Autonomous Vehicles
Introduction
The field of autonomous vehicles has led to significant interest among researchers as many studies have been established in this area. Autonomous cars are a fundamental contribution to the automotive industry, and the aspect is shifting towards innovations and economic development. The past decade has gained momentum regarding new research, and the whole world is at an advanced phase of technological transformations, including the introduction of autonomous cars. Autonomous vehicles are self-driving cars, and their main focus is to keep people out of the car's control loop and relieve them from the act of driving. The fundamental aspect of autonomous cars is the sensor that acquires traffic information of the vehicle environment. Modern computers also process sensor data and send it to warning and control detectors. Self-driving cars also have actuators that assist in longitudinal and lateral control. The automated car has generated publicity and debates. Each automobile organization is trying to create personal autonomous car concepts and underlying plans to begin producing self-driving cars in the coming years. However, people have mixed feelings of excitement and insecurity about self-driving. Many researchers have found that consumers will either accept or reject them on the ground of their effects (Overtoom et al., 2020). Analysts have already considered the impact of autonomous cars on carbon emission and the number of vehicles per individual. Researchers are providing their suggestions on car automation, and the central concept is that these vehicles must outperform human driving abilities to secure a large consumer market. The consequences of car automation have a huge impact on global mobility and the competition in the labor market. Overtoom et al. (2020) lay the basis for future research and point out potential weaknesses with technologies as the car's abilities evolve. On the same note, there are numerous controversies concerning the ethical guidelines, vehicle decision-making, and car's software ability.
Literature Review
Current Status and Research
The automotive sector is at rapid technological transformation due to concepts surrounding self-driving vehicles. All companies are now dedicated to making their autonomous vehicles. Even the organization that is not in mainstream automobile sectors such as Google and Uber also plan and research the self-driving car idea comprehensively. Apple is currently making its driverless vehicle, and the project is referred to as 'Titan" (Overtoom et al., 2020). Also, the idea of electric vehicles is already in practical application. Tesla and General Motors have significantly launched their respective electric vehicles in the market and are available to clients (Pribyl & Lom, 2019). However, the autonomous vehicle is still in research, but some vehicles already have minimal autonomy levels, such as GM supercruise management and Tesla autopilot.
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Additionally, the Massachusetts Institute of Technology (MIT) has an ongoing project called iSee. They develop and test autonomous driving systems by utilizing artificial intelligence. The team has an object detection concept called YOLO (you only look once) created by Joseph Redmond (Overtoom et al., 2020). The concept is being utilized to further research self-driving vehicles. Faurecia, who deals in making car components, has launched the cockpit for self-driving vehicles. When the autonomous mode is chosen, the steering wheel folds and the system behind the parts falls at the center of the screen. Additionally, Waymo, the subsidiary parent organization of Google, an autonomous technology firm, successfully tested its concept vehicle. The company argues that it will launch driverless vehicles to distribute items, especially with firms launching their self-driving vehicles, such as Aston Martin. They launched their version of driverless cars called Lagonda Vision Concepts. It is an expensive electrical level 4 autonomous vehicle. Another example is Renault, which made their driverless concept vehicle called SYMBIOZ, which drives manually but in autonomous mode (Kim et al., 2020). Many more advancements are being performed in the autonomous vehicles sector, and the above examples demonstrate the seriousness and enthusiasm regarding the transformation of the automotive industry.
Effects of Autonomous Vehicles on Mobility
The initial prototype of autonomous cars was made with huge conservative aspects to guarantee safety and convenience. In that case, it will reduce traffic jams on the road. For instance, there is a recommended time gap set to 2 seconds instead of 0.7 seconds in common human driving (Kim et al., 2018). Additionally, the acceleration and deceleration of self-driving vehicles are smooth and alter lanes only under suitable situations. Kim (2018) found out that significant rates of autonomous cars were launched to ease traffic streams due to their driving behaviors. The study concluded that it would ease congestions due to increased capacity reactions. The capacity loss has been approximated to be about 600 cars/hour/lane for a typical freeway (Kim, 2018). However, the recommendation has not been put into practice because few individuals will attempt to travel in cars that drive faster than individuals do. The solution to the matter depends on collaboration between cars, i.e., sharing information and making wise decisions regarding safety and global efficiencies.
