History of Automated Vehicles
Automated vehicles in the past in 1939 World’s Fair, General Motors established the first ideal self-driving car (De Freitas et al., 2021). The model was an electric car steered by a radio-managed electromagnetic field. Moreover, the car functioned from captivated metal stakes implanted in the streetway. The vehicle had triggers that could sense the current flow via a wire implanted on the street. The draft can be altered to shift the controlling wheel from either left side to the right direction. Since 1977, the idea of automated vehicles has been improved by different researchers to create a better self-driving car.
The present autonomous cars use a combination of forward-facing cameras with a collection of radar networks which gather relevant information about different factors such as road conditions, which help in further processing. The systems in autonomous vehicles can learn to detect, classify and allocate ‘weights’ to obstacles on the road, thus providing the car with a processor with sufficient information to choose the route of least resistance. Every weight is arbitrary, which plays a vital role in determining how an autonomous car behaves.
These are six levels of automation, with the primary level being level 0, which has no automation. At this stage, the driver is fully responsible for controlling a vehicle, performing every required task, including steering control, breaking and managing the speed. Level 1 is driver assistance, where the systems start to operate an automated vehicle in particular situations, but the systems don’t have complete control. Level 2 is partial automation, where the car begins to perform complex tasks like steering control and breakinglevel 2+ with an advanced partisan automation stage where the driver still monitors the vehicle.
De Freitas et al. (2021) contemplate that level 3 is conditional automation, allowing drivers to disengage from controlling the car only during certain events. The drivers only respond to tasks in the vehicle. Stage 4 is a high automation level where the autonomous driving system can monitor the driving environment and manage all driving functions in a car. Level 5, where full automation occurs, allows the autonomous vehicle without any driver behind the wheel, with advanced features like voice commands.
Autonomous vehicles in the future will likely possess the capability to generate approximately 300TB of data in one year. There is a high continuity in the evolution of safety technologies, laying a foundation for the better establishment of intelligent software-defined automated networks. A system which will have the capability to foster better navigation of roads with minimized human intervention. Moreover, the innovation of 5G technologies will play a key role in promoting the implementation of artificial intelligence, which will be pivotal in autonomous vehicles.
Pros and Cons of Automated Vehicles
Based on safety, automated vehicles have an advantage as reports indicate that in more than 37,133 car accidents in 2017, 94% of the accidents were caused by human errors. According to Elliott et al. (2019), automated cars will serve as an advantage in improving the safety of passengers. The computer’s sophisticated networks and algorithms will reduce human mistakes like drunk driving. The cons of autonomous vehicles based on safety are security issues, as the automated cars can share the same network, thus making them susceptible to easy hacking, which threatens the safety of passengers in the autonomous vehicle.
Automated cars can solve ethical dilemmas as they can communicate in real-time. Thus the vehicle can easily travel efficiently at optimized distances from each other. Moreover, automated vehicles can decide which is the best route to take to avoid traffic jams. Despite possessing this advantage, motorized vehicles have a moral machine dilemma. They cannot initiate judgements linked to multiple unfavourable outcomes, like deciding whether to veer and hit a pedestrian or deviate from hitting an object and possibly injuring the passenger inside.
Based on environmental impact, automated cars are environmentally friendly because most are electric. Thus they contribute to less emission of harmful gases into the environment; therefore, they are ecologically sustainable (Elliott et al., 2019). Automated vehicles promote efficiency, as driving cars serve as a safe and reliable form of transport. Individuals who ate physically challenged can be able to drive a car with limited risks and access areas where infrastructure is lacking. However, machine error is associated with autonomous vehicles, compromising efficiency because the vehicles do not eliminate the chances of accidents resulting from machine errors such as software failure. Autonomous vehicles are promising in offering a solution to reducing traffic congestion in public transportation through GPS technology, offering alternative routes to reduce traffic jams, thus optimizing the flow of vehicles on the road.
The city as an app store will play a key role in offering solutions for the full utilization of automated cars. This is achievable as ride-hailing companies, including Uber and Lyft, are incorporating public transit into their apps, which will help individuals to initiate door-to-door trips, thus promoting mobility as a service (Hult et al., 2020). The app can encourage adherence to public transport guidelines, as the apps will have a mutual agreement with the app store where they can sell their products. Thus any violation means that they are out of the app store.
Allowing autonomous vehicles to utilize rapid transit lanes will be an appropriate approach to establish a solution to heterogeneous traffic pertaining to autonomous cars and regular cars, further providing a basis for traffic efficiency and guaranteeing safety. Furthermore, committed bus rapid transit lanes can offer a separate right-of-way for autonomous vehicles. An approach will provide practical and economical options for promoting independent vehicle enhancement.
Providing ethical solutions is a challenging element in fully utilizing autonomous vehicles. Still, the technology being used on the vehicle is anticipated to reduce the number of fatalities due to motor vehicle crashes. An approach will boost public health at a meaningful scale by reducing casualties. Software in automated cars will formulate behaviours with ethical ramifications aligning with norms of ethical conduct.
De Freitas, J., Censi, A., Smith, B. W., Di Lillo, L., Anthony, S. E., & Frazzoli, E. (2021). From driverless dilemmas to more practical commonsense tests for automated vehicles. Proceedings of the national academy of sciences, 118(11).Retrieved from: https://dig.watch/trends/rise-autonomous-vehicles
Elliott, D., Keen, W., & Miao, L. (2019). Recent advances in connected and automated vehicles. Journal of traffic and transportation engineering (English edition), 6(2), 109-131.
Hult, R., Zanon, M., Gros, S., Wymeersch, H., & Falcone, P. (2020). Optimisation-based coordination of connected, automated vehicles at intersections. Vehicle System Dynamics, 58(5), 726-747. Retrieved from: https://www.weforum.org/agenda/2019/07/autonomous-vehicles-driverless-cars-p
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