The technology used in the Google car will increase safety in transport by reducing the number of car accidents. As of 2013, Google had accumulated more than 500,000 miles of autonomous vehicle driving on public roads without causing any accidents (RAND Corporation, 2015). This record is important in demonstrating the safety associated with autonomous vehicles. The available statistics on car accidents have proven that people are poor at driving and many accidents can be associated with erroneous decisions by drivers. In 2011, there were 32,000 road fatalities in the US and about two-thirds of these fatalities were associated with human error while other statistics associated over 90% of accidents with poor decision making (RAND Corporation, 2015). These statistics means that if cars can drive themselves well, then the number of road accident fatalities can be reduced by more than two-thirds. The current developments show that it is possible to realize well-driven vehicles within few years. Some of the existing autonomous vehicle models can park themselves, stay in designated lanes, evade obstacles, brake and warn drivers of emergencies. As the technology improves, the autonomous vehicles will be able to eliminate most of the human errors that result in car accidents. The common sources of human errors in driving are distractions and lack of enough awareness about the surroundings. A human driver can miss a road sign as a result of distraction from a phone and other personal issues. Also, the human senses are limited in recording and analyzing a lot of details at once. The autonomous vehicles include sophisticated sensors that can keep track of every aspect on the road and the condition of the vehicle at all times.
The technology operates based on the specifications from the vehicle manufacturer and thus there are no chances of distractions while the car is driving. The technology used in Google cars can complement some human weaknesses in road driving. Human weaknesses in driving vehicles include poor eyesight and lack of enough experiences to handle a car. The sensors in automated vehicles make it possible for people with poor visibility to drive safely by scanning the surrounding environment on their behalf. Accidents caused by inexperienced drivers will reduce with automated driving. New human drivers easily cause accidents during routine operations like reversing and when driving in narrow pathways. The existing technologies are able to provide assistance to drivers by performing certain functions like monitoring the condition of the pathway on behalf of the driver. Basically, the automated vehicles reduce the need for people to have driving experience in order to drive safely. According to Google, the driving capability of an automated car is equivalent to over 90 years of driving experience in a typical adult in the US (Google, 2015). This capability means that the car is able to navigate complex and rare scenarios that can prove challenging to most of the existing drivers and the navigation of the vehicle is predictable on the road. For example, the technology considers the risk of careless pedestrians entering the road at random and includes a predefined procedure on how to handle such a scenario (Google, 2015). A human driver may face challenges responding to such a situation because of the high response speed required to make an informed driving decision. Also, it means that the average level of experience in driving will be higher among all vehicles on roads and thus reduce the chances of accidents that are caused by inexperience.
Automated vehicles will facilitate easier traffic flow on roads through accommodation of more vehicles on roads, reduction of traffic snarl up caused by poor human decisions and ability to serve many people throughout the day (Wolverton, 2016). Road congestion is already a major issue, especially in urban areas. Motorists in large cities are forced to spend a significant part of their time in traffic jams or looking for parking spaces near their working areas. The sensors in automated vehicles allow them to drive closely to each other without causing accidents. By allowing vehicles to drive close to each other, more vehicles will be accommodated in the existing road infrastructure and still facilitate the smooth flow of traffic. Human drivers overreact to other cars when changing lanes or slowing, and are also unpredictable in their navigation. The sensors in automated vehicles are able to synchronize the decision making by vehicles at close proximity and thus facilitate the smooth flow of traffic when vehicles are changing lanes or braking. Automated vehicles provide a chance for social ownership of vehicles in providing personalized services to motorists and therefore reduce the need for driving a personal vehicle in congested urban areas (Wolverton, 2016). Personalized transit systems are already in small-scale applications through services like Uber taxis, where people can easily request for a vehicle to a given destination through technology. Modern urban planners envision a road transport system where vehicles can pick up passengers, drop them at their destinations and move on to provide services to other people throughout the day (RAND Corporation, 2015). The current road transport system is mainly characterized by people driving their vehicles to their destination and them parking the vehicles until their time of departure. This system creates congestion as well and the need for physical space for parking in urban areas. It is estimated that private cars spend about 95% of their time parked, and that automated vehicles can reduce the need for parking space in the US by more than 5.7 billion square miles (Schwartz, 2015). Ease of traffic flow is associated with the improved safety of automated vehicles. Car accidents on roads contribute to traffic snarl-ups during rescue missions to remove wreckage or reconcile those involved in accidents. As the technology reduces the number of accidents, the issues that contribute to traffic congestion will reduce in road transport.
