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The negatives for self-driving cars are the following: 1) Just having the ability to operate a self-driving car would require an education on the driver's part. While the computer takes over once the vehicle is operational, the driver would still be required to maintain some knowledge about how to operate it safely. 2) The cost of implementing the new technology could be way out of reach for most Americans. Currently, the engineering, power and computer requirements, software, and sensors add up to more than $100K. 3) The most savings in terms of cost, time, and lives is going to come from when more people "opt in" to the service. If self-driving cars are not adopted widely, accidents can and will still happen. 4) In order for a computer to operate a vehicle, a lot of information would have to be stored on the software. Some individuals are concerned about the opportunity for a computer built into the self-driving car to collect personal data. 5) Self-driving cars would eliminate many jobs from auto manufacturing, freight transportation, taxi drivers, package and food delivery services, auto repair, hotels, media entertainment and online retail, insurance, legal professionals, law enforcement, real estate, and parking services, just to name a few. 6) A self-driving car doesn't completely eliminate the likelihood of a car accident. In fact, there's no legal precedent for how a case would be handled. The difficult question of who holds responsibility in a car accident, the driver? the car manufacturer? the software developer? etc. 7) The cars are not able to operate at a high level of safety in all weather conditions. In fact, heavy rain can do serious damage to the laser sensor calling into question what role the driver might have to play in the event the technology fails. 8) If other technology fails such as traffic signals that the cars rely on, there's no accounting for human traffic signals. 9) The reliance on technology could mean that over time, drivers are no longer equipped with the skills to operate cars. 10) It's unclear how self-driving cars would maneuver through hazards like roadblocks or unique local driving laws.

April 3, 2019

The positives for self-driving cars are the following: 1) In comparison to the myriad of bad behaviors a driver might exhibit behind the wheel, a computer is actually an ideal motorist. Since 81% of car crashes are the result of human error, computers would take a lot of danger out of the equation entirely. 2) There are no opportunities for a computer to be "distracted", which is a leading cause of accidents in the US at present since computers use complicated algorithms to determine appropriate stopping distance and distance from another vehicle. 3) It's obvious that human driven cars come at a very high cost in terms of danger. Therefore, there would be significant cost savings in many different venues like insurance costs and healthcare costs associated with accident recovery. 4) There is also a cost savings associated with time. When a computer takes over the driving responsibilities, drivers can use that time to do other things like catch up on reading or chat with passengers, all without having to worry too much about road safety. 5) Self-driving cars in large number participate in a behavior known as "platooning", which would significantly improve traffic conditions and congestion, and reduce commute times for drivers in high-traffic areas but also to maximize gasoline usage. 6) Disabled individuals who have to rely to public transportation or assistance from others to get around, could reap the benefits of self-driving cars with new freedom and enhanced mobility. 7) Larger cities are plagued with the problem of providing adequate public transportation. Many have a lack of appropriate infrastructure to support the needs of their residents, a void that could partially be filled by self-driving cars. 8) Drunk driving incidents should decrease because there's no designated driver needed when the car drives itself. 9) Massive savings could be recouped from being spent on older mass transit projects like trains. 10) Police officer focus could be shifted from writing traffic tickets and handling accidents to managing other more serious crimes.

April 2, 2019

Artificial Intelligence (AI) plays an integral role in the progression of self-driving vehicles on public roads. Each autonomous vehicle is outfitted with advanced tools to gather information, including long-range radar, LIDAR, cameras, short/medium-range radar, and ultrasound. Each of these technologies is used in different capacities, and each collects different information. However, this information is useless unless it is processed and some form of action is taken based on the gathered information. This is where AI comes into play and can be compared to the human brain, and the actual goal of AI is for a self-driving car to conduct in-depth learning. At its core, AI is a complex algorithm that mimics how the human brain learns. Instead of hard-coding an autonomous car with thousands of "If-Then" statements, software engineers create an algorithm that outlines to the car's onboard computers various examples of what is right, wrong, safe, and unsafe for the car to perform. The real power of this approach is realized because autonomous cars have one advantage that human drivers don't have; self-driving cars have the ability to share their experiences and readings with other cars instantaneously. This type of shared experience and active learning creates a situation where autonomous cars, through AI algorithms, can improve their ability to react to situations on the road without actually having to experience those situations first-hand. This means that not only does the future of autonomous cars depend on advanced AI algorithms, self-driving cars also rely on the standardization of that algorithm across all autonomous cars. Without this shared technology, we can't expect our society or policy makers to accept autonomous cars on public roads on a wide-scale.

April 1, 2019

There are three different types of hybrids and each works in a different way. 1) Parallel hybrid cars are the most common type of hybrid, and the Toyota Prius is the most widely known example. The car's wheels can be powered in three different ways: either directly by the engine, by the electric motor alone, or by both power sources working together. Whenever you decelerate or use the brakes, the regenerative braking system produces electricity and stores it in the battery for use later on. The battery is big enough that the electric motor can power the car for up to 1.25 miles. 2) Range extender hybrid cars only use their conventional engine to produce electricity for a generator that recharges the batteries. The engine never drive the car, it only produces energy for the electric motor. The BMW i3 with Ranger Extender is one of the most popular examples. These hybrids are also categorized as either strong or mild depending on the amount of battery power they have. With more battery capacity, strong hybrids can drive further than mild ones on electric power only. 3) Plug-in hybrids as the name implies can by plugged into an electric outlet to recharge their batteries, as well as being charged on the move. Effectively, they are a halfway house between conventional hybrids and full electric vehicles. Although they have a conventional engine, they also have larger batteries than regular hybrids and can drive longer distances on electric power alone - up to 30 miles in some cases.

March 22, 2019

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