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In 2017, Husch and Teigen explained that leaving room in between vehicles for drivers to enter and exit the freeway would allow traffic to flow freely at any pace. A consensus by Husch and Teigen (2017) asked drivers to consider leaving room between cars to improve traffic flow. The results of the study suggest the driving technique would fail because other drivers would close the gap. Autonomous vehicles can be programmed to keep a specific distance from other vehicles eliminating traffic jams. Shi, Chen, and Li, (2017) state that traffic capacity on any route increases when the greater number of cars operated are autonomous. An increase in autonomous vehicles on the road by 10-50% will double the speed of traffic and improve the flow of traffic on highways, intersections, and multiple lanes as well as completely eliminate breaking events. Traffic is caused and amplified solely by humans, never car defects or manufacturing errors. Autonomous vehicles utilize adaptive cruise control which stabilizes traffic by syncing traveling speeds which can end traffic completely. A study conducted by the National Science Foundation demonstrates how having one autonomous vehicle on the road can mitigate the congestion of at least 20 manual vehicles around it (Stilgoe, 2018). The NSF rented 20 manually operated cars and one autonomous car of different makes and models and placed them on a circular track. When all of the cars were driven manually around the track, there was stop-and-go traffic and the cars traveled at inconsistent speeds. When the autonomous car was activated, the stop-and-go traffic ceased and the cars speed stabilized. Nassim (2018) conducted a similar study with the University of Illinois. The study found that the presence of a single autonomous vehicle can reduce the number of hits to the brakes by nine per vehicle for every 1 to 2.5 kilometers traveled. One autonomous vehicle can also lower the standard deviation in the speed of the cars stuck in traffic by 50%.
Safety benefits.
Human error leads to car accidents in multiple scenarios such as driving under the influence, speeding, inexperience, and over-compensation. An accident caused by an autonomous vehicle would result from a harmful miscalculation by the car sensors and connectivity. Because there is only one factor for potential accidents caused by autonomous cars, accidents would decrease dramatically. 30,800 deadly accidents occurred in 2012 killing 22,912 drivers and passengers, 4,743 pedestrians, 273 bicyclists and 4,957 motorcyclists. Having as little as 10% of autonomous vehicles on the road, up to 211,000 accidents would be prevented and 1,100 lives would be saved annually (Frielink, Schuengel, & Embregts, 2018). With the slim chance of an accident occurring with an AV, if there were 10,000 deaths annually due to AV which is an obscure number, at least 20,000 lives would still be saved. The NHTSA specifies that autonomous vehicles can reach full automation where the vehicle can exceed a human’s capabilities in every driving condition. The radars built into autonomous vehicles can see through objects and create real time perspectives that humans cannot. In addition to expanded visibility, autonomous vehicles can react faster than humans (Fleetwood, 2017). Petrilli (2014) stated that the truck accident rate could drop to eight crashes per 100 million miles from 222 accidents with autonomous vehicles. Autonomous vehicles also successfully multitask unlike humans. Autonomous vehicles are always looking for pedestrians, measuring surroundings and interpreting data at the same time. While it is possible for a driver to be completely conscious and alert, humans do not have the same ability as self-driving cars in terms of their sensors, connectivity, and control algorithms that never lose vigilance.

Cost benefits.
According to the Department of Transportation, the human life is worth $9.2 billion dollars. With a decrease in fatal accidents by AV, there is the potential for $276 billion dollars to be saved annually. In 2013, The Center for Disease Control and Prevention estimated the medical and work loss costs to be $44 billion as a result of crash deaths (Stilgoe, 2017). The costs for car accidents not including the accidents that do not cause harm to the passengers totals $317 billion yearly. Using AV would save a drastic amount of lives and money annually for millions of drivers. Goodall (2017) claims that businesses will be able to profit off of autonomous vehicles. Companies can offer rides for customers and greater options for deliveries. Businesses beyond the food industry, like Amazon, will be able to utilize autonomous vehicles launching mobile office space, libraries, and more. The car to car communication systems integrated in AV reduce fuel consumption greatly. AV are programmed to eliminate hard braking and abrupt accelerating that require more gas than gradually speeding up or slowing down. AV also sync the driving speeds and patterns of the vehicles surrounding them whether they are autonomous or not saving fuel for any type of vehicle. 40% of fuel can be saved across vehicles in a traffic jam when stop-and-go traffic is eliminated. The sensors that enable AV to anticipate other car’s actions and operate at a continuous engine speed consumes less fuel than human drivers making self-driving cars more cost-friendly (Goodall, 2017). With a decrease in traffic congestion, billions of gallons of gas would be preserved. Passengers would also save a substantial amount of money on insurance rates as AV shift liability from drivers to the manufacturer of the vehicle or the software driving the vehicle (Bogue, 2018).

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