A recently-released study by the National Highway Traffic Safety Administration (NHTSA) finds that hybrid vehicles are more likely than conventional cars to hit pedestrians, especially while turning.
The study, conducted on 8,387 hybrids and 559,703 conventional vehicles with internal combustion engines, showed that the “incidence rate of pedestrian crashes in scenarios when vehicles make turns was significantly higher” for hybrids. It also concluded that hybrids were “two times more likely to be involved in a pedestrian crash” while slowing, stopping, backing up, and entering or leaving a parking space.
Advocates for the blind have long argued that hybrids are more dangerous than conventional vehicles because they are quieter. Earlier this year, the Japanese government set up a panel to study the idea of adding sounds to hybrid vehicles. Proposed sounds included artificial engine noises, music, or even ring tones, like those in cell phones. An informal study conducted by the Japanese Federation of the Blind also showed that more than half of blind pedestrians were “terrified” of hybrids.
In its accident analysis, NHTSA concluded that “a statistically significant effect was found due to engine type.”
Tesla Motors plans to roll out a “compelling, affordable electric car” that will sell for about half the price of its high-profile Model S by the end of 2016, company chairman Elon Musk said last week.
For industrial control applications, or even a simple assembly line, that machine can go almost 24/7 without a break. But what happens when the task is a little more complex? That’s where the “smart” machine would come in. The smart machine is one that has some simple (or complex in some cases) processing capability to be able to adapt to changing conditions. Such machines are suited for a host of applications, including automotive, aerospace, defense, medical, computers and electronics, telecommunications, consumer goods, and so on. This radio show will show what’s possible with smart machines, and what tradeoffs need to be made to implement such a solution.