Automated mixed traffic vehicle design AMTV 2

The design of an improved and enclosed Automated Mixed Traffic Transit (AMTT) vehicle is described. AMTT is an innovative concept for low-speed tram-type transit in which suitable vehicles are equipped with sensors and controls to permit them to operate in an automated mode on existing road or walkway surfaces. The vehicle chassis and body design are presented in terms of sketches and photographs. The functional design of the sensing and control system is presented, and modifications which could be made to the baseline design for improved performance, in particular to incorporate a 20-mph capability, are also discussed. The vehicle system is described at the block-diagram-level of detail. Specifications and parameter values are given where available

Perception enhancement system for automotive steering

Laboratory-based experiments were conducted to evaluate the effect of the frequency and scale of transient vibration events on the human detection of road surface type by means of steering wheel vibration. The study used steering wheel tangential direction acceleration time histories which had been measured in a mid-sized European automobile that was driven over three different types of road surface. The steering acceleration stimuli were manipulated by means of the mildly non-stationary mission synthesis (MNMS) algorithm in order to produce test stimuli which were selectively modified in terms of the number, and size, of transient vibration events they contained. Fifteen test participants were exposed to both unmanipulated and manipulated steering wheel rotational vibration stimuli, and were asked to indicate, by either “yes or no”, whether the test stimuli was from a target road surface which was displayed on a board. The findings suggested that transient vibration events play a key role in the human detection of road surface type in driving situations. Improvements of up to 20 percentage points in the rate of correct detection were achieved by means of selective manipulation of the steering vibration stimuli. The results also suggested, however, that no single setting of the MNMS algorithm proved optimal for all three road surface types that were investigated

Effect of transient event frequency content and scale on the human detection of road surface type

This paper describes two laboratory-based experiments which evaluate the effect of transient event frequency content and scale on the human detection of road surface type by means of steering wheel vibration. This study used steering wheel tangential direction acceleration time histories which had been measured in a mid-sized European automobile that was driven over two different types of road surface. The steering acceleration stimuli were manipulated by means of the mildly non-stationary mission synthesis (MNMS) algorithm in order to produce test stimuli which were selectively modified in terms of the number, and size, of transient vibration events they contained. Fifteen test participants were exposed to both unmanipulated and manipulated steering wheel rotational stimuli by means of a steering wheel vibration simulator. For each road surface type a total of 45 vibration test stimuli were presented to each participant. Each participant was asked to state, by means of a simple "yes" or "no" answer, whether each individual stimuli was from a road surface which was being presented in front of the simulator as a picture on a large board. Using Signal Detection Theory as the analytical framework the results were summarized by means of the detectability index d' and by means of receiver operating curve (ROC) points. Improvements of up to 20 percentage points in the rate of correct detection were achieved by means of selective manipulation of the steering vibration stimuli. The results suggested that no single setting of the MNMS algorithm proved optimal for both two road surface types that were investigated

Making Transport Safer: V2V-Based Automated Emergency Braking System

An important goal in the field of intelligent transportation systems (ITS) is to provide driving aids aimed at preventing accidents and reducing the number of traffic victims. The commonest traffic accidents in urban areas are due to sudden braking that demands a very fast response on the part of drivers. Attempts to solve this problem have motivated many ITS advances including the detection of the intention of surrounding cars using lasers, radars or cameras. However, this might not be enough to increase safety when there is a danger of collision. Vehicle to vehicle communications are needed to ensure that the other intentions of cars are also available. The article describes the development of a controller to perform an emergency stop via an electro-hydraulic braking system employed on dry asphalt. An original V2V communication scheme based on WiFi cards has been used for broadcasting positioning information to other vehicles. The reliability of the scheme has been theoretically analyzed to estimate its performance when the number of vehicles involved is much higher. This controller has been incorporated into the AUTOPIA program control for automatic cars. The system has been implemented in Citroën C3 Pluriel, and various tests were performed to evaluate its operation

