An autonomous vehicle (AV) is one with the capability to drive itself to a predetermined destination using inbuilt self-driving technologies. The study of AVs is critical in helping the car manufacturers, policymakers and end-users to understand the new features of the automobiles. The mention of AVs stirs feelings of expectancy and excitement among individuals because of automobiles’ unique features. Therefore, the research topic will create a vivid image of the features of AVs and their transformative impact on society. Over the last two decades, there has been an increased desire for AVs, particularly in serving as special purpose vehicles for the aged and disabled (Bagloee, 2016). As a result, motor vehicle manufacturers have invested more resources in the development of the technology. Among the frontline developers of AVs has been Google and Toyota. The conceptualization of AVs not only appeals to the public but also provides an opportunity to reflect on human possibilities. Therefore, to fully appreciate the transformative impacts AVs will have on society, understanding how they will reduce road accidents and traffic congestion is paramount. Also, the demerits of unpredictable demand forecasts and ambiguities in interpreting machine and human decisions should be considered.
Advantages of Autonomous Vehicles
Reduced Accident Prevalence Rates
The use of AVs will diminish incidents of road accidents by eliminating human beings in the driving equation. AVs have the capability to reduce road accidents caused by human recklessness since they are self-driven (Mohseni et al., 2020). The advantage of reducing road accidents is amplified by the glaring fact that above ninety percent of road accidents are caused by human errors and choices, which could include inexperienced driving, driving on the wrong side, careless overtaking, overloading and driving while drunk. Reduced road accidents will be possible provided that manufacturers remain thorough during the manufacture of AVs. Therefore, the emergence of AVs will enhance road safety by reducing road accidents because it replaces human drivers who are prone to errors.
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Reduced Congestion, Enhanced Economic Growth and Mobility
It is expected that AVs will massively reduce traffic congestion in the cities. Reduced traffic congestion will be possible because AVs will result in smooth traffic flow unlike when human drivers are involved (Overtoom et al., 2020). Also, AVs will minimize congestion because their use will eliminate crashes which often cause delays on roads when they happen (Bagloee, 2016). Additionally, the technology will allow the AVs to be connected and easy to share unlike human-driven vehicles (Overtoom, 2016). Due to the ease of sharing and connecting, the net result will be a decline in congestions. Moreover, AVs will lead to a vibrant economy since the hours spent in traffic jams will be translated into economic building. On the other hand, mobility denotes versatility or the ability to move or be moved freely (Ionita, 2017). Automated vehicles will eliminate the biases experienced by individuals living with disabilities on the roads since the vehicles are driverless and the processes that need to be done by human beings will be carried out by Artificial Intelligence machines (AI machines) (Ionita, 2017). Moreover, the disabled groups will be able to make purchases and receive services at their doorsteps without being subjected to traffic on the roads or the tedious process of driving. Therefore, the onset of autonomous vehicles will ease traffic congestion by reducing crashes, propelling economic growth and enhancing the lives of people living with disabilities.
Challenges of AVs
Difficulties in Framing AVs Driving Decisions
Autonomous vehicles are built based on AI. Therefore, AVs will have to interpret the various human decisions to be successful (Cunneen, et al., 2019). The major challenge of AVs will be to frame the machine driving decisions (Cunneen, et al., 2019). According to Cunneen et al., (2019), there exist differences between the AI and human decision-making processes. Therefore, all stakeholders in the transportation sectors have to focus on how to harmonize the various decisions made by humans and AI machines. Additionally, human decisions may be interpreted differently from one person to the other (Cunneen, et al., 2019). Since interpretation varies, it remains a difficult task to ensure that AI machines will deduce human decisions as meant by humans. On the other hand, whether humans will precisely interpret the AI machine decisions is another matter altogether (Cunneen, et al., 2019). Hence, while autonomous vehicles present an opportunity to transform transportation, harmonizing human decisions and those of AVs and developing a uniform interpretation of the decisions remains an uphill task.
