In recent years, cars have become a more affordable mode of transport, and their number is growing rapidly. Traffic congestion is increasing and, along with this, traffic accidents are becoming more frequent. The causes of accidents are different, but in many cases, the human factor is triggered. In conditions of heavy traffic, it can be difficult for a person to navigate in a critical situation because he or she loses their temper and can make fatal mistakes. Given these circumstances, it becomes relevant to use self-driving cars, which could be controlled by special information and intelligent systems. However, the process of switching to self-driving vehicles is time-consuming and not fast for many reasons.
To successfully set up and run a business of self-driving cars, it is important to overview the potential problems. The control unit processors in automobiles still cannot handle the processing of large amounts of data necessary for the correct solution. There is no single large-scale information and transport system that combines all the vehicles, transport infrastructure, and information centres. To release self-driving cars on the road, changes are needed in the situation regarding traffic, which states that the driver must drive the vehicle. Before starting mass production of vehicles with a self-driving type of control, it takes a lot of time to develop, manufacture, and test prototypes.
The decommissioning and disposal of existing cars will also take time and financial resources. Since self-driving cars are likely to be launched on the road gradually, it is required to incorporate the function of responding to the inadequate behaviour of ordinary car drivers on the road in the intelligent control system. It is necessary to create a state program, the purpose of which will be to support manufacturers and stimulate the population to switch to self-driving vehicles.
Therefore, the business and its innovative technology should be integrated with a small segment of the automobile industry. For example, the program can be implemented in vehicles with a fixed route and driving time, such as delivery trucks. The latter sector is worth $740 billion annually, which means it is a prospective sector (Viscelli, 2018). I would set up the organizational structure in such a way that it thoroughly supports the truck owners.
In addition, to avoid controversies of unemployment among truck drivers and have an assurance for potential accidents, I believe that the drivers can be transitioned to become truck operators or monitoring employees. I also think that the support team department, in conjunction with the IT department, should be the largest division, and this dual-component should be the core of the organization. The human resources department and marketing team will be smaller components but will be critical in advancing the company’s interests.
The main reason why Uber went public seems to be based on the fact that the company is not profitable. It was gradually losing money, and at the end of 2018, its deficit reached $8 billion (Hawkins, 2019). Thus, by going public, the company can fully or partially cover its deficits. It means that Uber rides can become more expensive as a result, which will not be manifested in the higher pay for drivers. In addition, there are no prospects of Uber implementing self-driving cars shortly. The main reason is that there is only one death caused by a self-driving car, and the responsible party is Uber (Hawkins, 2019). Therefore, it is clear that Uber’s primary motivation for going public is the need for money, which will reduce the deficit.
Hawkins, A. J. (2019). Uber goes public: Everything you need to know about the biggest tech IPO in years. The Verge. Web.
Viscelli, S. (2018). Driverless? Autonomous trucks and the future of the American trucker. TRB. Web.