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Technical Paper

Interactive Modes F-ANP Evaluation for In-Vehicle Secondary Tasks

2016-09-14
2016-01-1890
With the development of automotive HMI and mobile internet, many interactive modes are available for drivers to fulfill the in-vehicle secondary tasks, e.g. dialing, volume adjustment, music playing. For driving safety and drivers’ high expectation for HMI, it is urgent to effectively evaluate interactive mode with good efficiency, safety and good user experience for each secondary tasks, e.g. steering wheel buttons, voice control. This study uses a static driving simulation cockpit to provide driving environment, and sets up a high-fidelity driving cockpit based on OKTAL SacnerStudio and three-dimensional modeling technology. The secondary tasks supported by HMI platform are designed by customer demands research. The secondary task test is carried out based on usability test theory, and the influence on driving safety by different interactive modes is analyzed.
Technical Paper

A Usability Study on In-Vehicle Gesture Control

2016-09-14
2016-01-1870
Gesture control has been increasingly applied to automotive industry to reduce the distraction caused by in-vehicle interactions to the primary task of driving. The aim of this study is to find out if gestures can reasonably be used to control in-car devices. Since there exists a big cultural difference of gesture between different countries because of its particularity, a set of gestures which support intuitive human-machine interaction in an automotive environment is searched. The results show a gesture dictionary for a variety of on-board functions, which conforms to Chinese drivers’ driving habits. Furthermore, this paper also describes a driving simulator test to evaluate the usability of gesture from different aspects including the effectiveness, efficiency, satisfaction, memorability and security. Static driving simulator is considered as an excellent environment for the in-car secondary task as its high safety level, repeatability and reliability.
Technical Paper

Analysis of Driver Emergency Steering Behavior Based on the China Naturalistic Driving Data

2016-09-14
2016-01-1874
Based on the emergency lane change cases extracted from the China naturalistic driving data, the driving steering behavior divides into three phases: collision avoidance, lateral movement and steering stabilization. Using the steering primitive fitting by Gaussian function, the distribution of the duration time, the relationship between steering wheel rate and deflection were analyzed in three phases. It is shown that the steering behavior essentially is composed of steering primitives during the emergency lane-change. However, the combination of the steering primitives is different according to the specific steering constraints in three phases. In the collision avoidance phase, a single steering primitive with high peak is used for the fast steering; in the lateral movement and stabilization phase, a combination of two or even more steering primitives is built to a more accurate steering.
Technical Paper

In-Vehicle Driving Posture Reconstruction from 3D Scanning Data Using a 3D Digital Human Modeling Tool

2016-04-05
2016-01-1357
Driving posture study is essential for the evaluation of the occupant packaging. This paper presents a method of reconstructing driver’s postures in a real vehicle using a 3D laser scanner and Human Builder (HB), the digital human modeling tool under CATIA. The scanning data was at first converted into the format readable by CATIA, and then a personalized HB manikin was generated mainly using stature, sitting height and weight. Its pelvis position and joint angles were manually adjusted so as to match the manikin with the scan envelop. If needed, a fine adjustment of some anthropometric dimensions was also preceded. Finally the personalized manikin was put in the vehicle coordinate system, and joint angels and joint positions were extracted for further analysis.
Journal Article

Active Noise Equalization of Vehicle Low Frequency Interior Distraction Level and its Optimization

2016-04-05
2016-01-1303
On the study of reducing the disturbance on driver’s attention induced by low frequency vehicle interior stationary noise, a subjective evaluation is firstly carried out by means of rank rating method which introduces Distraction Level (DL) as evaluation index. A visual-finger response test is developed to help evaluating members better recognize the Distraction Level during the evaluation. A non-linear back propagation artificial neural network (BPANN) is then modeled for the prediction of subjective Distraction Level, in which linear sound pressure RMS amplitudes of five Critical Band Rates (CBRs) from 20 to 500Hz are selected as inputs of the model. These inputs comprise an input vector of BPANN. Furthermore, active noise equalization (ANE) on DL is realized based on Filtered-x Least Mean Square (FxLMS) algorithm that controls the gain coefficients of inputs of trained BPANN.
Technical Paper