Self-driven cars will reduce the employment opportunities in transport and related industries. Job loss is mainly associated with the need by corporations to replace drivers with autonomous vehicles. Self-driving vehicles offer various incentives for large corporations to reduce the number of drivers operating their vehicles. These incentives include reductions in labor costs, employment benefits and employees’ compensation claims (Mui, 2013). Self-driving vehicles represent low labor costs to corporations, and this will affect the decisions to employ drivers to operate vehicles instead of acquiring self driving vehicles. The self driving car technology is cost effective to corporations as it offers certain efficiencies over drivers. Drivers are susceptible to fatigue and thus, can only work for a given number of hours every day. The large companies involved in transport and logistics are forced to employ more than one driver per vehicle because of human limitations to work throughout the day. The Google car technology eliminates these inefficiencies in business operations because the vehicle can be used for longer hours each day without the risk of fatigue and requirements for additional working hours for drivers. Basically, additional working hours is associated with added operation costs to businesses in terms of overpayments and compensations to employees. The contribution of self driving vehicles to increased unemployment is also associated with its safety standards. Because of the improved safety, there will be loss of jobs in sectors associated with auto parts manufacturing, insurance, collision repair shops and tow-truck operators (Mui, 2013). These economic sectors have developed as a result of inefficiencies with human drivers that lead to accidents and frequent damages to vehicles. As earlier stated, the automated driving technology will significantly reduce the number of accidents that cause damages to vehicles and injuries and loss of life to people. Currently, many people and businesses depend on these inefficiencies in repair work, servicing, and other related issues. For example, the collision repair shops will be forced to downsize their operations because of reduced number of accidents, and therefore affect the number of people employed in that business. The need for insurance coverage will be low, and thus the insurance companies will be forced to charge low premiums for their services to vehicle owners. Basically, the automated vehicles will affect all businesses that are directly associated with road transportation in a certain way. Loss of job as a result of new technologies has been proven in other economic activities in the past. For instance, the introduction of self-service Laundromats and washing machines affected the livelihood of many immigrants in the US in the 1970s, because they depended on providing laundry to residents as a form of employment (Mui, 2013). These innovations that are associated with low costs of operations and more efficiency are preferable to human labor. If corporations adopt the self-driving cars, a large number of people working as truck drivers, delivery people, and taxi drivers will lose their jobs. It will be cost effective for a company to buy a self-driven truck for delivery of goods instead of buying a conventional truck and then employing drivers for its operation.
In conclusion, it is clear that the Google car will have impacts on road safety, traffic flow and employment in the society. The technologies used in self driven vehicles take into consideration all issues that are associated with car accidents among drivers. The ongoing testing shows that the Google car can considerably reduce road accidents by eliminating human errors and dealing with challenges in driving. The technology will facilitate smooth flow of traffic by avoiding accidents that cause traffic snarl up, accommodating more vehicles on roads and reducing the need for personal parking in urban areas. However, the Google car is also a disruptive technology because of its likelihood to create unemployment. The technology offers a cheap and efficient way of providing road transport services and corporations may decide to buy the self driving vehicles in order to avoid the costs associated with human drivers. Apart from the direct impact on driving jobs, there are certain businesses that are already in place and which depend on inefficiencies of human driving. Massive adoption of self-driven vehicles will affect the employment opportunities offered by these related business in future. Although Google car may lead to job losses, road accidents, and traffic congestion are associated with higher costs to individuals and the economy.
Google. (2015). Google Self-Driving Car Project: Monthly Report. Retrieved 1 March 2016 from https://static.googleusercontent.com/media/www.google.com/en//selfdrivingcar/files/reports/report-0915.pdf
Mui, C. (2013). Will Driverless Cars Force A Choice Between Lives And Jobs? Forbes. Retrieved 1 March 2016 from http://www.forbes.com/sites/chunkamui/2013/12/19/will-the-google-car-force-a-choice-between-lives-and-jobs/#30b0c653546e
RAND Corporation. (2015). The dream drive. Retrieved 1 March 2016 from http://www.rand.org/blog/rand-review/2015/01/the-dream-drive.html
Schwartz, D. (2015). Self-driving cars confront urban traffic congestion. CBC News. Retrieved 1 March 2016 from http://www.cbc.ca/news/technology/self-driving-cars-confront-urban-traffic-congestion-1.3155811
Wolverton, T. (2016). Self-driving cars promise a ‘revolution,’ but not necessarily a positive one. San Jose Mercury News. Retrieved 1 March 2016 from http://phys.org/news/2016-02-self-driving-cars-revolution-necessarily-positive.html