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A Maneuver-Based Threat Assessment Strategy for Collision Avoidance

SAE International Journal of Passenger Cars - Electronic and Electrical Systems

Beihang University, China-Weiwen Deng
General Motors LLC, USA-Jinsong Wang
  • Journal Article
  • 07-12-01-0003
Published 2019-08-22 by SAE International in United States
Advanced driver-assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of the driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This article presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modelled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models. Subsequently, time to collision (TTC) is calculated in a strategy of employing collision detection at every predicted trajectory instance. For this purpose, safe areas via bounding boxes are applied on every vehicle, and Separating Axis Theorem (SAT) is applied for collision prediction…
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Trajectory-Tracking Control for Autonomous Driving Considering Its Stability with ESP

General Motors-Jinsong Wang
Jilin Univ.-Fei Pan, Weiwen Deng, Sumin Zhang, Shanshan Wang
Published 2018-08-07 by SAE International in United States
With rapid increase of vehicles on the road, safety concerns have become increasingly prominent. Since the leading cause of many traffic accidents is known to be by human drivers, developing autonomous vehicles is considered to be an effective approach to solve the problems above. Although trajectory tracking plays one of the most important roles on autonomous driving, handling the coupling between trajectory-tracking control and ESP under certain driving scenarios remains to be challenging.This paper focuses on trajectory-tracking control considering the role of ESP. A vehicle model is developed with two degrees of freedom, including vehicle lateral, and yaw motions. Based on the proposed model, the vehicle trajectory is separated into both longitudinal and lateral motion. The coupling effect of the vehicle and ESP is analyzed in the paper. The lateral trajectory-tracking algorithm is developed based on the preview follower theory. Spacing control strategy is used in longitudinal trajectory-tracking algorithm. Yaw angular velocity and lateral deflection are the control variables for ESP. When the vehicle is under certain driving scenarios remains to be challenging, the influence…
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Mechanism Analysis and Simulation Study of Automobile Millimeter Wave Radar Noise

General Motors-Jinsong Wang
Jilin Univ.-Weiwen Deng, Shanshan Wang
Published 2018-08-07 by SAE International in United States
The paper analyzes the mechanism of automobile millimeter wave radar noise, this paper does not study radar noise from the angle of signal processing, but from the level of false detection and missed detection, at the same time, the noise mechanism is modeled and verified.Firstly, the purpose and significance of the research of radar vehicle noise are described, and then, we summarize and outline the macro phenomenon and the specific characteristics of the automobile millimeter wave radar noise. On the basis of the above discussion, the paper studies three aspects in detail: firstly, the mechanism of the false detection “multi path propagation of electromagnetic wave” and “multi radar interference” is studied; secondly, the mechanism of the missed detection“ propagation loss of the space environment “and“ dynamic changes of target RCS “is studied; finally, the simulation of the noise mechanism is carried out by using NI Vehicle Radar Test System and the Delphi radar, the accuracy of noise mechanism in the target false detection and missed detection are compared and analyzed.The paper presents a set of…
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Studies on Drivers’ Driving Styles Based on Inverse Reinforcement Learning

General Motors LLC-Jinsong Wang
Jilin University-Yuande Jiang, Weiwen Deng, Bing Zhu
Published 2018-04-03 by SAE International in United States
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. Based on the reinforcement learning theory, driving action can be treated as maximizing a reward function. Instead of calibrating the unknown reward function to satisfy driver’s desired response, we try to recover it from the human driving data, utilizing maximum likelihood inverse reinforcement learning (MLIRL). An…
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GPS Modeling for Vehicle Intelligent Driving Simulation

SAE International Journal of Connected and Automated Vehicles

General Motors LLC-Jinsong Wang
Jilin University-Xiangyue Gao, Weiwen Deng
  • Journal Article
  • 2018-01-0763
Published 2018-04-03 by SAE International in United States
In recent years, intelligent vehicles have become one of the major research topics in vehicle engineering and have created a new opportunity for the automotive industry. Simulation and real experiment are both essential to the development of intelligent vehicle technologies. Vehicle positioning systems, such as global positioning system (GPS), play an important role in intelligent vehicle development. The GPS model plays a major part in the development of intelligent vehicle simulation systems. Primarily focusing on application requirements of intelligent vehicle simulation platforms for GPS sensor modeling, considering the major factors affecting positioning accuracy in vehicle driving environments, this article establishes a new GPS model and algorithm based on the physical and functional characteristics of GPS. As the basis of this model system, a precise ephemeris model is established to obtain the coordinates of GPS satellites at any given time. A new occlusion model is proposed in order to describe external environmental disturbance more effectively. This model takes into account not only the emission angle of the satellite signal and the shadow of the earth but…
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Driving Behavior Prediction at Roundabouts Based on Integrated Simulation Platform

