About self-driving cars

Deadline is approaching?

Wait no more. Let us write you an essay from scratch

Receive Paper In 3 Hours

The arrival of self-driving cars, also known as self-driving or non-driving machines, appears to be upon us, and yes, engineers have been playing with self-driving cars for the last few decades (Zakharenko, 2016). Self-driving vehicles are built to feel their sorroundings and navigate safely without human interference. Research reveals that 90% of car crashes are caused by mistakes committed by drivers, such as using cell phones while driving or driving under the influence of drugs or alcohol (Robertson et al., 2017). Over the past two decades, vehicle manufacturers have designed new and increasingly sophisticated features that provide more assistance to drivers to help mitigate such errors (Robertson et al., 2017). Features such as driver lane assists, blind spot monitors, speed monitors, and lane watch are all early forms of the autonomous vehicle innovation. Such features are essential precursors of semi- or fully-automated vehicles and will dramatically reduce road crashes.

The idea of autonomous cars goes back to General Motor’s vision for the future of transportation at the 1939 New York World’s fair (Gogoll & Muller, 2016). In, recent year’s autonomous car research has experienced an unprecedented uptake. Due to advancements in technology, autonomous cars are now within our reach (Gogoll & Muller, 2016). Big automobile manufacturing companies such as BMW, Mercedes, Ford, GM, and Toyota, as well as leading tech companies such as Google and Apple, back the idea of the autonomous driving (Zakharenko, 2016). The first autonomous pods were introduced to public roads in the Netherlands, while the Japanese government launched an experiment with an unmanned taxi service in 2016 (Gogoll & Muller, 2016).

Of course, not all autonomous vehicles operate the same way, and there continues to be a continuum of different types of vehicle automation. According to The US National Highway Traffic Safety Administration, automated vehicles can be distinguished at five levels. Level 0 indicates that they do not have any of their control systems, computerized, while levels 1 and 2 are cars in which the human driver is still mainly in control, though some features may be automated. Levels 3 and 4 are cars that are fully automated such that a human driver can cede full control of the vehicle (Gogoll & Muller, 2016). An example is the Tesla Vehicle Autopilot feature which has the capability of both being fully automated while still being able to be driven.

Avoiding obstacles, such as other automobiles, pedestrians, curbs, and bicycles, is an essential component of autonomous driving. Autonomous cars use a variety of techniques to detect their surroundings, such as lidar, radar, laser light, GPS, odometer, and computer vision (Surden & Williams, 2016). The lidar system, which is mounted on the roof of the vehicle and rapidly rotates 360-degrees, enables autonomous cars to detect obstacles around them (Surden & Williams, 2016). The placement of the lidar on the roof and its rapid rotation allows it to identify objects on all sides of the vehicle. These include those behind the car, at a rate of up to one million readings per second (Surden & Williams, 2016), using lasers which allow them to be precise in their location determinations of objects.

In addition to lidar, radar is used to detect the position and speed of surrounding objects. Radar detectors have a few advantages over lidar in specific positioning tasks as radar has a more extended range of up to several hundred meters or more (Surden & William, 2016). More importantly, radar is used in assessing the speed of multiple moving objects, such as nearby vehicles, in real time (Bajpayee & Mathur, 2015). A significant disadvantage of radar compared to lidar is its precision, which can be off by several inches to feet in detecting the location of stationary obstacles. To compensate for the advantages and disadvantages of both, autonomous vehicles often use information from radar and lidar in parallel to gain different sources of information about the location of obstacles (Surden & William, 2016).

An array of sensors, powered and controlled by sophisticated algorithms and powerful software, is also used to aid the vehicle during navigation. In simple terms, the sensors fall into three broad categories: navigation and guidance; driving and safety; performance and control. Furthermore, many autonomous vehicles also use video cameras to detect the location and speed of nearby obstacles. Video cameras are spaced around the vehicle at known distances, which allow the vehicle’s computer to receive parallel images of the same objects from slightly different angles (Surden & Williams, 2016). The video cameras are used to read words on traffic signs or determine whether a traffic signal is green. Visual cues play an essential role in driving, and video cameras can capture information, such as color or language, that the other sensors such as lidar or radar may not be well suited to retrieve (Surden & Williams, 2016).