Worked Example of X-by-Wire Technology in Electric Vehicle: Braking and Steering

The chapter emphasizes on the worked example of braking system and steering system for electric vehicle. The x-by-wire technology is investigated and validated comprehensively. Brake-by-wire is considered a new brake technology that uses electronic devices and control system instead of conventional brake components to carry out braking function based on wire-transmitted information. However, the physical parameters associated with braking function cause nonlinear characteristics and variations in the braking dynamics, which eventually degrade stability and performance of the system. Therefore, this study presents the design of fuzzy-PID controller for brake-by-wire (BBW) to overcome these undesired effects and also to derive optimal brake force that assists to perform braking operation under distinct road conditions and distinct road types. Electric power-assisted steering (EPAS) system is a new power steering technology for vehicles especially for electric vehicles (EV). It has been applied to displace conventional hydraulic power-assisted steering (HPAS) system due to space efficiency, environmental compatibility, and engine performance. An EPAS system is a driver-assisting feedback system designed to boost the driver input torque to a desired output torque causing the steering action to be undertaken at much lower steering efforts

스티어 바이 와이어 시스템의 목표 조향감 재현을 위한 조향 반력 제어

학위논문(박사)--서울대학교 대학원 :공과대학 기계공학부,2020. 2. 이경수.This dissertation focused on the development of and steering assist torque control algorithm of Electric-Power-Steering (EPS) system from the conventional steering system perspective and Steer-by-Wire (SBW) system. The steering assist torque control algorithm has been developed to overcome the major disadvantage of the conventional method of time-consuming tuning to achieve the desired steering feel. A reference steering wheel torque map was designed by post-processing data obtained from target performance vehicle tests with a highly-rated steering feel for both sinusoidal and transition steering inputs. Adaptive sliding-mode control was adopted to ensure robustness against uncertainty in the steering system, and the equivalent moment of inertia damping coefficient and effective compliance were adapted to improve tracking performance. Effective compliance played a role in compensating the error between the nominal rack force and the actual rack force. For the SBW system, the previously proposed EPS assist torque algorithm has been also enhanced using impedance model and applied to steering feedback system. Stable execution and how to give the person the proper steering feedback torque of contact tasks by steering wheel system interaction with human has been identified as one of the major challenges in SBW system. Thus, the problem was solved by utilizing the target steering torque map proposed above. The impedance control consists of impedance model (Reference model with the target steering wheel torque map) and controller (Adaptive sliding mode control). The performance of the proposed controller was evaluated by conducting computer simulations and a hardware-in-the-loop simulation (HILS) under various steering conditions. Optimal steering wheel torque tracking performances were successfully achieved by the proposed EPS and SBW control algorithm.본 논문은 종래의 조향 시스템 관점에서 전동식 동력 조향 (EPS) 시스템과 스티어 바이 와이어 (SBW) 조향 보조 토크 제어 알고리즘의 개발을 중점으로 하였습니다. 기존 조향 보조 토크 제어 알고리즘은 원하는 조향감을 구현하기 위해 종래의 시간 소모적 인 튜닝 방법을 사용합니다. 