General Motors LLC-Jinsong Wang
Jilin University-Shun Yang, Yuande Jiang, Guojun Wang, Weiwen Deng
Published 2018-04-03 by SAE International in United States
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. Ten drivers were chosen for the data acquisition. Samples of these drivers were used in training the random forest classifier. The out-of-bag errors indicates that random forest model has good performance in predicting the roundabout behaviors…
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Design and Control of Torque Feedback Device for Driving Simulator Based on MR Fluid and Coil Spring Structure

General Motors LLC-Jinsong Wang
Jilin University-Hongwei Jiang, Weiwen Deng, Yuyao Jiang
Published 2018-04-03 by SAE International in United States
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. Simulation has been conducted to compare the proposed device and control method with the systems under conventional approaches, and the results show that the feedback torque from the…
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A Nonlinear Slip Ratio Observer Based on ISS Method for Electric Vehicles

Beihang University-Bingtao Ren, Weiwen Deng
General Motors LLC-Jinsong Wang
Published 2018-04-03 by SAE International in United States
Knowledge of the tire slip ratio can greatly improve vehicle longitudinal stability and its dynamic performance. Most conventional slip ratio observers were mainly designed based on input of non-driven wheel speed and estimated vehicle speed. However, they are not applicable for electric vehicles (EVs) with four in-wheel motors. Also conventional methods on speed estimation via integration of accelerometer signals can often lead to large offset by long-time integral calculation. Further, model uncertainties, including steady state error and unmodeled dynamics, are considered as additive disturbances, and may affect the stability of the system with estimated state error. This paper proposes a novel slip ratio observer based on input-to-state stability (ISS) method for electric vehicles with four-wheel independent driving motors. Instead of estimating vehicle speed, the proposed method employs the estimated error of motor torque as the correction output by taking the advantage of electric vehicles that the torque of the driving motors can directly reflect the tire force. Also vehicle acceleration is directly used as a time-varying parameter of the system to reflect the longitudinal dynamic…
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A Comprehensive Testing and Evaluation Approach for Autonomous Vehicles

General Motors LLC-Jinsong Wang
Jilin University-Guojun Wang, Weiwen Deng, Sumin Zhang, Shun Yang
Published 2018-04-03 by SAE International in United States
Performance testing and evaluation always plays an important role in the developmental process of a vehicle, which also applies to autonomous vehicles. The complex nature of an autonomous vehicle from architecture to functionality demands even more quality-and-quantity controlled testing and evaluation than ever before. Most of the existing testing methodologies are task-or-scenario based and can only support single or partial functional testing. These approaches may be helpful at the initial stage of autonomous vehicle development. However, as the integrated autonomous system gets mature, these approaches fall short of supporting comprehensive performance evaluation. This paper proposes a novel hierarchical and systematic testing and evaluation approach to bridge the above-mentioned gap. In this paper, firstly a three-dimensional evaluation model conforming to the functional architecture of autonomous vehicles was built, with each dimension representing one of the three key functional layers of autonomous vehicle including sensing & perception, decision-making ﹠ planning, control & execution. Each dimension has a set of metrics carefully defined with their weights fairly determined based on an entropy weights method. Then, considering environment effect…
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A Maneuver-Based Threat Assessment Strategy for Collision Avoidance

General Motors LLC-Jinsong Wang
Jilin University-Yaxin Li, Weiwen Deng, Bohua Sun, Jian Zhao
Published 2018-04-03 by SAE International in United States
Advanced driver assistance systems (ADAS) are being developed for more and more complicated application scenarios, which often require more predictive strategies with better understanding of driving environment. Taking traffic vehicles’ maneuvers into account can greatly expand the beforehand time span for danger awareness. This paper presents a maneuver-based strategy to vehicle collision threat assessment. First, a maneuver-based trajectory prediction model (MTPM) is built, in which near-future trajectories of ego vehicle and traffic vehicles are estimated with the combination of vehicle’s maneuvers and kinematic models that correspond to every maneuver. The most probable maneuvers of ego vehicle and each traffic vehicles are modeled and inferred via Hidden Markov Models with mixture of Gaussians outputs (GMHMM). Based on the inferred maneuvers, trajectory sets consisting of vehicles’ position and motion states are predicted by kinematic models. Subsequently, time to collision (TTC) is calculated in a strategy of employing collision detection at every predicted trajectory instance. For this purpose, safe areas via bounding boxes are applied on every vehicle, and Separating Axis Theorem (SAT) is applied for collision prediction,…
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