Correlation Analysis of Interior and Exterior Wind Noise Sources of a Production Car Using Beamforming Techniques

2017-03-28
2017-01-0449
Beamforming techniques are widely used today in aeroacoustic wind tunnels to identify wind noise sources generated by interaction between incoming flow and the test object. In this study, a planar spiral microphone array with 120 channels was set out-of-flow at 1:1 aeroacoustic wind tunnel of Shanghai Automotive Wind Tunnel Center (SAWTC) to test exterior wind noise sources of a production car. Simultaneously, 2 reference microphones were set in vehicle interior to record potential sound source signal near the left side view mirror triangle and the signal of driver’s ear position synchronously. In addition, a spherical array with 48 channels was set inside the vehicle to identify interior noise sources synchronously as well. With different correlation methods and an advanced algorithm CLEAN-SC, the ranking of contributions of vehicle exterior wind noise sources to interested interior noise locations was accomplished.
Technical Paper

Predicting the Head-Neck Posture and Muscle Force of the Driver Based on the Combination of Biomechanics with Multibody Dynamics

2017-03-28
2017-01-0407
Biomechanics and biodynamics are increasingly focused on the automotive industry to provide comfortable driving environment, reduce driver fatigue, and improve passenger safety. Man-centered conception is a growing emphasis on the open design of automobile. During the long-term driving, occupational drivers are easily exposed to the neck pain, so it is important to reduce the muscle force load and its fatigue, which are not usually considered quantitatively during traditional ergonomics design, so standards related are not well developed to guide the vehicle design; On the other hand, the head-neck models are always built based on the statics theory, these are not sufficient to predict the instantaneous variation of the muscle force. In this paper, a head-neck model with multi DOFs is created based on multibody dynamics. Firstly, a driver-vehicle-road model considering driver multi-rigid body model, vehicle subsystems, and different ranks of pavement is built.
Technical Paper

Parameter Identification of Self-Inductance in Wireless Power Transfer System for Electric Vehicles

2018-04-03
2018-01-0463
For a practical pad design, a magnetic shielding layer is imperative which is made of ferrite, aluminum or some other metallic material. However, once the magnetic shielding layer is added, not only the mutual inductance but also the self-inductance of the coupling coils vary with the lateral misalignment which is inevitable for a human driver. The change of self-inductance will also result in the mistuning problem in the resonant circuit, which can significantly reduce the transmission efficiency of the whole wireless power transfer (WPT) system. This paper proposed a method of parameter identification of self-inductance based on the least square in order to solve the mistuning problem. In order to verify the proposed method, both the simulation model and the experiment set-up are built.
Technical Paper

Critical Driving Scenarios Extraction Optimization Method Based on China-FOT Naturalistic Driving Study Database

2018-08-07
2018-01-1628
Due to the differences in traffic situations and traffic safety laws, standards for extraction of critical driving scenarios (CDSs) vary from different countries and areas around the world. To maintain the characteristic variables under the Chinese typical CDSs, this paper uses the three-layer detection method to extract and detect CDSs in the Natural Driving Data from China-FOT project which executing under the real traffic situation in China. The first layer of detection is mainly based on the feature distributions which deviate from normal driving situations. These distributions associated with speed and longitudinal acceleration/lateral acceleration/yaw rate also quantify the critical levels classification.
Technical Paper

Driver Risk Perception Model under Critical Cut-In Scenarios

2018-08-07
2018-01-1626
In China Cut-in scenarios are quite common on both highway and urban road with heavy traffic. They have a potential risk of rear-end collision. When facing a cutting in vehicle, driver tends to brake in most case to reduce collision risk. The timing and dynamic characteristics of brake maneuver are indicators of driver subjective risk perception. Time to collision (TTC) and Time Headway (THW) demonstrate objective risk. This paper aims at building a model quantitatively revealing the relationship between drivers’ subjective risk perception and objective risk. A total of 66 valid critical Cut-in cases was extracted from China-FOT, which has a travel distance of about 130 thousand miles. It is found that under Cut-in scenarios, driver tended to brake when the cutting in vehicle right crossing line. This time point was defined as initial brake time. Brake strength and brake speed were taken to describe brake maneuver.
Technical Paper

