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Viewing 271 to 300 of 85301
2017-09-23
Journal Article
2017-01-1966
Min Ke, Bing Zhu, Jian Zhao, Weiwen Deng
Abstract Knowledge of intelligent vehicle absolute position is a vital premise for the implementation of decision programming, kinematic and dynamics control. In order to achieve high accuracy positioning and reduce running cost as much as possible under all operating conditions, this paper proposed an integrated positioning method based on GPS and Ultra Wide Band(UWB) for intelligent vehicle’s navigation and position system. In this method, GPS and UWB are alternately active according to the confidence level of GPS signal. When the vehicle is traveling in a wide-open area and GPS signal is well received, the positioning results of Dead Reckoning system are corrected by the low frequency positioning output from GPS. During the correcting process, in order to realize the better fusion of measurement data, a simplified federal Kalman filter was designed by using indirect method.
2017-09-23
Technical Paper
2017-01-1971
Sihan Chen, Libo Huang, Xin Bi, Jie Bai
Abstract For sensing system, the trustworthiness of the variant sensors is the crucial point when dealing with advanced driving assistant system application. In this paper, an approach to a hybrid camera-radar application of vehicle tracking is presented, able to meet the requirement of such demand. Most of the time, different types of commercial sensors available nowadays specialize in different situations, such as the ability of offering a wealth of detailed information about the scene for the camera or the powerful resistance to the severe weather for the millimeter-wave (MMW) radar. The detection and tracking in different sensors are usually independent. Thus, the work here that combines the variant information provided by different sensors is indispensable and worthwhile. For the real-time requirement of merging the measurement of automotive MMW radar in high speed, this paper first proposes a fast vehicle tracking algorithm based on image perceptual hash encoding.
2017-09-23
Technical Paper
2017-01-1967
Wei Liu, Huan Tian, Jun Hu, Shuai Cheng, Huai Yuan
Abstract Image segmentation is critical in autonomous driving field. It can reveal essential clues such as objects’ shape or boundary information. The information, moreover, can be leveraged as input information of other tasks: vehicle detection, for example, or vehicle trajectory prediction. SegNet, one deep learning based segmentation model proposed by Cambridge, has been a public baseline for scene perception tasks. It, however, suffers an accuracy deficiency in objects marginal area. Segmentation of this area is very challenging with current models. To alleviate the problem, in this paper, we propose one edge enhanced deep learning based model. Specifically, we first introduced one simple, yet effective Artificial Interfering Mechanism (AIM) which feeds segmentation model manual extracted key features. We argue this mechanism possesses the ability to enhance essential features extraction and hence, ameliorate the model performance.
2017-09-23
Technical Paper
2017-01-1974
Tao Chen, Jie Bai, Fang Wang, Libo Huang
Abstract In the last years, in order to fit the requirements of automotive radar application under the multi-target conditions, several proposals about Continuous Waveform (CW)have been developed. The transmit signal with Multiple Frequency Shift Keying (MFSK) technology was developed to analyze the target information in range domain and Doppler frequency domain simultaneously, but the MFSK waveform has lower estimation accuracy in phase measuring. A higher accuracy signal type is the chirp sequence waveform of monopulse radar, which is based on two-dimension independent frequency measuring. It can also get the range and velocity information, but might lead to ambiguities in Doppler domain. To avoid the Doppler ambiguity, a method is proposed in this paper, which uses the modified chirp sequence waveform. The carrier frequencies of the modified chirp sequence are different, which causes the Doppler frequency offset.
2017-09-23
Journal Article
2017-01-1972
Sen Li, Xin Bi, Libo Huang, Bin Tan
Abstract In Advanced Driver Assistant System (ADAS), the automotive radar is used to detect targets or obstacles around the vehicle. The procedure of Constant False Alarm Rate (CFAR) plays an important role in adaptive targets detection in noise or clutter environment. But in practical applications, the noise or clutter power is absolutely unknown and varies over the change of range, time and angle. The well-known cell averaging (CA) CFAR detector has a good detection performance in homogeneous environment but suffers from masking effect in multi-target environment. The ordered statistic (OS) CFAR is more robust in multi-target environment but needs a high computation power. Therefore, in this paper, a new two-dimension CFAR procedure based on a combination of Generalized Order Statistic (GOS) and CA CFAR named GOS-CA CFAR is proposed. Besides, the Linear Frequency Modulation Continuous Wave (LFMCW) radar simulation system is built to produce a series of rapid chirp signals.
