Abstract
Self-driving vehicles and artificial intelligence are frequently complementing technological concepts. Many significant automakers, including the AI Robotics Company, have been developing autonomous vehicles and driving technologies. Artificial intelligence is used in almost every step of the production of cars. AI is widely used in the machine-building sector as it helps to manage robots that manufacture cars or create specific vehicles driven by AI (Pel et al., 2020). The concept behind self-driving cars is very straightforward, as it involves constructing a vehicle with cameras that can track everything around it.
Self-driving cars will not merely alter how people perceive transportation. They will significantly alter people’s behavior, opening up new opportunities for digital marketing. This kind of marketing could emerge as a new pillar when taking into account the two hours the average person spends daily in their car, according to most research. By developing individualized, value-added services, this emerging market might be an excellent new method for businesses to interact with their target demographic (Currano et al., 2018). Technology is primarily aimed at younger consumers as well as locals without access to private vehicles or who may otherwise have driving issues. It is anticipated that it will particularly benefit the elderly, the disabled, and members of the millennial generation. Specialists predict that driverless vehicles can help to save around $800 billion annually, which will benefit society (Kabzan et al., 2020). It can be achieved due to the reduced number of car accidents and costs necessary to manage them, lower number of injured patients and reduced spending on healthcare, more effective use of fuel, and enhanced logistics.
Introduction and Problem Statement
An automated vehicle is a type of car that can analyze external factors and function without any human driver. AI is the major element of these vehicles; however, they also require sensors, machine learning software, and a CPU to process all information. All these components process the acquired information and build a route using the existing maps. Sensors and radars help the vehicle to avoid other cars and accidents. The car uses cameras to respond to traffic lights, passengers’ movements, and other changes in settings (Pel et al., 2020). The vehicle is also equipped with lidar to determine boundaries and build a better image of the world around it. The parking is enhanced due to the use of ultrasonic sensors placed on wheels and helping to avoid crushes. Information coming from all devices mentioned above is analyzed by AI and software and helps to build a new route and avoid accidents.
This technology, however, is experiencing a major drawback due to skepticism about its general workability. The general public is afraid of embracing it as it is common with any other type of technology. Like any other technological advancement, a self-driving car would be susceptible to hacking. Since the operation of these vehicles depends on software, a hacker who gains control of the software effectively has control over the vehicle. There are several ways in which this could be hazardous to car owners’ safety (Kinra et al., 2020). The vehicles operated by AI can help to reduce the number of pedestrian accidents and manage the risks mentioned above. The world’s universities, automakers, Google (GOOG), and DARPA are all working hard to make this a reality. The concept of autonomous automobiles and their wide use might be beneficial because of the reduced traffic accidents and financial savings because of the lack of physical damage or injuries that should be compensated (Wiseman, 2022). Moreover, this type of car can help to reduce energy costs because of the increased driving efficiency and better traffic management. Potentially, the net economic advantage will be huge.
Situation Analysis
Potentially safer transportation is one of the automated vehicles’ strengths, arguably the most important benefit. Controlling traffic flow is substantially facilitated when a human mistake is eliminated by machines. Even if machine technology and software still raise issues, the present transportation model already includes these risks (Czech et al., 2018). The stress that would no longer be a part of daily life due to individuals having all the time they need to make preparations is another significant benefit of autonomous driving.
The drawbacks of automated driving take many different shapes. It may be dangerous to drive, so it is unsettling to completely hand that responsibility over to an automatic system. Safety in an autonomous transportation system depends on the program’s infrastructure (Ondruš et al., 2020). Automated driving needs to be made practicable in some places, which may include changing traffic systems and establishing regulations for manufacturers. Before deployment is feasible, a significant amount of data must be gathered, and extensive testing must be done.
The opportunities opened up by autonomous transportation appear endless as the manufacturing industry will make losses and win benefits. Autonomous automobiles would create a new transportation paradigm in which considerably fewer cars spend much more time on the road, and manufacturing itself would undergo a significant change (Gandhi, 2019). Moreover, ride-sharing and the opportunities associated with it can help to prolong the life cycle of most cars. As a result, a reduced number of cars will be needed, while autonomous cars will perform more functions and will be frequently used.
The ownership structure might also alter in tandem with this shift in the manufacturing paradigm. The necessity to possess a car may become less pressing for many Americans, even though they may become more expensive. Instead, the popularity of ride-sharing may skyrocket, making transportation more of a pay-as-you-go business (Currano et al., 2018). As the nation gets ready to switch to a different mode of transportation, this might also be the ideal time to increase the amount of electric technology in cars, cutting down on carbon emissions.
The advantages of self-driving cars may seem endless, but so may the dangers. The possibility of harm from unforeseen circumstances poses perhaps the biggest threat (Ghansiyal et al., 2021). The major threats of this technology include whether the software systems are secure and free of errors. It is also a major concern whether someone can program such software for malicious purposes (Kinra et al., 2020). There are many wealthy individuals and a plethora of powerful organizations such as oil corporations, driver’s unions, and automakers that may potentially perceive self-driving cars as a danger.