Demand Forecasts and Consumer Acceptance
Another major problem facing AVs is the unpredictability surrounding its markets and demand forecasts. Bagloee et al., (2016) argue that it is difficult for car manufacturers or policymakers to evaluate the number of users who will turn to the use of AVs. The unpredictability is amplified by the expected high costs of the vehicles. Moreover, the motivation for developing AVs which was anchored on enhancing mobility for the disadvantaged groups seemingly suggests that it could attract a low number of consumers. For instance, in developed countries, AVs were purposely designed to help the aged and disabled groups to freely move in the cities and towns. Therefore, the main consumers of AVs could be the minority groups, a notion that is disastrous for manufacturers. Additionally, in developing countries, the high poverty and dependency ratios manifested by the minority groups implies that it could be difficult for AVs to gain customer acceptance. Hence, despite the excitement of policymakers and manufacturers about the idea of AVs, inadequate demand forecasts could lead to eventual failure. There needs to be a mechanism to succinctly study the AVs markets to aid in rolling out plans, including the market demand rates and the available markets. Lastly, demand forecasts are further contemplated by the expected high costs of AVs. Hence, AVs manufacturers have a mandate to strategize AVs programs to achieve their full potential.
Debunking the Misconceptions about Autonomous Vehicles
After the emergence of the possibility of manufacturing AVs, many misconceptions have clouded the process. As a result, consumers have high expectations about AVs and their performance (Dani et al., 2019). Some of the widespread myths are that AVs are safer than human driving, they will greatly reduce congestion, lead to the closure of vehicle insurance companies and enhance environmental conservation (Dani et al., 2019). The misconceptions are detrimental because AVs have not been tested on a large scale and proven to be so. Also, such unproven ideas may lead to consumer rejection if, after their large scale roll-out, they fail to meet consumer expectations. To be precise, AVs could still cause road accidents as they are manufactured by humans who are vulnerable to errors. Lastly, since errors are inevitable, insurance companies have to insure owners and users. Therefore, unless facts about AVs are brought to the fore, the misconceptions could be catastrophic to manufacturers given the high consumer expectations.
Conclusion
Individuals need to understand the benefits of AVs to fully recognize their transformative impacts on society. AVs will benefit the society by reducing traffic congestion, fostering economic growth and enhancing mobility for the minority groups like the aged and disabled. Nonetheless, the existing uncertainties regarding demand forecasts and interpretation of AI machine decisions should be handled alongside the ever-spreading misconceptions about AVs. Ultimately, AVs will revolutionize the transportation sector.
References
Bagloee, S. A., Tavana, M., Asadi, M., & Oliver, T. (2016). Autonomous vehicles: Challenges, opportunities, and future implications for transportation policies. Journal of Modern Transportation , 24 (4), 284-303. https://doi.org/10.1007/s40534-016-0117-3
Cunneen, M., Mullins, M., & Murphy, F. (2019). Autonomous vehicles and embedded artificial intelligence: The challenges of framing machine driving decisions. Applied Artificial Intelligence , 33 (8), 706-731. https://doi.org/10.1080/08839514.2019.1600301
Dani, S., Nikitas, A., & Njoya, E. T. (2019). Examining the myths of connected and autonomous vehicles: Analyzing the pathway to a driverless mobility paradigm. International Journal of Automotive Technology and Management , 19 (1-2), 10. https://doi.org/10.1504/ijatm.2019.10019850
Ionita, S. (2017). Autonomous vehicles: From paradigms to technology . IOP Conference Series: Materials Science and Engineering , 252 , 012098. https://doi.org/10.1088/1757-899x/252/1/012098
Mohseni, S., Pitale, M., Singh, V., & Wang, Z. (2019). Practical solutions for machine learning safety in autonomous vehicles. arXiv preprint arXiv:1912.09630
Overtoom, I., Correia, G., Huang, Y., & Verbraeck, A. (2020). Assessing the impacts of shared autonomous vehicles on congestion and curb use: A traffic simulation study in The Hague, Netherlands. International Journal of Transportation Science and Technology , 9 (3), 195-206. https://doi.org/10.1016/j.ijtst.2020.03.009