2017-09-23
Technical Paper
2017-01-1975
Wenhui Li, Wenlan Li, Jialun Liu, Yuhao Chen
Abstract Vehicle detection has been a fundamental problem in the research of Intelligent Traffic System (ITS), especially in urban driving environment. Over the past decades, vision-based vehicle detection has got a considerable attention. In addition to the rich appearance information, the stereo vision method also provides depth information, which could achieve higher accuracy and precision. In this paper, a hybrid method for stereo vision-based real-time vehicle detection in urban environment is proposed. Firstly, we extract vehicle features and generate the Region of Interest (ROI). Semi-global Matching (SGM) algorithm is then utilized on the ROIs to generate disparity maps and get the depth information, which could be used to compute the width of each ROI. The noise regions, always with obvious depth variation in the disparity maps are excluded by the clustering approach.
2017-09-23
Technical Paper
2017-01-1973
Yang Yin, Xin Bi, Libo Huang, Shitao Yan
Abstract Millimeter wave (MMW) automotive radar plays an important role in the advanced driving assistance system (ADAS), which detects vehicles, pedestrians and other obstacles. In the adaptive cruise control (ACC) and the automatic emergency brake (AEB) system, the target needs to be oriented. One of the automotive radar’s task is to get the direction information which includes the range, speed, azimuth and height of the target by high intermediate frequency (IF) signal sampling rate. In order to solve the problem of high sampling rate for the MMW radar caused by the traditional Nyquist sampling theorem when the target is located, a new method based on the compressed sensing (CS) for the target location is proposed in this paper. This paper presents the linear frequency modulated continuous wave (LFMCW) model and simulates the sampling and reconstruction of the radar’s IF signal via CS technique by using MATLAB.
2017-09-23
Technical Paper
2017-01-1982
Xiaoming Lan, Hui Chen, Xiaolin He, Jiachen Chen, Yosuke Nishimura, Kazuya Ando, Kei Kitahara
Abstract In the recent years, the interaction between human driver and Advanced Driver Assistance System (ADAS) has gradually aroused people’s concern. As a result, the concept of personalized ADAS is being put forward. As an important system of ADAS, Lane Keeping Assistance System (LKAS) also attracts great attention. To achieve personalized LKAS, driver lane keeping characteristic (DLKC) indices which could distinguish different driver lane keeping behavior should be researched. However, there are few researches on DLKC indices for personalized LKAS. Although there are many researches on modeling driver steering behavior, these researches are not sufficient to obtain DLKC indices. One reason is that most of researches are for double lane change behavior which is different from driver lane keeping behavior.
2017-09-23
Technical Paper
2017-01-1978
Yuxiang Feng, Simon Pickering, Edward Chappell, Pejman iravani PhD, Chris Brace
Abstract The major contribution of this paper is to propose a low-cost accurate distance estimation approach. It can potentially be used in driver modelling, accident avoidance and autonomous driving. Based on MATLAB and Python, sensory data from a Continental radar and a monocular dashcam were fused using a Kalman filter. Both sensors were mounted on a Volkswagen Sharan, performing repeated driving on a same route. The established system consists of three components, radar data processing, camera data processing and data fusion using Kalman filter. For radar data processing, raw radar measurements were directly collected from a data logger and analyzed using a Python program. Valid data were extracted and time stamped for further use. Meanwhile, a Nextbase monocular dashcam was used to record corresponding traffic scenarios. In order to measure headway distance from these videos, object depicting the leading vehicle was first located in each frame.
2017-09-23
Technical Paper
2017-01-1981
Bing Zhu, Weinan Li, Ning Bian, Jian Zhao, Weiwen Deng
Abstract 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.
2017-09-23
Technical Paper
2017-01-1977
Xin Bi, Bin Tan, Zhijun Xu, Libo Huang
Abstract Vehicle and pedestrian detection technology is the most important part of advanced driving assistance system (ADAS) and automatic driving. The fusion of millimeter wave radar and camera is an important trend to enhance the environmental perception performance. In this paper, we propose a method of vehicle and pedestrian detection based on millimeter wave radar and camera. Moreover, the proposed method complete the detection of vehicle and pedestrian based on dynamic region generated by the radar data and sliding window. First, the radar target information is mapped to the image by means of coordinate transformation. Then by analyzing the scene, we obtain the sliding windows. Next, the sliding windows are detected by HOG features and SVM classifier in a rough detect. Then using the match function to confirm the target. Finally detecting the windows in a precision detection and merging the detecting windows.