A prime example of a fully functioning self-driving / fully autonomous vehicle is the Tesla Model S/X. Manufactured by an American multinational corporation with the same name; Tesla is the most consumer-friendly car manufacturer of autonomous cars. In a recent marketing video posted by Tesla CEO Elon Musk on the social media platform Twitter, the ‘eyes’ of the machine (Tesla Model X) are depicted, and viewers are shown a visual representation of what the vehicle sees and how the vehicle can sense its environment and navigate the foreign terrain. The system can detect lane lines, successfully and safely perform a lane change, identify pedestrians and also identify city speed signs and adjust speeds accordingly. At the end of the video, viewers are shown a new technology based on artificial intelligence whereby the vehicle can predict and avoid a potential collision. In the video, it is explained that the vehicle was able to achieve this by observing variables such as the speed of the car ahead of it, pattern changes of the driver in front of it and the reactions of other vehicles around it. It was able to combine all of these variables and make a precise decision of how to safely steer away from a collision with the least possible outcome for error.

Since autonomous cars are relatively new technology, and their development is fostered mainly by automotive companies and engineers, much of the current debate revolves around the question of liability (Gogoll & Muller, 2016). Favorable ethical arguments for the introduction of the autonomous car have been made on environmental grounds. The optimization of acceleration profiles enabled by automation will allow energy usage to be optimized leading to reduced pollution and emissions (Diels & Jelte, 2016). With the increase in the aging population, automated vehicles could also improve mobility for those unable or unwilling to take the wheel. Also, self-driving vehicles may make traveling by car more productive and comfortable. The driver now becomes the passenger and can engage in non-driving activities, sit back and relax, read a newspaper, check emails or have conversations face to face with rear passengers (Diels & Jelte, 2016). As the vast majority of accidents can be attributed to human error, self-driving cars may reduce or eliminate driver error which could lead to safer roads (Diels & Jelte, 2016). It will also allow for more efficient road use with vehicles able to safely drive closer together, thereby using fewer roads, and reducing congestion and journey times (Diels & Jelte, 2016).

Though it may come across as an oxymoron, as with any incipient technological advancement, we must also understand the ethical issues regarding self-driving cars. Our focus will be on the sequence of steps that the system undergoes in the process of acting. Autonomous vehicles have not achieved complex singularity or consciousness; therefore, their actions are based on pre-programmed algorithms written by humans. Thus, following this algorithm, self-driving cars should follow ethical rules. Self-driving cars are already able to make decisions that have ethical consequences. As such machines make increasingly complex and important decisions, we will need to know that their choices are trustworthy and ethically justified. Hence, we will need them to be able to explain the reasons for these decisions.

Despite the various benefits associated with self-driving cars, there is a horde of the drawbacks related to their use. One of these is the ability of the vehicle to be hacked. Self-driven cars are purely dependent on latest technology. According to Eddie Schwartz, the vice president of the global solutions in the Verizon Enterprise subsidiary, the issue of cybersecurity is still half a century from maturity. He notes that the first half of the 21st century would see a large number of targets increase exponentially (Bansal & Kockelman, 2016). On August 2017, researchers demonstrated attacks of a Toyota Prius and Ford SUV allowing them to jerk the steering wheel, slam on brakes, or accelerate the car using a computer (laptop) which had been plugged into the diagnostic port.

In 2011, a team of researchers was able to penetrate the vehicles’ system using Bluetooth, mobile phone and moreover a malicious audio file which had been burned onto a CD and played within the vehicles media player. Hacking is one of the leading challenges that modern techno-savvy individuals encounter (Moon Lee, 2016). A vehicle that has been hacked is hazardous as the person responsible might decide to ram it into other cars, a group of pedestrians or even into a shopping mall. Assume a situation where a vehicle has been hacked, and it passes through a police checkpoint. What will the traffic police do? Even if they shoot at it will continue moving as directed by the hacker. This is more dangerous than when the robbers have hijacked it.

