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Training / Education
2014-12-04
Car companies and suppliers continue to develop new technologies that make vehicles safer and regulatory agencies continue to update safety regulations based on new research studies, making vehicle safety design more and more complex. This seminar covers the mechanics of frontal crashes and how vehicle structures, vehicle restraint systems, and vehicle interiors affect occupant safety. It also describes details of how CAE tools work in the simulation of frontal crashes. The goal of the course is to familiarize participants with engineering principles behind vehicle and restraint designs for occupant safety. Accident crash statistics, biomechanics, government regulations and public domain frontal safety tests will be reviewed briefly. Students will also be exposed to Madymo, one of the major occupant CAE tools. The basic inner workings of the tool, such as rigid body dynamics, joints, contact, airbag and seatbelt modeling, and modeling techniques will be shared with the class. The class also offers participants opportunities to do hands-on computer analysis as well as simplified hands-on crash tests, where students can learn first-hand how vehicle pulses and restraint design affect occupant response.
Event
2014-10-24
This presentation provides an overview of the current technological and market situation in the area of integrated safety systems. It will also include the Robert Bosch perspective as part of the overview. The presentation will address current and future challenges for passive and active safety systems and the strong link between integrated safety and automated driving. The concept will be further explained by means of concrete examples of integrated safety functions and their respective electrical architectures, functionalities, and safety benefits for vehicle automation up to and even beyond Level 2 systems as defined by NHTSA.
Event
2014-10-24
Event
2014-10-24
In any active safety system, it is desired to measure the “performance”. For the estimation case, generally a cost function like Mean-Square Error is used. For detection cases, the combination of Probability of Detection and Probability of False Alarm is used. Scenarios that would really expose performance measurement involve complex, dangerous and costly driving situations and are hard to recreate or even obtain. Using a virtual tool, we can produce the trials necessary to adequately determine the performance of active safety algorithms and systems. In this paper, we will outline the problem of measuring the performance of active safety algorithms or systems. We will then discuss the approach of using complex scenario design and Monte Carlo techniques to determine performance. We then follow with a brief discussion of Prescan and how it can help in this endeavor. Finally, two Monte Carlo type examples for particular active safety algorithms (LDW and AEB) will be presented.
Event
2014-10-24
The automotive industry is undergoing unprecedented change in the area of active safety and autonomous driving technology. The wide-scale development and implementation of advanced active safety technologies up to and including self-driving cars also raise many questions and bring new regulatory and product liability challenges to product designers and manufacturers. Examples of these questions include the follow: What is the state of regulation today applicable to this rapidly developing technology? What are the general views of the regulators about self driving cars? What is the consumer expectation? What happens when the system fails and reasonable actions by the driver/occupant could have prevented an accident? Who will consumers blame when accidents occur? Who will Courts hold liable when consumers file suit? How will this technology change current law applicable to automotive product liability? What challenges lie ahead for manufacturers that must defend their design decisions to juries by use of source code and other complex data?
Event
2014-10-24
Whether or not you like the idea of cars driving themselves, OEMs are adding increasing levels of automation to cars every year. These features improve safety and add driver convenience by offloading mundane tasks and managing information/task load. This step-by-step approach solves many problems but leads to technology fragmentation for OEMs and Tier 1s interested in a top down approach, which is a faster path toward revolutionizing mobility. Today every OEM and major Tier 1 has their own autonomous vehicle development program requiring investment on a massive scale. In addition, these companies end up duplicating much of the foundational work, even though that is not their key value add or differentiation.
Event
2014-10-24
Increasingly tough safety requirements are enormous challenges for the automotive industry. One way in which automobile manufacturers (OEMs) are responding is by implementing a growing number of advanced driver assistance systems. These help boost road safety and make motorists’ routine tasks easier. In the future, OEMs will increasingly introduce active safety functions in the different vehicles classes due to mandatory regulations at European level and stricter Euro NCAP criteria. From 2014 onwards, Euro NCAP ratings will include an assessment of lane support and autonomous emergency brake (AEB) systems for city (AEB City) and inter-urban (AEB Inter-Urban) use cases. Autonomous emergency braking with pedestrian and vulnerable road user detection (AEB Pedestrian, AEB VRU) will follow in 2016. For these active safety systems, Euro NCAP has defined or is defining distinct methods for real-world vehicle tests. This presentation introduces new technologies and tools for the verification of active safety and advanced driver assistance systems by means of model-in-the-loop (MIL), software-in-the-loop (SIL) and hardware-in-the-loop (HIL) simulation.
Event
2014-10-23
Event
2014-10-23
Event
2014-10-23
This presentation describes the development of test conditions and related equipment including an adult and child surrogate pedestrian target for test track evaluation of pedestrian Pre-Collision Systems (PCS). The test scenarios were developed using pedestrian crash data from NHTSA’s General Estimate System (GES), Fatality Analysis Reporting System (FARS), state data (Michigan) and analysis of 110-Car naturalistic driving data collected using video data recorders as part of this project. The 77GHz radar reflection characteristics of the pedestrian test targets were determined using radar scanning of 10 real people of different shapes and sizes including male, female and children. The shape and articulated motion of the surrogate pedestrian targets were determined from analysis of gait, knee angle and related measurements of real people. Finally the performance of two different Pedestrian PCS equipped vehicles were evaluated using the two surrogate pedestrian targets at test track testing.
Event
2014-10-23
Event
2014-10-23
Event
2014-10-23
Event
2014-10-23
This presentation discusses the methodologies of testing passenger vehicles to the NHTSA NCAP Advanced Technologies test program, which includes Lane Departure Warning (LDW), Forward Collision Warning (FCW), Crash Imminent Braking (CIB), Dynamic Brake Support (DBS) Systems, and Lane Keeping Support (LKS) tests. The presentation explains the test procedures developed by NHTSA as well as the pass / fail criteria, test equipment, and facilities required to conduct each test. Samples of actual test data are discussed, including an overview of data plots, photographs, and video footage.
Event
2014-10-23
Active safety systems hold great promise to help the vehicle safety community reduce crashes and crash severity. As these systems continue to be developed and offered on a wider range of vehicle models, we must consider not only what role they can play in contributing overall traffic safety, but also how the development and adoption of such technologies aids the auto industry in the development of autonomous vehicles.
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