Politically, the government has a crucial part to play in the implementation of driverless cars as it is overly regarded as a great source of revenue generation. However, the state government is not stable and powerful enough to support this technology. The central government disregards driverless vehicles as they result in high levels of unemployment (Fayjie et al., 2018). This makes it challenging to implement and fully adopt this type of technology. Economic factors affecting this technology include growing disposable incomes. People all around the world are making an increasing amount of money yearly. This factor explains the continuously growing demand for various vehicles (Stevens et al., 2019). For this reason, it is possible to predict a further increase in the number of sold cars and the generation of additional benefits for the industry’s workers.
Popularity in driving is one of the sociocultural factors involved. Most families globally prefer to have one or more cars to perform daily activities. This makes the adoption of the driverless car a problem as people are always reluctant to change. Technologically, the world is slowly shifting to self-driving technology (Schneble & Shaw, 2021). It is possible to predict the radical change in the ways clients interact with automakers because of the high digitalization and automation of the process and the use of technologies. For this reason, car manufacturers using traditional schemes should adapt their strategies and ensure they shift to new methods of working with clients to preserve their loyalty. The automobile sector may not inherently benefit or suffer from this, but conventional vehicle makers may need to adjust their business plans to remain relevant.
At the same time, from a legal perspective, the car business also has some copyright issues. Unique automotive features or innovative solutions are protected by copyright laws and trademarks. It provides companies with arguments that can be used in legal battles or lawsuits. (Amichai H., et al., 2020). The main environmental that impacts the transport industry is carbon emission which is currently a global concern. The automotive industry is one of the main producers of carbon dioxide, which is one of the most significant air pollutants (Dave et al., 2019). It creates the greenhouse effect promoting global climate change. For this reason, the possible solution to the environmental problem is the prohibition of motor vehicle production and a shift to electric vehicles. This factor might have a positive impact on AI companies and the market of driverless vehicles.
Objective
The objective of this company is to achieve a friendly self-driven world that is free of pollution and minimize road accidents. By adopting driverless cars, the company anticipates a 90% reduction in traffic accidents which are believed to be caused by human error. This will mean saving 30,000 lives in a single year (Pel et al., 2020). The rate of pollution caused by carbon emissions is also expected to reduce by 60% (Pel et al., 2020). This will provide a friendly environment due to decreased rate of global warming. This project also aims at saving people 40% of the time they spend traveling. It helps to acquire a gain in productivity of £20 billion and improve the time management of individuals who travel by car (Kabzan et al., 2020). Moreover, in the USA, driverless vehicles are expected to save about 80 billion hours and spare about $1.3 trillion (Kabzan et al., 2020). The overall net gain translates to an efficient green world where people will enjoy living.
Market Segmentation Analysis
The global market for self-driven cars is segmented based on their components, automation, application, vehicle type, and geography. The semi-autonomous car segment is anticipated to rule the market over the forecast period based on type (Fayjie et al., 2018). The semi-autonomous market category holds the most significant market share globally. There are many levels of automation in semi-autonomous vehicles, such as level 1, level 2, and level 3. They will have our fastest market growth in the level two and level three automation of semi-autonomous car segments. In comparison to level one, levels two and three have higher penetration rates. The market is expanding due to level 2 and level 3 technology advancements.
The passenger car sector is anticipated to have the biggest market share throughout the projected period when broken down by vehicle type. The passenger car category is anticipated to expand throughout the forecast period as a result of the rapid urbanization occurring in developing countries and the rise in population in developed countries (Zhou & Sun, 2019). The most significant drivers of this market’s rapid expansion are higher demographic growth, rising living standards, and rising purchasing power in developing countries.
The market is being driven by growing government funding for these self-driving car trials. Based on application, the market for self-driving cars has been led by the transportation sector, which had a share of around 93% in 2021 (Kaur & Rampersad, 2018). The UK government established the Intelligent Mobility Fund to encourage additional innovations in the transportation sector. The mode of transport could be either commercial or industrial. As the US government continues to alter the transportation legislation, it is anticipated that driverless technology will one day be a hired option in transportation. Enhanced transportation rules are facilitating the introduction of self-driving automobiles into this region.
The North American region was the leader in the market during the previous years. Before 2020, it had about 45% of the volume share of the whole industry (Kabzan et al., 2020). The development of self-driving vehicles in this industry results from changes made to US traffic laws. As a result, this type of car emerged on public highways in the USA. (Karmakar et al., 2021). The new approach is used in all stages of the country, which can make transportation completely autonomous. The market for self-driving cars is anticipated to expand strongly in the next years due to the rising demand for mobility as a service.