2017-09-23
Technical Paper
2017-01-1988
XueFei Deng, Lu Che, Lei Zhang, Rong Sun
Abstract The problem of this paper can be described as: An oil company has a number of distribution centers in a region, these distribution centers have a number of the same type of multi- compartment vehicles, The optimization goal of the problem is that the distribution costs and carbon emissions considering the oil transportation process, through the model of rational allocation of each distribution center planning and tanker route, so that the cost and carbon emissions throughout the distribution process reached the minimum or at the same time the results of low. This paper studies a low-carbon oil distribution route optimization problem with the targets of minimizing the transport costs and carbon emissions. Firstly, the mathematical model is proposed to describe the problem. According to the characteristics of the model We propose a kind of improved multi-objective SA-TS hybrid optimization algorithm to solve this model.
2017-09-23
Technical Paper
2017-01-1987
Renjie Li, Shengbo Li, Hongbo Gao, Keqiang Li, Bo Cheng, Deyi Li
Abstract 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.
2017-09-23
Technical Paper
2017-01-1984
Jun Ma, Junyi Li, Zaiyan Gong, Jihong Yu
Abstract Given the wide adoption of touchscreens in vehicles, an interesting debate is taking place regarding the good screen size, length-width ratio and whether the usability of in-vehicle information system (IVIS) would be decreased by a larger screen, especially. Moreover, the lack of scientific evidence about the concrete impact of touch screen size on usability raises questions to practitioners. In this paper, we investigated the impact of in-vehicle touch screen size on users’ visual behavior and usability as measured using eye tracker and questionnaire. Two experiments were conducted on 30 participants. In the first experiment, participants were asked to seek same information on four different in-vehicle screens based on simulated driving environment, while eye movement was recorded for analyzing efficiency of visual behavior.
2017-09-23
Journal Article
2017-01-1983
Bing Zhu, Shude Yan, Jian Zhao, Weiwen Deng, Ning Bian
Abstract Electric power steering (EPS) system is a kind of dynamic control system for vehicle steering, which can amplify the driver steering torque inputs to the vehicle to improve steering comfortable and performance, but the present EPS can’t cater to the driving habits of different people. In this paper, a personalized EPS controller is designed based on the driver behavior, which combines real-time driver behavior identification strategy with personalized assistance characteristic. Firstly, the driver behavior data acquisition system is designed and established, based on which, the input data of different kinds of drivers along with vehicle signals are collected under typical working conditions, then the identification of driver behavior online is realized using the BP neural network.
2017-09-23
Technical Paper
2017-01-1992
Qin Xia, Jianli Duan, Feng Gao, Tao Chen, Cai Yang
Abstract ADAS must be tested thoroughly before they can be deployed for series production. Comparing with road and field test, bench test has been widely used owing to its advantages of less labor costs, more controllable scenarios, etc. However, there is no satisfied systematic approach to generate high-efficiency and full-coverage test scenarios automatically because of its integration of human, vehicle and traffic. Most of the test scenarios generated by the existing methods are either too simple or too few to be able to achieve full coverage of requirements. Besides, the cost is high when the ET method is used. To solve the aforementioned problems, an automatic test scenario generation method based on complexity for bench test is presented in this paper. Firstly, considering the fact that the device is easier to malfunction under complex cases, an index measuring the complexity of test case is proposed by using the method of AHP.
2017-09-23
Technical Paper
2017-01-1991
Adit Joshi
The automotive industry is heading towards the path of autonomy with the development of autonomous vehicles. An autonomous vehicle consists of two main components. The first is the software which is responsible for the decision-making capabilities of the system. The second is the hardware which encompasses all aspects of the physical vehicle which are responsible for vehicle motion such as the engine, brakes and steering subsystems along with their corresponding controls. This component forms the basis of the autonomous vehicle platform. For SAE Level 4 autonomous vehicles, where an automated driving system is responsible for all the dynamics driving tasks including the fallback driving performance in case of system faults, redundant mechanical systems and controls are required as part of the autonomous vehicle platform since the driver is completely out of the loop with respect to driving.
2017-09-23
Technical Paper
2017-01-1990
Xiangyu huang, Hao Zhou
Abstract The most important role of V2X technology is to significantly enhance driving safety. This paper proposes an Omni-directional collision warning method based on vehicle to vehicle communication. With the Basic Safety Message (BSM), the driving states of vehicles which communicate with host vehicle can be obtained. The warnings are divided into two categories based on the Lateral Offset calculation: forward collision warning (FCW) for vehicles moving in the same direction and cross collision warning (CCW) for vehicles moving in different directions. For vehicles which moves in the same direction, the lateral offset of the two vehicles, the time to collision (TTC) and time headway (THW) are used to estimate forward collision risk. For vehicles which moves in different directions, time to the closest point approach (TCPA) model and the separating axis theorem (SAT) are used for cross collision detection.
