AUTONOMOUS DRIVING CARS
Driverless cars, 1, train their artificial intelligence (AI) based on neuronal networks in test environments. In this context, it has become evident that the vehicles are prone to errors – errors that were partially difficult to understand and trace and that are extremely problematic because wrong decisions of self-driving cars can ultimately put human life at risk. The AI issues revolving around driverless cars, however, also present additional ethical issues.
How would we deal with the case in which the AI-based software of a driverless car has to decide – in the event of an unavoidable accident – between several evasive manoeuvres, which may incur grave consequences? Should it swerve to the right into a group of pedestrians, or veer to the left onto the opposite lane with heavy traffic? Unfortunately, this scenario is just as difficult for a programmer of AI systems to decide, as it would be for any one of us. What has to be considered from an ethical viewpoint when dealing with AI issues? How can the chances be increased, or how can it be guaranteed that AI-based machines as well as driverless cars make the best decision in the case of doubt? How can potential sources of errors be correctly recognised and prevented?
ARTIFICIAL INTELLIGENCE METHODS
The majority of AI applications for the mass market are extensions of human activity. The applications are very heterogeneous and seemingly inexhaustible: while AI can be used to merely optimise an image, for instance, it can also perform more sophisticated tasks. Take the example of estimating the time required to arrive at a certain place, or AI informing the vehicle owner when maintenance is required. Ultimately, AI can perform very complex tasks such as driving a car.
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Sound Generation For Enhanced Road Safety
With an ever-increasing number of fully electric and hybrid vehicles entering the market, we are witnessing a change in the acoustic experience in and around the car. The silent nature of the electric powertrain means that other road users miss the familiar acoustic cues that warn them of an approaching vehicle. To remedy this situation, Harman is working on various noise management solutions.
OBJECTIVE ASSESSMENT OF THE SAFETY CONTRIBUTION OF TODAY'S AUTOMOTIVE HEADLAMPS
Good lighting makes a major contribution to road safety. In 2011, the International Commission on Illumination (CIE) presented an evaluation system for headlamps that can objectively assess the quality of illumination and glare limitation. New light sources like LEDs and lighting functions (glare-free high beam, partial high beam) have been available for several years, so that an extension of the proven CIE method is necessary, which takes into account, among other things, changed switch-on and service lives of new lighting functions and represents a generally understandable evaluation system. An evaluation system presented in the following by the Technische Uni versität Darmstadt, which was developed by an encompassing expert commission, is intended to provide representative data and enable an objective evaluation of headlamp performance.
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NISSAN'S NEW DIRECTION: ARIYA ALL-ELECTRIC
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BETTER SAFETY WITH EMERGENCY BRAKE ASSIST FOR MOTORCYCLES
Rear-end collisions with a slower vehicle suddenly cutting into the lane and intersection accidents with cross-traffic are among the most frequent motorcycle accident types. Continental is now developing an emergency brake assist, which detects an imminent collision with a vehicle ahead or with an obstacle, warns the rider and supports him during braking
ADAS WILL SERVE AS CATALYST FOR IMPROVED VEHICLE SAFETY
The automotive industry across the globe is increasingly focussing on safety.