Evaluation and Optimization of Driver Steering Override Strategy for LKAS Based on Driver’s Acceptability

2018-08-07
2018-01-1631
In order to satisfy design requirements of Lane Keeping Assistance System (LKAS), a Driver Steering Override (DSO) strategy is necessary for driver’s interaction with the assistance system. The assistance system can be overridden by the strategy in case of lane change, obstacle avoidance and other emergency situations. However, evaluation and optimization of the DSO strategy for LKAS cannot easily be completed quantitatively considering driver’s acceptability. In this research, firstly subjective and objective evaluation experiment is designed. Secondly, correlations between the subjective and the objective evaluation results are established by using regression analysis. Finally, based on the correlations established previously, the optimal performance of DSO strategy is obtained by setting the desired comprehensive evaluation ratings as the optimized goal.
Technical Paper

Analysis of Human Machine Interaction Program in Lane Keeping Assist System Based on Field Test

2018-08-07
2018-01-1632
Lane-keeping assist system (LKA) alerts the driver or intervenes in the driving when the vehicle deviates from the lane. But its effect is highly dependent on the driver’s acceptance. Distance to Lane Crossing (DTLC) and Time to Lane Crossing (TTLC) are two important factors to consider the danger level of the scenario, which are also two references for drivers to make decisions. At present, most of the functional design standards are based on these values, while they often differ for different vehicle movements. This study uses a driving robot to precisely control the test conditions and performs field tests on two advanced autonomous vehicles in National Intelligent Connected Vehicle (Shanghai) Pilot Zone. The test conditions are extended based on various test standards and the LKA performance of vehicles in the pre-experiment.
Technical Paper

Study on Important Indices Related to Driver Feelings for LKA Intervention Process

2018-08-07
2018-01-1586
Lane Keeping Assistance (LKA) system is a very important part in Advanced Driver Assistance Systems (ADAS). It prevents a vehicle from departing out of the lane by exerting intervention. But an inappropriate performance during LKA intervention makes driver feel uncomfortable. The intervention of LKA can be divided into 3 parts: intervention timing, intervention process and intervention ending. Many researches have studied about the intervention timing and ending, but factors during intervention process also affect driver feelings a lot, such as yaw rate and steering wheel velocity. To increase driver’s acceptance of LKA, objective and subjective tests were designed and conducted to explore important indices which are highly correlated with the driver feelings. Different kinds of LKA controller control intervention process in different ways. Therefore, it’s very important to describe the intervention process uniformly and objectively.
Technical Paper

Emergency Steering Evasion Control by Combining the Yaw Moment with Steering Assistance

2018-04-03
2018-01-0816
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.
Technical Paper

Adaptive Design of Driver Steering Override Characteristics for LKAS

2019-11-04
2019-01-5029
Lane Keeping Assistance System (LKAS) is a typical lateral driver assistance system with low acceptance. One of the main reasons is that fixed parameters cannot satisfy individual differences. So LKAS adaptive to driver characteristics needs to be designed. Driver Steering Override (DSO) process is an important process of LKAS. It happens when contradiction between driver’s intention and system behavior occurs. As feeling of overriding will affect the overall experience of using LKAS, the design of DSO characteristics is worthy of attention. This research provided an adaptive design scheme aiming at DSO characteristics for LKAS by building Driver Preference Model (DPM) based on simulator test data from preliminary experiments. The DPM was to represent the relationship between driver characteristics indices and driver preferred system characteristics indices. So that new drivers’ preference can be predicted by DPM based on their own daily driving data with LKAS switched off.
Technical Paper

Analysis of the Driver’s Breaking Response in the Safety Cut-in Scenario Based on Naturalistic Driving

