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Trajectory Planning and Tracking for Four-Wheel-Steering Autonomous Vehicle with V2V Communication

Jilin University-Fangwu Ma, Yucheng Shen, Jiahong Nie, Xiyu Li, Yu Yang, Jiawei Wang, Guanpu Wu
  • Technical Paper
  • 2020-01-0114
To be published on 2020-04-14 by SAE International in United States
Lane-changing is a typical traffic scene effecting on road traffic with high request for reliability, robustness and driving comfort to improve the road safety and transportation efficiency. The development of connected autonomous vehicles with V2V communication provide more advanced control strategies to research of lane-changing. Meanwhile, four-wheel steering is an effective way to improve flexibility of vehicle. The front and rear wheels rotate in opposite direction to reduce the turning radius to improve the servo agility operation at the low speed while those rotate in same direction to reduce the probability of the slip accident to improve the stability at the high speed. Hence, this paper established Four-Wheel-Steering(4WS) vehicle dynamic model and quasi real lane-changing scenes to analyze the motion constraints of the vehicles. Then, the polynomial function was used for the lane-changing trajectory planning and the extended rectangular vehicle model was established to get vehicle collision avoidance condition. Vehicle comfort requirements and lane-changing efficiency were used as the optimization variables of optimization function and the control of trajectory tracking can be obtained by using…
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A Dynamic Trajectory Planning for Automatic Vehicles Based on Improved Discrete Optimization Method

Chongqing University-Pengyun Zeng, Zheng Ling
  • Technical Paper
  • 2020-01-0120
To be published on 2020-04-14 by SAE International in United States
The dynamic trajectory planning problem for automatic vehicles in complex traffic scenarios is investigated in this paper. A hierarchical motion planning framework is developed to complete the complex planning task. An improved dangerous potential field in the curvilinear coordinate system is constructed to describe the collision risk of automatic vehicles accurately instead of the discrete Gaussian convolution algorithm. At the same time, the driving comfort is also considered in order to generate an optimal, smooth, collision-free and feasible path in dynamics. The optimal path can be mapped into the Cartesian coordinate system simply and conveniently. Furthermore, a velocity profile considering practical vehicle dynamics is also presented to improve the safety and the comfort in driving. The effectiveness of the proposed dynamic trajectory planning is verified by numerical simulation for several typical traffic scenarios.
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Decision Making and Trajectory Planning of Intelligent Vehicle’ s Lane-Changing Behavior on Highways under Multi-Objective Constrains

Wuhan University of Technology-Linzhen Nie, Zhishuai Yin, Haoran Huang
  • Technical Paper
  • 2020-01-0124
To be published on 2020-04-14 by SAE International in United States
Discretionary lane changing is commonly seen in highway driving. Intelligent vehicles are expected to change lanes discretionarily for better driving experience and higher traffic efficiency. This study proposed to optimize the decision-making and trajectory-planning process so that intelligent vehicles made lane changes not only with driving safety taken into account, but also with the goal to improve driving comfort as well as to meet the driver’ s expectation. The mechanism of how various factors contribute to the driver’s intention to change lanes was studied by carrying out a series of driving simulation experiments, and a Lane-Changing Intention Generation (LCIG) model based on Bi-directional Long Short-Term Memory (Bi-LSTM) was proposed. The inputs of the Bi-LSTM were data fragments of several influencing factors including the relative velocity and the distance between the relative vehicles, the type of the preceding vehicles, and the average velocity of the adjacent traffic flows, that over a certain period of time, which was determined via examining subjects’ visual behaviors of the left view mirror or the right view mirror. By combining the…
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Nonlinear Model Predictive Control of Autonomous Vehicles Considering Dynamic Stability Constraints

Tongji University-Xunjie Chen, Guangqiang Wu, Meng Ren
  • Technical Paper
  • 2020-01-1400
To be published on 2020-04-14 by SAE International in United States
Autonomous vehicle performance is increasingly highlighted in many highway driving scenarios, which leads to more priorities to vehicle stability as well as tracking accuracy. In this paper, a nonlinear model predictive controller for autonomous vehicle trajectory tracking is designed and verified through a real-time simulation bench of a virtual test track. The dynamic stability constraints of nonlinear model predictive control (NLMPC) are obtained by a novel quadrilateral stability region criterion instead of the conventional phase plane method using the double-line region. First, a typical lane change scene of overtaking is selected and a new composited trajectory model is proposed as a reference path that combines smoothness of sine wave and comfort of linear functional path. Reference lateral velocity, azimuth angle, yaw rate, and front wheel steering angle are subsequently taken into account. Then, by establishing a nonlinear vehicle dynamics model where Magic Formula of nonlinear tire model is adapted, the quadrilateral vehicle stability region is defined in consideration of designed velocity, road adhesion coefficient, and front wheel steering angle. Working condition-variant constraints determined by the…
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An LQR Approach of Automatic Transmission Upshift Control Including Use of Off-Going Clutch within Inertia Phase

Ford Motor Company-Vladimir Ivanovic, Yijing Zhang, Yuji Fujii
University of Zagreb-Ivan Cvok, Josko Deur
  • Technical Paper
  • 2020-01-0970
To be published on 2020-04-14 by SAE International in United States
This paper considers using linear quadratic regulation (LQR) for multi-input control of the Automatic Transmission (AT) upshift inertia phase. The considered control inputs include the transmission input/engine torque, oncoming clutch torque, and traditionally not used off-going clutch torque. Use of the off-going clutch has been motivated by discussed Control Trajectory Optimization (CTO) results demonstrating that employing the off-going clutch during the inertia phase along with the main, oncoming clutch can improve the upshift control performance in terms of the shift duration and/or comfort by trading off the transmission efficiency and control simplicity to some extent. The proposed LQR approach provides setting an optimal trade-off between the conflicting criteria related to driving comfort and clutches thermal energy loss. It ensures tracking a linear-like profile of oncoming clutch slip speed reference, which was found to be nearly optimal based on control trajectory optimization results. A special attention is given on proper implementation of nonlinear energy loss term through LQR cost function cross term and using a clipped optimal control approach to provide that the clutches (described as…
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Decision Making and Trajectory Planning for Lane Change Control Inspired by Parallel Parking