The second disadvantage of self-driven cars is that they entirely depend on the effectiveness of the sensor attached to car’s roof. If the sensors get damaged, it can be devastating to the operation of the car (Moon Lee, 2016). For instance, heavy rain may cause a malfunction of the sensor disabling it from assessing the conditions on the roads. This will prevent the car from proper navigation through the traffic, and the probability of the car having an accident is increased. Moreover, a change in the location of the road signs may hinder the sensors from detecting them and hence cause misdirection of the vehicle.

The cost of the driverless technology on these vehicles is a challenge both to the manufacturers and the possible buyers. It has been established that the engineering, the power and the computer requirements, sensors and the software could add to more than $100,000. This is absurd to most people. They cannot afford such vehicles. This will make the production of such vehicles to be affected negatively. According to the data from the National Automobile Dealers Association, an average American can only afford to spend $ 20, 806 on a car. Thus, it would be tough for such a person to buy a Toyota Prius, which is estimated to cost around $ 320, 000 (more than a Ferrari 599).

Self-driving cars create a legal issue since there is no legal precedent on how a case would be handled. The big question remains on who holds the responsibility when the car is involved in an accident. The software developer? The car manufacturer? The driver? This results in a blame game which is somehow tricky. Mostly, self-driven cars operate on the assumption that everyone else on the road is a law-abiding citizen and will follow the set guidelines. The vehicle is not equipped with instructions on how it can maneuver through hazardous situations. If example an oncoming vehicle skids off to the wrong lane, the self-driven car may not efficiently react to that situation. This is because they lack the moral ability to make the right decisions on the roads.

Self-driven cars rely purely on accurate mapping systems through the GPS. If a wrong mapping has been done, it leads to a security concern to the owner and the state at large. GPS devices are not always accurate, and hence wrong directions can be fed onto the vehicles. Agil Juliussen, Director of research for infotainment and advanced driver assistance at HIS Automotive says that the electronic systems in the modern cars contain insufficient security measures. Adoption of the self-driven vehicles has led to a debate on the effects on the economy of the nation. If such technology is used in the transportation sector, it could have an adverse impact on the job creation sector (Bansal & Kockelman, 2016). Data released in 2014 indicated that more than thirteen million Americans work in the transportation sector, accounting for about 4.6 percent of the total labor force. Adoption of such technology means that more than half of these individuals will be rendered jobless. This is disastrous to the employment sector within American alone.

A failure in other technologies will typically affect the functioning of self-driven cars. Failure of traffic signs may result in accidents since these cars do not account for human traffic signals. For example, in a situation where a traffic officer is directing vehicles in a crowded street, the self-driven cars will be unable to interpret the human signals. Privacy is another issue that can prevent people from buying the self-driven cars (Moon Lee, 2016). This is because for the computer to operate the vehicle, a lot of information would have to be stored on the software of the vehicle. People who love their privacy will not acquire such a vehicle for fear of the machine collecting personal data.

Most vehicle owning individuals enjoy the act of being in control of the movement of their cars. Research done by the National Automobile Dealers Association showed that people enjoy driving their vehicles, even if they can afford a personal driver (Moon Lee, 2016). They would not hence acquire self-driven cars as it is a distraction from their enjoyment of being in control of the movement of their vehicles. They would prefer a standard car as opposed to the self-driven cars.

Self-driven cars may also make people become ignorant of learning the driving ways. They would not see the benefit of a knowing how to drive as the vehicles will be self-driven. Instead of investing in driving education, they would spend the money in other ways (Bansal & Kockelman, 2016). One of the significant questions that continue to linger in people’s minds is; what would happen if such technology fails in the future and people are illiterate in the driving sectors? This would be devastating effects in the transport industry.

Although the issue of self-driving vehicles has received mixed reactions, the driverless car is coming. The companies that are developing these vehicles consider such challenges as being, ’normal and expected’ (Moon Lee, 2016). As John Krafcik, CEO of Waymo, notes, these are some of the challenges that manufacturers encountered during the introduction of the electric trains. Kraficik, however, notes that several issues need to be addressed to ensure that the self-driving vehicles meet the buyers’ requirements.

