During the information age, the motor vehicle has evolved from a simple mechanical device to a smart body of sensors that can measure different attributes, enhancing both vehicle safety and driver/passenger experience. Motor vehicles are now safer and smarter than they have ever been. However, our transportation system still suffers from major problems. The fast growth of metropolitan areas has been accompanied with an increasing influx of vehicular traffic to and from big cities. As a result, urban roads and highways are plagued by traffic congestions and road crashes, resulting in serious socio-economic problems. The latest report from the United States (U.S.) National Highway Traffic Safety Administration (NHTSA) has listed the annual casualties of motor vehicle crashes with a total of 32,999 fatalities and 3.9 million injuries on the roadways of the U.S., mounting the annual economical loss to $836 billion . Based upon NHTSA crash assessment report, the critical reason was assigned to the driver in an estimated 94% (±2.2%) of the crashes. The wide adoption of self-driving, autonomous vehicles promises to dramatically reduce the number of traffic accidents. Many hurdles still face the full deployment of self driving cars, from regulatory to technical issues. One of the major challenges, is public opinion. A recent survey has shown that 75% of people are very/moderately/slightly concerned about self-driving cars, which reflects the level of skepticism towards the technology . In this work, I try to answer the following question: can the automotive industry engage in a different conversation with the public such that it sways its perception of the technology to a more favorable one? To this end, I have developed a predictive model that predicts the public's favorability of self-driving cars. The model is based on self-driving car related twitter feed that were publised by verified accounts (which have the most influence on public opinion). Automotive industry and news agencies can evaluate the favorability of their self-driving related tweets before publishing them, and iterate them to a more favorable ones.
Help prepare and motivate the public for the coming self-driving cars
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