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A Deep Forward Collision Detector Based on Deep Reinforcement Learning

Concordia University Montreal-Pedram Fekri, Javad Dargahi
Kettering University-Mehrdad Zadeh
  • Technical Paper
  • 2020-01-0138
To be published on 2020-04-14 by SAE International in United States
Forward collision is one of the most challenging concern in the safety of autonomous vehicle. Cooperation between many sensors such as LIDAR, Radar and camera helps to enhance the safety. Apart from the significance of being aware of objects on the drivable area, making an apt decision in the moment is noticeable. In this study, we concentrate on detecting front vehicle of autonomous car using a sensor fusion method, beyond only a detection method. In fact, we devise a solution which provides forward collision warning signal by discriminating between the vehicles moving in and opposite direction of autonomous vehicle, without lane check. Then, the result of classification is combined by the speed of autonomous vehicle as well as the size of detected front vehicle in the images. As a sensor fusion method, this data is utilized to determine whether the front detected car is an obstacle with a potential collision hazard or not. For this reason, we implement a deep neural network with two main parts. The first part is a faster regional convolutional neural…
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Design and Development of an Ultrasonic Fatigue Testing System for Very High Cycle Fatigue

Concordia University Montreal-Paul Catalin Ilie, Xavier Lesperance, Ayhan Ince
  • Technical Paper
  • 2020-01-0183
To be published on 2020-04-14 by SAE International in United States
There has been growing demand for increased fuel efficiency, reduced emissions and improved power performance while maintaining reliability and durability of mechanical and structural systems in many different industries. The structural engineering components often experience long loading histories, typically ten million cycles or greater, i.e. high cycle fatigue (HCF) and very high cycle fatigue (VHCF) regimes. HCF in the range of 106-108 cycles and VHCF in the range of 108-1010 cycles are key design criteria for aerospace, automotive, military, transportation and many other industries. However, fatigue characterization of metal alloys in the HCF and VHCF regimes is hindered by limitations of traditional fatigue testing machines due to time and cost constraints. The development of high power piezoceramic actuators enables efficient and reliable fatigue tests in the HCF and VHCF regimes within a very short time frame on the basis of ultrasonic fatigue testing approaches. A fully instrumented ultrasonic fatigue test machine operating at 20 kHz was designed and built to investigate HCF and VHCF behavior of lightweight metallic alloys. The fatigue testing machine went through…
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A Control Strategy to Reduce Torque Oscillation of the Electric Power Steering System

Concordia University Montreal-Subhash Rakheja
South China University of Technology-Duo Fu, Wen-Jun Yan, Wen-Bin Shangguan
Published 2019-06-05 by SAE International in United States
This paper proposes a new evaluation method of analyzing stability and design of a controller for an electric power steering (EPS) system. The main purpose of the EPS system’s control design is to ensure a comfortable driving experience of drivers, which mainly depends on the assist torque map. However, the high level of assist gain and its nonlinearity may cause oscillation, divergence and instability to the steering systems. Therefore, an EPS system needs to have an extra stability controller to eliminate the side effect of assist gain on system stability and attenuate the unpleasant vibration. In this paper, an accurate theoretical model is built and the method for evaluating system quality are suggested. The bench tests and vehicle experiments are carried out to verify the theoretical analysis. The evaluation method proposed in this paper can not only guide the design of controller parameters, but also evaluate the control effect while the performance of several controllers are all excellent.
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On the Safety of Autonomous Driving: A Dynamic Deep Object Detection Approach

Concordia University Montreal-Javad Dargahi
Kettering University-Mehrdad Zadeh
Published 2019-04-02 by SAE International in United States
To improve the safety of automated driving, the paramount target of this intelligent system is to detect and segment the obstacle such as car and pedestrian, precisely. Object detection in self-driving vehicle has chiefly accomplished by making decision and detecting objects through each frame of video. However, there are diverse group of methods in both machine learning and machine vision to improve the performance of system. It is significant to factor in the function of the time in the detection phase. In other word, considering the inputs of system, which have been emitted from eclectic type of sensors such as camera, radar, and LIDAR, as time-varying signals, can be helpful to engross ‘time’ as a fundamental feature in modeling for forecasting the object, while car is moving on the way. In this paper, we focus on eliciting a model through the time to increase the accuracy of object detection in self-driving vehicles. In fact, we designed a deep recurrent neural network, which is fed by the output of a deep convolutional neural network. Eventually, the…
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Optimization for Power System of Electric Vehicle Based on CPSO

Concordia University Montreal-Bin Li
Zhaoqing University-Tianjun Zhu, Hongyan Zheng
Published 2019-04-02 by SAE International in United States
To improve the power and economy performance of pure electric vehicles, chaos particle swarm optimization (CPSO) algorithm is adopted in this study to optimize the parameters of the power system. The optimized parameter is then imported into CRUISE. The whole vehicle performance simulation in power system optimization for pure electric vehicle is carried out in CRUISE. Simulation results show that optimized vehicles can meet the expected dynamic performance and the driving range has been greatly improved. Meanwhile, it is also viable that the parameters of the optimal objective function can achieve the purpose of balancing the power performance and economic performance, which provides a reference for the development of vehicle power performance.
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Model-Based Systems Engineering Methodology for Implementing Networked Aircraft Control System on Integrated Modular Avionics – Environmental Control System Case Study