2017-09-23
Technical Paper
2017-01-1989
Yi Chen, Gaoxiang Lin, Ying He
Abstract Chinese National projects “13th Five Year Plan” and “Made in China 2025” have both put forward a goal of developing Intelligent and Connected Vehicles(ICV). Shanghai is a typical city of automobile industry which spearhead the development of China’s ICV industry. After the adjustment and transition of industrial structure, Shanghai has initially formed the industrialization layout of ICV covering core areas including environmental perception, intelligent decision-making, actuator, human-computer interaction and vehicle integration. However, currently Shanghai is still in the beginning stage and there exists a large gap with world advanced level in both the core technology and marketization. This article is based on former qualitative survey combined with quantitative analysis which uses the Analytic Hierarchy Process(AHP) method to objectively evaluate the status quo and development trend of Shanghai’s ICV.
2017-09-23
Technical Paper
2017-01-1997
Cui Hua
Abstract Vision based driving environment perception is current research hotspot in automatic driving field, which has made great progress due to the continuous breakthroughs in the research of deep neural network. As is well known, deep neural network has won tremendous successes in a wide variety of image recognition tasks, such as pedestrian detection and vehicle identification, which have accomplished the commercialization successfully in intelligent monitor system. Nevertheless, driving environment perception has a higher request for the generalization performance of deep neural network, which needs further studies on its design and training methods. In this paper, we presented a new boosted deep neural network in order to improve its generalization performance and meanwhile keep computational budget constant. Above all, the most representative methods to improve the generalization performance of deep neural network were introduced.
2017-09-23
Technical Paper
2017-01-1994
Adit Joshi
The advancement towards development of autonomy follows either the bottom-up approach of gradually improving and expanding existing Advanced Driver Assist Systems (ADAS) technology where the driver is present in the control loop or the top-down approach of directly developing Autonomous Vehicles (AV) hardware and software using alternative approaches without the driver present in the control loop. Most ADAS systems today fall under the classification of SAE Level 1 which is also referred to as the driver assistance level. The progression from SAE Level 1 to SAE Level 2 or partial automation involves the critical task of merging autonomous lateral control and autonomous longitudinal control such that the tasks of steering and acceleration/deceleration are not required to be handled by the driver under certain conditions [1].
2017-09-23
Technical Paper
2017-01-1996
Zhichao Lin, Xuexun Guo, Xiaofei Pei, Bo Yang, Yanggang Zhang
Abstract Dynamic modeling and state estimation are significant in the trajectory tracking and stability control of the intelligent vehicle. In order to meet the requirement of the stability control of the eight-in-wheel-motor-driven intelligent vehicle, a full vehicle dynamics model with 12 degrees of freedom, including the longitudinal, lateral, yaw and roll motion of the body, and rotational motion of 8 wheels, is established for the research of the intelligent vehicle in this paper. By simulation with MATLAB/SIMULINK and by comparison with the TruckSim software, the reliability and practicality of the dynamics model are verified. Based on the established dynamics model, an extended Kalman filter (EKF) state observer is proposed to estimate the vehicle sideslip angle, roll angle and yaw rate, which are the key parameters to the stability control of the intelligent vehicle.
2017-09-23
Technical Paper
2017-01-1993
Daoyuan Sun, Xiaofei Pei, Xu Hu, Hao Pan, Bo Yang
Abstract This paper presents a Driver-In-the-Loop (DIL) bench test system for development of ESC controller. The real-time platform is built-up based on NI/PXI system and the real steering/throttle/braking actuator. In addition, the CarSim provides the vehicle model and the animator for virtual driving environment. A hierarchical ESC controller is proposed in MATLAB/Simulink then download into PXI. In the upper motion controller, the sliding mode theory is adopted and the logic threshold algorithm is used in the lower slip controller. Finally, ESC test is implemented under typical conditions by DIL and Model-In-the-Loop (MIL). The results show that, DIL could make up the shortage of driver model which can’t accurately simulate the emergency response of real driver. Therefore, DIL test could verify the ESC controller more accurately and effectively with considering the human-vehicle-road environment.
2017-09-23
Technical Paper
2017-01-2003
Zhang Wei, 1Lt Xidaodong Tang
Active safety has grown to significant popularity in the recent years in the Chinese automotive market. So far the active safety devices such as radars, cameras and AEB are installed as the "bright spots " for the sales purpose. For some companies the devices also serve as the "point getter " in E-NCAP safety assessment. There has been no practical means for quantitative assessment of the real safety benefits from these devices. In this paper a CAE method is proposed not only to assess the safety performance of each device in each single standard setups, but also analyze the total safety performance of the integration of all the active safety devices. By utilizing a database of the past traffic accidents and reverse-constructing the road environments, the method makes it possible to quantitatively estimate the number of lives the active safety system could save.