The accessories in autonomous vehicles could improve safety and experience. According to Cui et al. (2019), transport accidents are among the leading causes of death globally. The study argues that the world could have prevented about 6 million human deaths and 60 million severe injuries by introducing the latest and innovative techniques and transformations in road safety nationally and globally. The Commission of Global Road Safety argues that is essential to eradicate preventable and hazardous increase in road accidents. The study showed approximately 3500 deaths daily due to road accidents. The study also reported that if long-lasting solutions are not implemented, road injuries are set to increase by 3 million yearly, becoming the 4th leading cause of death globally. With the introduction of self-driving cars, traffic collisions will drastically reduce due to automatic mode, increased reliability, and rapid response time. The phenomenon would also decrease accidents because there will be a rise in roadways ability. The driverless cars would result in a decreased requirement of safety gaps. The traffic flow management will become efficient.
Parking scarcity will become a historical problem with the introduction of self-driving vehicles. A vehicle could only drop off people and park at any convenient area, then go back to pick up other individuals. Therefore, there will be a reduction in parking spaces. There will also be no need for physical signage as the self-driving vehicles will get the required data via the network. Traffic police work will be limited, which will decrease government expenditure or areas like traffic management. The requirement for car insurance will also reduce because there will be a huge reduction in vehicle theft. Alongside that, vehicle sharing and goods transport systems such as taxis and trucks can be launched with complete eradication of redundant passengers. Martínez-Díaz and Soriguera (2018) found that not every person is suitable for driving. Therefore, self-driving vehicles offer relief from driving and navigation duties.
Additionally, the number of consumers of ride-sharing systems is constantly on the rise. Isele (2019) found that many young people find it unnecessary or non-advisable to own a car for various reasons. They argue that personal cars spend more time parking approximately 22 hours in a day than in motion. The purchase and maintenance expenses are extremely high, and congestion in urban regions is a significant problem. They also have other mobility solutions, and there is a growing sustainability awareness among the developed communities. This trend towards car utilization instead of its ownership is expected to increase according to the recent survey (Isele, 2019). The presence of hailing methods will become intensive, and they will become less costly due to economies of scale. Furthermore, autonomous cars are excellent in supporting mobility methods because huge technological components save on labor experience and appeal to entrepreneurs. Self-driving cars' high costs will ensure there is shared utilization instead of personal ownership. Sharing techniques based on electric self-driving cars are expected to be supported by the general population's administration. The initial conclusion could be drawn from the older solutions that the general care fleet will drastically reduce. Isele (2019) argues that the car fleet reduction has already been approximated to be around 20-26% in Europe and United States by 2030. The aspect will benefit both the automotive industry and the general public.
About the mobility rates, there is no agreement between its application. Multiple studies approximate the decrement of car-km per person, whereas there is a general rise regarding car-km (Kim et al., 2019). Both dimensions imply much higher individual mobility of the nation. The phenomenon is also linked to car-sharing as vehicles would carry more individuals in every travel. For instance, the current vehicle occupancy is 1.3 pax, but this is expected to rise for shared cars. However, the most recent study disputes the expectancy by pointing out that car-km per person will likely increase. Personal self-driving cars make empty travel, for instance, in parking once their owners are at the destination. The configurations of the collective road system will also be vital. The car-sharing technique will make mobility effective and sustainable if only they replace personal car tips but not the people in mobile whose occupancy is higher and more sustainable. It will be attained if car-sharing complete collective road systems aim to cover the last miles of a person's reroute towards the minimal density regions. Mass transit must adapt to these latest situations when integrating on-demand services such as MaaS. Koopman et al. (2019) demonstrate that the trade-off between the essential investment and general advantages is significantly affirmative. The total car-km will decrease transportation experience because of maximum usage rates of cars and their shared utilization. As a result, both freight and passenger transport are expected to increase. The number of passengers will increase as non-drivers such as the young and old population will be on transit in autonomous cars.
