199 research outputs found
Development of electric vehicle with advanced lighting system and all electric drive
Author name used in this publication: K. W. E. ChengAuthor name used in this publication: S. L. HoVersion of RecordPublishe
Design of The CRONE Automatic Headlight Leveling System
Automotive headlights system represents a safety key system when it comes to drive by night. It aims to increase the comfort of the driver by providing a clear visibility in order to anticipate obstacles and follow the right path. One of the main challenges that the lighting system is facing today is its automatic leveling adjustment. Variations of load of the vehicle, its dynamics and the environment are the main sources of disturbance to the leveling system. These disturbances causes variations of vehicle pitch angle and as a result the lighting cut-off level that may glare other road users and affect the driver's visibility range. This paper proposes an innovative automatic leveling system based on an ultrasonic motor which is able to dynamically reject such disturbances on the lighting cut-off level using a robust CRONE controller
Cooperative Collision Avoidance in a Connected Vehicle Environment
Connected vehicle (CV) technology is among the most heavily researched areas
in both the academia and industry. The vehicle to vehicle (V2V), vehicle to
infrastructure (V2I) and vehicle to pedestrian (V2P) communication capabilities
enable critical situational awareness. In some cases, these vehicle
communication safety capabilities can overcome the shortcomings of other sensor
safety capabilities because of external conditions such as 'No Line of Sight'
(NLOS) or very harsh weather conditions. Connected vehicles will help cities
and states reduce traffic congestion, improve fuel efficiency and improve the
safety of the vehicles and pedestrians. On the road, cars will be able to
communicate with one another, automatically transmitting data such as speed,
position, and direction, and send alerts to each other if a crash seems
imminent. The main focus of this paper is the implementation of Cooperative
Collision Avoidance (CCA) for connected vehicles. It leverages the Vehicle to
Everything (V2X) communication technology to create a real-time implementable
collision avoidance algorithm along with decision-making for a vehicle that
communicates with other vehicles. Four distinct collision risk environments are
simulated on a cost effective Connected Autonomous Vehicle (CAV) Hardware in
the Loop (HIL) simulator to test the overall algorithm in real-time with real
electronic control and communication hardware
Discrete-time Robust PD Controlled System with DOB/CDOB Compensation for High Speed Autonomous Vehicle Path Following
Autonomous vehicle path following performance is one of significant
consideration. This paper presents discrete time design of robust PD controlled
system with disturbance observer (DOB) and communication disturbance observer
(CDOB) compensation to enhance autonomous vehicle path following performance.
Although always implemented on digital devices, DOB and CDOB structure are
usually designed in continuous time in the literature and also in our previous
work. However, it requires high sampling rate for continuous-time design block
diagram to automatically convert to corresponding discrete-time controller
using rapid controller prototyping systems. In this paper, direct discrete time
design is carried out. Digital PD feedback controller is designed based on the
nominal plant using the proposed parameter space approach. Zero order hold
method is applied to discretize the nominal plant, DOB and CDOB structure in
continuous domain. Discrete time DOB is embedded into the steering to path
following error loop for model regulation in the presence of uncertainty in
vehicle parameters such as vehicle mass, vehicle speed and road-tire friction
coefficient and rejecting external disturbance like crosswind force. On the
other hand, time delay from CAN bus based sensor and actuator command
interfaces results in degradation of system performance since large negative
phase angles are added to the plant frequency response. Discrete time CDOB
compensated control system can be used for time delay compensation where the
accurate knowledge of delay time value is not necessary. A validated model of
our lab Ford Fusion hybrid automated driving research vehicle is used for the
simulation analysis while the vehicle is driving at high speed. Simulation
results successfully demonstrate the improvement of autonomous vehicle path
following performance with the proposed discrete time DOB and CDOB structure
Virtual and Real Data Populated Intersection Visualization and Testing Tool for V2X Application Development
The capability afforded by Vehicle-to-Vehicle communication improves
situational awareness and provides advantages for many of the traffic problems
caused by reduced visibility or No-Line-of-Sight situations, being useful for
both autonomous and non-autonomous driving. Additionally, with the traffic
light Signal Phase and Timing and Map Datainformation and other advisory
information provided with Vehicle-to-Infrastructure (V2I) communication,
outcomes which benefit the driver in the long run, such as reducing fuel
consumption with speed regulation or decreasing traffic congestion through
optimal speed advisories, providing red light violation warning messages and
intersection motion assist messages for collision-free intersection maneuvering
are all made possible. However, developing applications to obtain these
benefits requires an intensive development process within a lengthy testing
period. Understanding the intersection better is a large part of this
development process. Being able to see what information is broadcasted and how
this information translates into the real world would both benefit the
development of these highly useful applications and also ensure faster
evaluation, when presented visually, using an easy to use and interactive tool.
Moreover, recordings of this broadcasted information can be modified and used
for repeated testing. Modification of the data makes it flexible and allows us
to use it for a variety of testing scenarios at a virtually populated
intersection. Based on this premise, this paper presents and demonstrates
visualization tools to project SPaT, MAP and Basic Safety Message information
into easy to read real-world based graphs. Also, it provides information about
the modification of the real-world data to allow creation of a virtually
populated intersection, along with the capability to also inject virtual
vehicles at this intersection
Customized Co-Simulation Environment for Autonomous Driving Algorithm Development and Evaluation
Increasing the implemented SAE level of autonomy in road vehicles requires
extensive simulations and verifications in a realistic simulation environment
before proving ground and public road testing. The level of detail in the
simulation environment helps ensure the safety of a real-world implementation
and reduces algorithm development cost by allowing developers to complete most
of the validation in the simulation environment. Considering sensors like
camera, LIDAR, radar, and V2X used in autonomous vehicles, it is essential to
create a simulation environment that can provide these sensor simulations as
realistically as possible. While sensor simulations are of crucial importance
for perception algorithm development, the simulation environment will be
incomplete for the simulation of holistic AV operation without being
complemented by a realistic vehicle dynamic model and traffic cosimulation.
Therefore, this paper investigates existing simulation environments, identifies
use case scenarios, and creates a cosimulation environment to satisfy the
simulation requirements for autonomous driving function development using the
Carla simulator based on the Unreal game engine for the environment, Sumo or
Vissim for traffic co-simulation, Carsim or Matlab, Simulink for vehicle
dynamics co-simulation and Autoware or the author or user routines for
autonomous driving algorithm co-simulation. As a result of this work, a
model-based vehicle dynamics simulation with realistic sensor simulation and
traffic simulation is presented. A sensor fusion methodology is implemented in
the created simulation environment as a use case scenario. The results of this
work will be a valuable resource for researchers who need a comprehensive
co-simulation environment to develop connected and autonomous driving
algorithms
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