2017-09-23
Technical Paper
2017-01-2005
Zhihong Wu, Jian_ning Zhao, Yuan Zhu, Qingchen Li
Abstract Vehicle cybersecurity consists of internal security and external security. Dedicated security hardware will play an important role in car’s internal and external security communication. TPM (Trusted Platform Module) can serve as the security cornerstone when vehicle connects with external entity or constructs a trusted computing environment. Based on functions such as the storage of certificate, key derivation and integrity testing, we research the principle of how to construct a trusted environment in a vehicle which has telematics unit. HSM (Hardware Security Module) can help to realize the onboard cryptographic communication securely and quickly so as to protect data. For certain AURIX MCU consisting of HSM, the experiment result shows that cheaper 32-bit HSM’s AES calculating speed is 25 times of 32-bit main controller, so HSM is an effective choice to realize cybersecurity.
2017-09-23
Technical Paper
2017-01-2004
Yangyang Wang, Rong Feng, Ding Pan, Zhiguang Liu, Nan Wu, Wei Li
Abstract The automatic lane change assist system is an intelligent driving assistance technology oriented to traffic safety, which requires trajectory planning of the lane change maneuver based on the lane change decision. A typical scene of lane change for overtaking is selected, where the front vehicle in the same lane and the rear vehicle in the left lane are deemed to be potential dangerous vehicles through the lane change. Lane change trajectory equation is first established according to the general law of steering wheel angle through lane changes. Based on the relative position, velocity and acceleration information of the dangerous vehicles and the lane change vehicle, motions of these surrounding dangerous vehicles are predicted. At the same time, a multi-objective optimization function is established based on the relative longitudinal safety boundary. The objectives are the minimum safety distance, the lane change time and the front wheel angle.
2017-09-23
Technical Paper
2017-01-1998
Shun Yang, Weiwen Deng, Zhenyi Liu, Ying Wang
Abstract 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.
2017-09-23
Technical Paper
2017-01-2007
Fang Li, Lifang Wang, Yan Wu
Abstract With the rapid development of vehicle intelligent and networking technology, the IT security of automotive systems becomes an important area of research. In addition to the basic vehicle control, intelligent advanced driver assistance systems, infotainment systems will all exchange data with in-vehicle network. Unfortunately, current communication network protocols, including Controller Area Network (CAN), FlexRay, MOST, and LIN have no security services, such as authentication or encryption, etc. Therefore, the vehicle are unprotected against malicious attacks. Since CAN bus is actually the most widely used field bus for in-vehicle communications in current automobiles, the security aspects of CAN bus is focused on. Based on the analysis of the current research status of CAN bus network security, this paper summarizes the CAN bus potential security vulnerabilities and the attack means.
2017-09-23
Technical Paper
2017-01-2000
Jianping Li, Jian Wu, Hao Sun, Yuyao Jiang, Weiwen Deng, Bing Zhu
Abstract Simulation has been considered as one of the key enablers on the development and testing for autonomous driving systems as in-vehicle and field testing can be very time-consuming, costly and often impossible due to safety concerns. Accurately modeling traffic, therefore, is critically important for autonomous driving simulation on threat assessment, trajectory planning, etc. Traditionally when modeling traffic, the motion of traffic vehicles is often considered to be deterministic and modeled based on its governing physics. However, the sensed or perceived motion of traffic vehicles can be full of errors or inaccuracy due to the inaccurate and/or incomplete sensing information. In addition, it is naturally true that any future trajectories are unknown. This paper proposes a novel modeling method on traffic considering its motion uncertainties, based on Gaussian process (GP).
2017-09-23
Technical Paper
2017-01-2001
Xin Li, Lixin Situ, Yongqiang Yu, Feng Chen
Abstract Research and development of autonomous functions for a road vehicle become increasingly active in recent years. However, the vehicle driving dynamics performance and safety are the big challenge for the development of autonomous vehicles especially in severe environments. The optimum driving dynamics can only be achieved when the traction torque on all wheels can be influenced and controlled precisely. In this study, we present a novel approach to this problem by designing an advanced torque vectoring controller for an autonomous vehicle with four direct-drive in-wheel motors to generate and control the traction torque and speed quickly and precisely, thus to improve the stability and safety of the autonomous vehicle. A four in-wheel motored autonomous vehicle equipped with Radar and camera is modelled in PanoSim software environment. Vehicle-to-Vehicle (V2V) communication is used in this software platform to avoid collision.
Viewing 271 to 300 of 85301