Introduction
There are several methodologies available for studying and analyzing the design of driverless vehicles and traditionally powered cars. I'd rather use Google to compare the performance characteristics of the two vehicle models. Similarly, I will pay visits to the firms that make the cars and conduct in-depth interviews with them. In addition, I will use the 2282 SMS service to obtain specific details about the cars.
Classification and Investigation
A driverless car is a self-driving vehicle that does not require human intervention. Driver aided vehicles, on the other hand, are vehicles that are driven and powered by humans. This kind of classification induces an irresistible desire to investigate their similarities and differences. Mainly, these aspects are studied in terms of costs of promoting the vehicles, validity, efficiency in their use, the probability of their success and the manpower requirements.
Costs of Promoting the Vehicles
Driverless vehicles require fewer costs in promoting their brand since they only require single software that can be used in other autonomous cars (Litman 2014). Driven vehicles on the other hand tend to have individual specifications which are different in most of the brands. These specifications are expensive since each car brand will spend enormously to promote their technologies which are different from other manufacturers.
Efficiency in Use
Regarding efficiency, driverless cars are most efficient since they only require software instructions and drive themselves. They detect pedestrians and other vehicles at a distance hence reducing the number of accidents annually (Drury, Lucia & Caruso 2017). On the other hand, traditionally driven cars depend on human input that is inaccurate and imperfect occasionally. This situation makes these vehicles less efficient since human error is apparent and accidents have higher chances of occurring.
Probability of Success
Furthermore, the driverless vehicles have a more substantial probability of success compared to driven cars. The ever revolutionizing and technological world is rapidly taking over the place of human labor (Litman 2014). This renders traditionally driven vehicles vulnerable to extinction since most people are leaning towards the technology-driven economy.
Legality and Validity
The legality and validity of driverless vehicles are still pending. The manufacturers are still experimenting with some features, though some reports indicate that the vehicles are yet to be legally allowed on public roads (Drury, Lucia & Caruso 2017). On the other side, the traditionally driven cars are legally allowed to operate on public highways but only after proper documentation and verification of their suitability of operation.
Manpower Requirements
Both vehicles, however, require the same manpower input requirements. Driverless vehicles require manpower in developing the software and also maintaining the same software regularly (Drury, Lucia, & Caruso 2017). Traditionally driven cars similarly require manpower in promoting their brands. The only difference with the driverless vehicles is that the occupant only needs to sit and enjoy the ride compared to the traditionally driven cars, which require physical and emotional attachment while driving.
Conclusion
In conclusion, it is evident that driverless cars have more positive impacts compared to traditionally driven vehicles. People around the globe are not the best drivers, and this paper has proved that driverless vehicles can decrease the number of accidents significantly. Introduction of the new type of vehicles equipped with computers, sensors and driving software will make our transport system healthy. Since their inception, traditionally driven cars have resulted to many accidents. It is high time the people should embrace technology in transport and resort to proper mechanisms of promoting quality and safety transport rules.
References
- Drury, M., Lucia, J., & Caruso, V. (2017). Autonomous Vehicles: An Ethical Theory to Guide Their Future.
- Litman, T. (2014). Autonomous vehicle implementation predictions. Victoria Transport Policy Institute, 28.
