018-01-1096
Most of the Advanced Driver Assistance System (ADAS) applications are aiming at improving both driving safety and comfort. Understanding human drivers' driving styles that make the systems more human-like or personalized for ADAS is the key to improve the system performance, in particular, the acceptance and adaption of ADAS to human drivers. The research presented in this paper focuses on the classification and identification for personalized driving styles. To motivate and reflect the information of different driving styles at the most extent, two sets, which consist of six kinds of stimuli with stochastic disturbance for the leading vehicles are created on a real-time Driver-In-the-Loop Intelligent Simulation Platform (DILISP) with PanoSim-RT®, dSPACE® and DEWETRON® and field test with both RT3000 family and RT-Range respectively.
Technical Paper

Simulation of Straight-Line Type Assist Characteristic of Electric Power-Assisted Steering

2004-03-08
2004-01-1107
Electric Power-Assisted Steering (EPAS) is a new power steering technology that will define the future of vehicle steering. The assist of EPAS is the function of the steering wheel torque and vehicle velocity. The assist characteristic of EPAS is set by control software, which is one of the key issues of EPAS. The straight-line type assist characteristic has been used in some current EPAS products, but its influence on the steering maneuverability and road feel hasn't been explicitly studied in theory. In this paper, the straight-line type assist characteristic is analyzed theoretically. Then a whole vehicle dynamic model used to study the straight-line type assist characteristic is built with ADAMS/Car and validated with DCF (Driver Control Files) mode of ADAMS/Car. Based on the whole vehicle dynamic model, the straight-line type assist characteristic's influence on the steering maneuverability and road feel is investigated.
Technical Paper

Studies on Drivers’ Driving Styles Based on Inverse Reinforcement Learning

2018-04-03
2018-01-0612
Although advanced driver assistance systems (ADAS) have been widely introduced in automotive industry to enhance driving safety and comfort, and to reduce drivers’ driving burden, they do not in general reflect different drivers’ driving styles or customized with individual personalities. This can be important to comfort and enjoyable driving experience, and to improved market acceptance. However, it is challenging to understand and further identify drivers’ driving styles due to large number and great variations of driving population. Previous research has mainly adopted physical approaches in modeling drivers’ driving behavior, which however are often very much limited, if not impossible, in capturing human drivers’ driving characteristics. This paper proposes a reinforcement learning based approach, in which the driving styles are formulated through drivers’ learning processes from interaction with surrounding environment.
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