이러한 주요 단점을 극복하기 위해 새로운 조향 보조 제어 알고리즘을 개발하였습니다. 목표 스티어링 휠 토크 맵은 정현파(Weave test) 및 등속도 스티어링 입력 (Transition test) 모두에 대해 높은 등급의 조향감을 차량 테스트에서 얻은 후 데이터 처리를 하여 설계되었습니다. 스티어링 시스템의 불확실성에 대한 강건성을 보장하기 위해 적응 형 슬라이딩 모드 제어가 채택되었으며, 관성 모멘트 감쇠 계수와 컴플라이언스 계수(Effective compliance)가 제어기 성능을 개선하도록 적응형 파라미터로 선정되었습니다. 컴플라이언스 계수는 계산된 랙 힘과 실제 랙 힘 사이의 차이를 보상하는 역할을 했습니다. SBW 시스템의 경우, 이전에 제안 된 EPS 지원 토크 알고리즘을 개선하고 향상시키기 위해 임피던스 모델을 사용하였으며 스티어링 피드백 시스템에 적용되었습니다. SBW 시스템의 주요 과제 중 하나는 사람과 스티어링 휠 시스템 상호 작용에 의해 안정적인 작동과 사람에게 적절한 스티어링 피드백 토크를 제공하는 방법입니다. 임피던스 제어는 임피던스 모델 (타겟 스티어링 휠 토크 맵)과 컨트롤러 (적응 슬라이딩 모드 제어)로 구성됩니다. 따라서, 상기 제안 된 목표 조향 토크 맵을 이용함으로써 스티어 바이 와이어에서 스티어링 피드백 토크를 절절히 적용 됨을 확인 하였습니다. 제안 된 컨트롤러의 성능은 다양한 조향 조건에서 컴퓨터 시뮬레이션 및 HILS (Hardware-in-the-loop) 시뮬레이션을 수행하여 평가되었습니다. 제안 된 EPS 및 SBW 제어 알고리즘을 통해 최적의 스티어링 휠 토크 추적 성능을 달성했습니다.Chapter 1 Introduction 1 1.1. Background and Motivation 1 1.2. Previous Researches 4 1.3. Thesis Objectives 9 1.4. Thesis Outline 10 Chapter 2 Dynamic Model of Steering Systems 11 2.1. Dynamic model of Hydraulic/Electrohydraulic Power-Assisted Steering Model 11 2.2. Dynamic model of Electric-Power-Assisted-Steering Model 17 2.3. Dynamic model of Steer-by-Wire Model 21 2.4. Rack force characteristic of steering system 23 Chapter 3 Target steering wheel torque tracking control 28 3.1. Target steering torque map generation 28 3.2. Adaptive sliding mode control design for target steering wheel torque tracking with EPS 30 3.2.1. Steering states estimation with a kalman filter 38 3.3. Impedance Control Design for Target Steering Wheel Torque Tracking with SBW 43 Chapter 4 Validation with Simulation and Hardware-in-the-Loops Simulation 49 4.1. Computer Simulation Results for EPS system 49 4.2. Hardware-in-the-Loops Simulation Results for EPS system 61 4.3. Computer Simulation Results for SBW system 77 4.4. Hardware-in-the-Loops Simulation Results for SBW system 82 Chapter 5 Conclusion and Future works 89 Bibliography 91 Abstract in Korean 97Docto

Actuators for Intelligent Electric Vehicles

This book details the advanced actuators for IEVs and the control algorithm design. In the actuator design, the configuration four-wheel independent drive/steering electric vehicles is reviewed. An in-wheel two-speed AMT with selectable one-way clutch is designed for IEV. Considering uncertainties, the optimization design for the planetary gear train of IEV is conducted. An electric power steering system is designed for IEV. In addition, advanced control algorithms are proposed in favour of active safety improvement. A supervision mechanism is applied to the segment drift control of autonomous driving. Double super-resolution network is used to design the intelligent driving algorithm. Torque distribution control technology and four-wheel steering technology are utilized for path tracking and adaptive cruise control. To advance the control accuracy, advanced estimation algorithms are studied in this book. The tyre-road peak friction coefficient under full slip rate range is identified based on the normalized tyre model. The pressure of the electro-hydraulic brake system is estimated based on signal fusion. Besides, a multi-semantic driver behaviour recognition model of autonomous vehicles is designed using confidence fusion mechanism. Moreover, a mono-vision based lateral localization system of low-cost autonomous vehicles is proposed with deep learning curb detection. To sum up, the discussed advanced actuators, control and estimation algorithms are beneficial to the active safety improvement of IEVs