2019-11-04
2019-01-5052
For the personification of automotive vehicle function performance under common traffic scenarios, analysis of human driver behavior is necessary. Based on China Field Operational Test (China-FOT) database of China Natural Driving Study project, this paper studies the driver's response in the common cut-in scenario. A total of 266 cut-in cases are selected by manual interception of driving recorder video. The relevant traffic environment characteristics are also extracted from video, including light conditions, road conditions, scale and lateral position of cut-in vehicle, etc. Dynamic information is decoded form CAN, such as speed, acceleration and so on. Then image processing results, such as relative speed and distance of cut-in and subject vehicles, are calculated. Statistical results based on above information show the response type and distribution of human driver: the behavior of keeping lane is 96.24%, in which the ratio of braking response is 51.13%.
Technical Paper

Prediction Model of Driving Range of Electric Vehicle Based on Driver’s Driving Behavior

2019-11-04
2019-01-5058
Aiming at the problem of "mileage anxiety" caused by the inaccurate estimation of vehicle owners due to the complicated and changeable actual driving conditions, the current study of electric driving range prediction focuses on exploring the battery parameters or fitting the linear relationship between electric vehicle SOC (state of charge) and driving range under ideal conditions of experiments or software simulation, which ignores the actual vehicle driving conditions and the difference in driving range due to differences in driver's driving behaviors. This paper puts forward an innovative prediction model of the driving mileage of pure electric vehicles based on driver's driving behavior.
Technical Paper

Analysis of the Correlation between Driver's Visual Features and Driver Intention

2019-04-02
2019-01-1229
Driver behaviors provide abundant information and feedback for future Advanced Driver Assistance Systems (ADAS). Driver’s eye and head may present some typical movement patterns before executing driving maneuvers. It is possible to use driver’s head and eye movement information for predicting driver intention. Therefore, to determine the most important features related to driver intention has attracted widespread research interests. In this paper, a method to analyze the correlation between driver’s visual features and driver intention is proposed, aiming to determine the most representative features for driver intention prediction. Firstly, naturalistic driving experiment is conducted to collect driver’s videos during executing lane keeping and lane change maneuvers. Then, driver’s head and face visual features are extracted from those videos. By using boxplot and independent samples T-test, features which have significant correlation with driver intention are found.
Technical Paper

Driver Behavior Classification under Cut-In Scenarios Using Support Vector Machine Based on Naturalistic Driving Data

2019-04-02
2019-01-0136
Cut-in scenario is common in traffic and has potential collision risk. Human driver can detect other vehicle’s cut-in intention and take appropriate maneuvers to reduce collision risk. However, autonomous driving systems don’t have as good performance as human driver. Hence a deeper understanding on driving behavior is necessary. How to make decisions like human driver is an important problem for automated vehicles. In this paper, a method is proposed to classify the dangerous cut-in situations and normal ones. Dangerous cases were extracted automatically from naturalistic driving database using specific detection criteria. Among those cases, 70 valid dangerous cut-in cases were selected manually. The largest deceleration of subject vehicle is over 4 m/s2. Besides, 249 normal cut-in cases were extracted by going through video data of 2000km traveled distance. In normal driving cases, subject vehicle may brake or keep accelerating and the largest deceleration was less than 3 m/s2.
Technical Paper

Naturalistic Driving Behavior Analysis under Typical Normal Cut-In Scenarios

2019-04-02
2019-01-0124
Cut-in scenarios are common and of potential risk in China but Advanced Driver Assistant System (ADAS) doesn’t work well under such scenarios. In order to improve the acceptance of ADAS, its reactions to Cut-in scenarios should meet driver’s driving habits and expectancy. Brake is considered as an express of risk and brake tendency in normal Cut-in situations needs more investigation. Under critical Cut-in scenarios, driver tends to brake hard to eliminate collision risk when cutting in vehicle right crossing lane. However, under less critical Cut-in scenarios, namely normal Cut-in scenarios, driver brakes in some cases and takes no brake maneuver in others. The time when driver initiated to brake was defined as key time. If driver had no brake maneuver, the time when cutting-in vehicle right crossed lane was defined as key time. This paper focuses on driver’s brake tendency at key time under normal Cut-in situations.
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