Marketing Mix Strategy
The product is a valuable object or service that is offered to clients. Thus, availability, maintenance services, specific recommendations, brand name, and physical products are the major aspects that AR Robotics can offer to clients. The brand also supports buying new products and pre-purchase education for its staff to improve the product (Koul & Eydgahi, 2018). AI Robotics Company’s managers possess unique chances to create a specific value of the firm’s proposal to ensure it differs from rivals.
The firm conducted market and customer research to acquire an enhanced understanding of its clients’ needs and meet them. Using this information, the current value proposition, and clients’ interest, AI Robotics created a particular product. Thus, designing and testing a certain product, it is vital to consider customer value proposition, the potential for differentiation, AI Robotics’ resources, and profitability issues (Grigorescu et al., 2020). Driving an autonomous product launch implies determining the product’s price, creating the communication plan, selecting the distribution model and channel, and establishing the developed infrastructure.
Pricing is the next important and complex aspect that should be considered when developing and introducing a product. First, it is impacted by the product’s features, setting, promotion, and advertising (Salonen & Haavisto, 2019). Thus, the perceived value is the highest possible price consumers ready to pay for AI Robotics products. The firm can employ a cost-based approach by determining the final price regarding the cost of production and manufacturing. It can help the firm to survive in an environment characterized by fierce rivalry and changes in demand.
Furthermore, AI Robotics uses specific distribution channels to deliver its products to final users. Distribution and marketing channels help to provide clients with data about the products and help to customize offerings to acquire better sales. Moreover, the employment of an effective distribution channel helps to improve product accessibility and provide users with opportunities to buy them (Jones et al., 2021). The company should choose between the direct, indirect, or combined distribution model. The choice can be impacted by the current product’s range, customer value proposition, convenience points, breadth and length of the firm’s offerings, and competitors’ approaches to working with clients.
A promotion mix approach combines the different promotion resources at AI Robotics’ disposal. The company uses specific models, such as personal selling, sales promotion, direct marketing, and public relations. The price and specific product features can be explained to the AI Robotics company’s customers by using all options mentioned above. (Bissell et al., 2020). Thus, email marketing can help AI Robotics to cooperate with clients directly. Using the information collected through customer surveys and other tools, such as direct communication and kiosks, the firm can design new projects and ensure they are connected to the current demands and clients’ needs.
Implementation and Evaluation
To keep driverless cars on the road, several factors need to be considered. Because autonomous vehicles will be electric, AI Robotics will require a consistent charging source with increasing capacity to handle an increase in demand. The company will also require a change in the insurance model (Pisarov & Mester, 2021). The model will have to shift from insuring human beings to insuring self-driven vehicles. The general public’s view on the implementation is positive, as they are excited about being able to work, rest, read, eat, or watch TV while on the ride. This will impact the company positively during the general marketing of its product.
For driverless cars to grasp their surroundings and the context of their driving, they will require rules and constraints. Based on infrastructure and hazards, the company has to choose when and where autonomy is allowed. To represent the diverse situations, this must be different in urban and rural settings, as bad weather can be problematic because it limits the sensors’ range and precision (Pokusaev et al., 2019). The instruction must be as close to infallible as possible and provided to the cars in real-time. Determining whether passengers should pay for each ride or whether the council should buy cars for their region will need allocating financing for driverless cars. Additionally, money must be allocated for maintenance, energy, and higher standards of road maintenance.
To fund the AI Robotics activities, the company will partner with various funding agents as well as apply for grants. An example of these funding agents is the AVIN Research and Development Partnership Fund for autonomous vehicles (Fayjie et al., 2018). A program called the AV Research and Development Partnership Fund is also provided by AVIN. Lead applicants (technology developers) collaborate with partners, including other SMEs, big businesses, and post-secondary universities, to design, prototype, and evaluate cutting-edge autonomous vehicle technologies through the program’s Technology Demonstrations stream (Karmakar et al., 2021). In such a way, regarding the application and partner contributions, the offered grants can help to cover around 33% of eligible costs and comprise about $1 million (Pokusaev et al., 2019). These funds will be used to achieve the organization’s goals and sell its product to the bigger world. A mega product launch will be done as part of the marketing.
Conclusion
Altogether, self-driving technology continues to evolve and can alter the conventional transportation system radically. However, although self-driving cars are legalized and become part of the legal environment, people remain skeptical because of safety concerns and do not use them in everyday life. At the same time, this type of vehicle can become the dominant form of transportation because of the continuous development of technology. The future of AI-driven cars is linked to accountability, responsibility, sustainability, and effectiveness issues. Moreover, moral and ethical concerns remain relevant and influence customers and producers. Transitioning to this type of car will help to reduce emissions, address the climate change problem, and improve society’s cohesiveness. For this reason, companies focusing on manufacturing and selling self-driven cars might become potent change agents, promoting the alteration of the sector and popularizing this type of vehicle. Moreover, they can expect continuously growing revenue because of the further development of technology.
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