The recently launched Google self-driving car confirmed many people’s thoughts; self-driving cars are real. Since the introduction of Waymo vehicle, the company has been able to establish its position as the leading entity in the self-driving technology (Wieczorek, 2017). In fact, Fiat Chrysler Automobiles have confirmed that they will provide 500 Pacific plug-in hybrid cars that are to be used in the Arizona project. Waymo has also invited Phoenix resident to join the trial for testing the self-driven vehicles (Wieczorek, 2017). The individuals who have been chosen are from diverse backgrounds and have different transportation needs. They have to give feedback on their experience, which will enable Waymo to modify the vehicles with their requirements.

Adoption of self-driving technology in vehicles will require the combined efforts among the many sectors in the transport industry. The manufacturers will have to make a car that incorporates the modern technology within it (Wieczorek, 2017). A vehicle that will enable users to install the latest technology and not cause any malfunction within it. The software developers will have to develop software that will be convenient to the users (Wieczorek, 2017). Moreover, the technology should not interfere with the functioning of the vehicle but should make it more advanced. They should also consider the privacy-conscious individuals.

The security factor should also be a significant consideration by the developers. If all the security features are enhanced, many people will embrace the idea, and hence it will be successful. For instance, if a system which is difficult to hack is used, I believe the project will be a very successful one (Wieczorek, 2017). The government should, on the other hand, ensure that road components have been developed and ensure that they are up-to-date. For instance, the roads should be in excellent condition. The road signals should be effective so that they will not mislead the vehicles (Moon Lee, 2016). A damaged road sign should be repaired quickly and any changes within the transport industry to be communicated to the road users.

When all these aspects are adhered to, the future of the self-driving cars will be guaranteed to be smooth and successful. No new technology lacks its share of challenges; hence manufacturers should not be cowered by hindrances to this technology (Wieczorek, 2017). Self-driving technology is not a futuristic idea; it is here with us.

References

Bajpayee, D., Mathur, J. (2015). A comparative study of the autonomous vehicle.

Retrieved from http://ieeexplore.iee.org.proxy.bib.uottawa.ca

Bansal, P., & Kockelman, K. (2016). Are we ready to embrace connected and self-driving vehicles? A case study of Texans. Transportation.

Retrieved from http://dx.doi.org/10.1007/s11116-016-9745-z

Diels, C., Jelte, E. B. (2016). Self-driving carsickness. Applied Ergonomics, 53.

Retrieved from http://doi.org/10.1016/j.apergo.2015.09.009

Gogoll, J., Muller, J. F. (2016). Autonomous cars: in favor of a mandatory ethics setting. Science and Engineering Ethics, 23(3), 681-700.

Retrieved from http://doi-org.proxy.bib.uottawa.ca/10.1007/511948-016-9806-x

Moon Lee, J. (2016). A Design of Road Database for Self-Driving Vehicles. Indian Journal of Science and Technology, 9 (20). http://dx.doi.org/10.17485/ijst/2016/v9i20/94704

Robertson, D. R., Meister, S. R., Vanlaar, W. G. M., Hing, M. M. (2017). Automated vehicles and behavioral adaptation in Canada. Transportation Research Part A: Policy and Practice, 104, 50-57.

Retrieved from http://doi.org/10.1016/j.tra.2017.08.005

Surden, H., William, M. A. (2016). Technological opacity, predictability, and self-driving cars. Cardozo Law Reviews, 38(1), 121.

Retrieved from http://fc3yq3bj4d.search.serialssolutions.com

Wieczorek, A. (2017). The influence of self-driving transport vehicles on the field of logistics. Zeszyty Naukowe Uniwersytetu Gdańskiego. Ekonomika Transport I Logistyka, 66 (0), 107-114.

Retrieved from http://dx.doi.org/10.5604/01.3001.0010.5602

Zakharenko, R. (2016). Self-driving cars will change cities. Regional Science and Urban Economics, 61, 26-37.

Retrieved from http://doi.org/10.1016/j.regsciurbeco.2016.09.003

This sample could have been used by your fellow student... Get your own unique essay on any topic and submit it by the deadline.

Let a professional writer get your back and save some time!

Hire Writer

Find Out the Cost of Your Paper

Get Price