Concordia University Montreal-Prince George Mathew, Susan Liscouet-Hanke
Bombardier Aerospace-Yann Le Masson
Published 2018-10-30 by SAE International in United States
Integrated modular avionics (IMA) architectures host multiple federated avionics applications on a single platform and provide benefits in terms of size, weight, and power, which, however, leads to increased complexity, especially during the development process. To cope efficiently with the high level of complexity, a novel, structured development methodology is required. This paper presents a model-based systems engineering (MBSE) development approach for the so-called “distributed integrated modular architecture” (DIMA). The proposed methodology adapts the open-source Capella tool, based on the Architecture Analysis & Design Integrated Approach (ARCADIA) methodology, to implement a complete design cycle, starting with requirements captured from the aircraft level to streamline the development, culminating in the integration of an avionics application into an ARINC 653 platform. This paper shows how to address the variability of technology implementations at the aircraft and system levels and how the specification artifacts are efficiently managed and traced from the aircraft to the system to the item level to implement the SAE ARP4754A guidelines. The effectiveness of the methodology is presented via a case study of the…
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Multi-level Modeling Methodology for Aircraft Thermal Architecture Design

Concordia University Montreal-Florian Sanchez, Susan Liscouet-Hanke
Bombardier Aerospace-Yanik Boutin, Sebastien Beaulac, Stephane Dufresne
Published 2018-10-30 by SAE International in United States
This paper proposes a new methodology to conduct thermal analysis in the conceptual phase of the aircraft development process. Traditionally, thermal analysis is conducted after the system architecture has already been defined. The aircraft system thermal environment evaluation may lead to late design changes that can have a significant impact on the development process. To reduce the risk of late design changes, thermal requirements need to be defined and validated in the conceptual design phase. This research paper introduces a novel multi-level modeling strategy based on a bottom-up approach. It proposes an automatic geometrical simplification procedure for Computational Fluid Dynamic (CFD) analysis, a methodology for the generation of analytical correlations based on highly detailed methods, and a thermal risk assessment approach based on dimensionless numbers. This methodology generates models with the right level of fidelity to conceptual and preliminary design, offers the possibility to assess thermal risk, and defines thermal requirements for the selection of aircraft and systems architectures. A proof-of-concept of the methodology for a simplified test case is presented to highlight the benefits…
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Implementation of an Extended Model for Multi-Axle Articulated Vehicle with Nonlinear Tire Model

Concordia University Montreal-Bin Li
Hebei University of Engineering-Tianjun Zhu
Published 2017-03-28 by SAE International in United States
A new extended planar model for multi-axle articulated vehicle with nonlinear tire model is presented. This nonlinear multi-axle articulated vehicle model is specifically intended for improving the model performance in operating regimes where tire lateral force is near the point of saturation, and it has the potential to extend the specific axles model to any representative configuration of articulated vehicle model. At the same time, the extended nonlinear vehicle model can reduce the model's sensitivity to the tire cornering coefficients. Firstly, a nonlinear tire model is used in conjunction with the 6-axle planar articulated vehicle model to extend the ranges of the original linear model into the nonlinear regimes of operation. Secondly, the performance analysis of proposed nonlinear vehicle model is verified through the double lane change maneuver on different road adhesion coefficients using TruckSim software. Simulation results demonstrate that the proposed vehicle model shows high accuracy, which provides accurate simulation of the vehicle states on different road adhesion coefficient.
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Effects of Entrapped Gas within the Fluid on the Stiffness and Damping Characteristics of a Hydro-Pneumatic Suspension Strut

SAE International Journal of Commercial Vehicles

Concordia University Montreal-Yuming Yin, Subhash Rakheja
IRSST-P-E. Boileau
  • Journal Article
  • 2017-01-0411
Published 2017-03-28 by SAE International in United States
This study is aimed at characterizing the nonlinear stiffness and damping properties of a simple and low cost design of a hydro-pneumatic suspension (HPS) that permits entrapment of gas into the hydraulic fluid. The mixing of gas into the oil yields highly complex variations in the bulk modulus, density and viscosity of the hydraulic fluid, and the effective gas pressure, which are generally neglected. The pseudo-static and dynamic properties of the HPS strut were investigated experimentally and analytically. Laboratory tests were conducted to measure responses in terms of total force and fluid pressures within each chamber under harmonic excitations and nearly steady temperature. The measured data revealed gradual entrapment of gas in the hydraulic fluid until the mean pressure saturated at about 84% of the initial pressure, suggesting considerably reduced effective bulk modulus and density of the hydraulic fluid. An analytical model of the HPS strut was formulated considering polytropic change in the gas state and increased fluid compressibility due to entrapped air. Both the measured data and the model results showed progressively hardening stiffness…
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Yaw Stability Enhancement of Articulated Commercial Vehicles via Gain-Scheduling Optimal Control Approach

SAE International Journal of Commercial Vehicles

Concordia University Montreal-Bin Li, Subhash Rakheja
  • Journal Article
  • 2017-01-0437
Published 2017-03-28 by SAE International in United States
In this paper, a gain-scheduling optimal control approach is proposed to enhance yaw stability of articulated commercial vehicles through active braking of the proper wheel(s). For this purpose, an optimal feedback control is used to design a family of yaw moment controllers considering a broad range of vehicle velocities. The yaw moment controller is designed such that the instantaneous tractor yaw rate and articulation angle responses are forced to track the target values at each specific vehicle velocity. A gain scheduling mechanism is subsequently constructed via interpolations among the controllers. Furthermore, yaw moments derived from the proposed controller are realized by braking torque distribution among the appropriate wheels. The effectiveness of the proposed yaw stability control scheme is evaluated through software-in-the-loop (SIL) co-simulations involving Matlab/Simulink and TruckSim under lane change maneuvers. Simulation results demonstrate that the proposed gain scheduling optimal controllers can yield enhanced yaw stability of articulated commercial vehicles by the updating of control gains with the change of vehicle velocity.
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