Tsinghua University-Liangyao Yu, Ze Ru, Zhenghong Lu, Guanqun Liang, Cenbo Xiong, Abi Lanie, Ruyue Wang
  • Technical Paper
  • 2020-01-0134
To be published on 2020-04-14 by SAE International in United States
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. Compared to algorithm for static parking space, the uncertainty of the space between moving vehicles and host vehicle dynamics raises stricter requirements for algorithms. Works are conducted to deal with dynamically changing scenarios, such…
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Toward High Automatic Driving by a Dynamic Optimal Trajectory Planning Method Based on High-order Polynomials

Hunan University-Haotian Cao, Xiaolin Song, Mingjun Li
Waterloo University-Song Zhao
  • Technical Paper
  • 2020-01-0106
To be published on 2020-04-14 by SAE International in United States
Automatic driving has received great attention from a broad of domains such as academia, industry, and government nowadays, while the subsystem of the path-planning for obstacle avoidance is crucial for the high-level automatic driving vehicle. This paper intends to present a novel optimal path planning method for obstacle avoidance on highways. At first, a mapping from the road Cartesian coordinate system to the road Frenet-based coordinate system is built, and the path lateral offset in the road Frenet-based coordinate system is represented by a function of quintic polynomial respecting to the traveled distance along the road centerline. With different terminal conditions regarding its position, heading and curvature of the endpoint, and together with initial conditions of the starting point, the path planner generates a bunch of candidate paths via solving nonlinear equation sets numerically. Then a path selecting mechanism is built which considers a normalized weighted sum of the path length, curvature, heading error to the road centerline, the consistency with the previous path, as well as the road hazard risk. The road hazard is…
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Intention-aware Lane Changing Assistance Strategy Basing on Traffic Situation Assessment

Jilin University-Jian Wu, Sihan Liu, Rui He, Bohua Sun
  • Technical Paper
  • 2020-01-0127
To be published on 2020-04-14 by SAE International in United States
Traffic accidents avoidance is one of the main advantages for automated vehicles. As one of the main causes of vehicle collision accidents, lane changing of the ego vehicle in case that the obstacle vehicles appear in the blind spot with uncertain motion intentions is one of the main goals for the automated vehicle. An intention-aware lane changing collision assistance strategy basing on traffic situation assessment in the complex traffic scenarios is proposed in this paper. Typical Regions of Interest (ROI) within the detection range of the blind spots are selected basing on the road topology structures and state space consisting of the ego vehicle and the obstacle vehicles. Then the motion intentions of the obstacle vehicles in ROI are identified basing on Gaussian Mixture Models (GMM) and the corresponding motion trajectories are predicted basing on the state equation. Traffic situation is assessed according to the index of the motion intentions and the coupling tendency between the ego vehicle and the obstacle vehicles and the risk level is graded basing on the map with collision time.…
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Vehicle Trajectory Prediction Based on Motion Model and Maneuver Model Fusion with Interactive Multiple Models

Tongji University-Wei Xiao, Lijun Zhang, Dejian Meng
  • Technical Paper
  • 2020-01-0112
To be published on 2020-04-14 by SAE International in United States
Safety is the cornerstone for Advanced Driver Assistance Systems (ADAS) and Autonomous Driving Systems (ADS). To assess the safety of a traffic situation, it is essential to predict motion states of traffic participants in the future with mathematic models. Accurate vehicle trajectory prediction is an important prerequisite for reasonable traffic situation risk assessment and appropriate decision making. Vehicle trajectory prediction methods can be generally divided into motion model based methods and maneuver model based methods. Vehicle trajectory prediction based on motion models can be accurate and reliable only in the short term. While vehicle trajectory prediction based on maneuver models present more satisfactory performance in the long term, these maneuver models rely on machine learning methods. Abundant data should be collected to train the maneuver recognition model, which increases complexity and lowers real-time performance. In this paper, a vehicle trajectory prediction method based on motion model and maneuver model fusion with Interactive Multiple Model (IMM) is proposed. Firstly, Constant Turn Rate and Acceleration (CTRA) motion model and Unscented Kalman Filter (UKF) are used to predict…
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Customer Oriented Vehicle Dynamics Assessment for Autonomous Driving in Highway

Centro Ricerche Fiat-Giovanni Gabiati
Fiat Chrysler Automobiles-Silvio Data
Published 2019-04-02 by SAE International in United States
Autonomous Driving is one of the main subjects of academic research and one important trend in the automotive industry. With the advent of self-driving vehicles, the interest around trajectory planning raises, in particular when a customer-oriented analysis is performed, since more and more the carmakers will have to pay attention to the handling comfort.With that in mind, an experimental approach is proposed to assess the main characteristics of human driving and gain knowledge to enhance quality of autonomous vehicles. Focusing on overtaking maneuvers in a highway environment, four comfort indicators are proposed aiming to capture the key aspects of the chosen paths of a heterogeneous cohort.The analysis of the distribution of these indicators (peak to peak lateral acceleration, RMS lateral acceleration, Smoothness and Jerk) allowed the definition of a human drive profile. These characteristics were then transferred to the simulation environment to create a pseudo-natural trajectory planning strategy, via polynomial fitting and spline optimization. This strategy differs from the standard approach of trajectory planning, where absolute minimums of cost functions are pursued.The polynomial and spline…
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