Further Considerations about Autonomous Vehicles
Like in all past road transformations, the variables that will support or reject autonomous cars' overall adoption will arise, especially those related to mobility. For instance, increasing awareness regarding global warming and environmental effects will play a vital role. Pendleton et al. (2017) argue that the number of electric vehicles will increase with automation as the significant disadvantages due to inadequate charging networks or battery-related range anxieties will be eliminated. The public incentive to electric cars, their minimal maintenance expenses, and the adoption of fuel economy guidelines and electric car mandates will significantly affect autonomous vehicles' transition procedures. Other factors that will affect the adoption include town access restrictions for cars powered by engine combustion. With driverless cars, electric vehicles will no doubt capture the market. Additionally, well-structured management techniques, including the autonomous, will increase traffic evidence and reduce carbon emissions and energy consumption. Generally, automation has already boosted eco-driving.
The autonomous vehicle will affect land utilization and could have adverse territorial impacts. According to Ribbens (2017), autonomous cars are thought to provoke urban entrepreneurs because of low transportation expenses and possible utilization of travel time to work and rest. It is expected that more than 60% of the world population will be living in towns by 2050 (Ribbens, 2017). Town planners must ensure that the urban planning techniques adhere to green, leisure, and agricultural areas. Also, on-demand services must have well-controlled mobility by organizing a distinct transport mode necessary to prevent congestion because of long commutes. For instance, park and ride amenities in the town periphery would lead to free space and sustainable urban areas.
Another fundamental dimension that must be considered is human's acceptability of autonomous vehicles. According to Ye and Yamamoto (2019), some individuals do not trust leaving their life under the control of machines. Other people reject the idea of sharing individual information due to numerous cyber-attacks. Entrepreneurs will see autonomous vehicles as competitors because professional drivers, old garages, and taxis are expected to disappear. Contrarily, some sectors will benefit from automation, especially those in informatics and communication. Proponents of autonomous vehicles argue that reduced mobility will positively affect the environment (Ye & Yamoto, 2019). The most probable solution of this debate on acceptability will depend on the progress, educational campaigns, and awareness that will transparently inform people about the benefits and disadvantages that autonomous cars will bring into society.
Conclusion
Arguably, autonomous vehicles' adoption has not been clearly accepted or rejected. However, car automation needs fundamental policy changes and new legislation. The legal guidelines are expected to postpone driverless cars' adoption due to technological problems. Information treatment must also be regulated. Safety, security, and privacy should be autonomous vehicles' fundamental goals. The administration should ensure that consumer data are safeguarded during sharing in the collaborative driving settings. Users should have the right to retain control over the information and engage car manufacturers, software developments, and authorities to protect their information against cybercriminals.
References
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Isele, D. (2019). Interactive decision making for autonomous vehicles in dense traffic. 2019 IEEE Intelligent Transportation Systems Conference (ITSC) . https://doi.org/10.1109/itsc.2019.8916982
Kim, T. J. (2018). Automated autonomous vehicles: Prospects and impacts on society. Journal of Transportation Technologies , 08 (03), 137-150. https://doi.org/10.4236/jtts.2018.83008
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Pribyl, O., & Lom, M. (2019). Impact of autonomous vehicles in cities: User perception. 2019 Smart City Symposium Prasgue (SCSP) . https://doi.org/10.1109/scsp.2019.8805717
Ribbens, W. B. (2017). Autonomous vehicles. Understanding Automotive Electronics , 573-593. https://doi.org/10.1016/b978-0-12-810434-7.00012-0
Ye, L., & Yamamoto, T. (2019). Evaluating the impact of connected and autonomous vehicles on traffic safety. Physica A: Statistical Mechanics and its Applications , 526 , 121009. https://doi.org/10.1016/j.physa.2019.04.245
