Self-driving cars, also known as autonomous vehicles (AVs), are vehicles that can operate without human intervention, using sensors, cameras, artificial intelligence, and communication systems to perceive the environment and make decisions. Vehicle-to-infrastructure (V2I) communication is a type of wireless communication that enables AVs to exchange information with the road infrastructure, such as traffic lights, signs, cameras, and sensors. Together, these technologies aim to create a safer, smarter, and more sustainable transportation system. However, they also pose significant challenges and risks that need to be addressed before they can be widely adopted and accepted. This article provides a comprehensive analysis of the technologies, opportunities, and risks of self-driving cars and V2I communication, and discusses the current and future implications of this emerging field.
Definition of self-driving cars and vehicle-to-infrastructure communication, and explanation of how these technologies work and what are the different levels of autonomous control.
Self-driving cars are vehicles that can perform some or all of the driving tasks without human intervention, such as steering, accelerating, braking, changing lanes, parking, and navigating. Self-driving cars use a combination of sensors, cameras, radars, lidars, and GPS to detect and recognize the surrounding objects, such as other vehicles, pedestrians, cyclists, animals, and obstacles. They also use artificial intelligence, machine learning, and computer vision to process the data and make decisions based on predefined rules and algorithms. Self-driving cars can communicate with each other and with the road infrastructure using wireless communication technologies, such as cellular, Wi-Fi, Bluetooth, and dedicated short-range communication (DSRC). This enables them to share information about their location, speed, direction, and intentions, and to receive information about the traffic conditions, road hazards, and optimal routes.
The level of autonomy of self-driving cars can vary according to the degree of human involvement and intervention required. The Society of Automotive Engineers (SAE) has defined six levels of automation for self-driving cars, ranging from level 0 (no automation) to level 5 (full automation). The levels are summarized in Table 1.
| Level | Name | Description |
| --- | --- | --- |
| 0 | No automation | The human driver performs all the driving tasks and has full control of the vehicle. |
| 1 | Driver assistance | The vehicle can assist the human driver with some driving tasks, such as steering or braking, but the human driver must monitor the environment and remain in control of the vehicle. |
| 2 | Partial automation | The vehicle can perform some driving tasks, such as steering and braking, simultaneously, but the human driver must monitor the environment and be ready to take over the control of the vehicle at any time. |
| 3 | Conditional automation | The vehicle can perform all the driving tasks under certain conditions, such as on highways or in good weather, but the human driver must be ready to intervene when the vehicle requests or when the conditions change. |
| 4 | High automation | The vehicle can perform all the driving tasks under certain conditions, such as on highways or in good weather, and the human driver does not need to intervene or monitor the environment, but the vehicle may not be able to operate in all situations or locations. |
| 5 | Full automation | The vehicle can perform all the driving tasks in all situations and locations, and the human driver does not need to intervene or monitor the environment at any time. |
Table 1: Levels of automation for self-driving cars (adapted from )
Vehicle-to-infrastructure (V2I) communication is a type of wireless communication that enables self-driving cars to exchange information with the road infrastructure, such as traffic lights, signs, cameras, and sensors. V2I communication can enhance the safety, efficiency, and sustainability of the transportation system by providing self-driving cars with real-time and accurate information about the traffic conditions, road hazards, and optimal routes. V2I communication can also enable the road infrastructure to control and coordinate the movements of self-driving cars, such as changing the traffic signals, adjusting the speed limits, and managing the traffic flow. V2I communication can use different wireless communication technologies, such as cellular, Wi-Fi, Bluetooth, and DSRC. DSRC is a dedicated wireless communication technology that operates in the 5.9 GHz band and has a range of up to 300 meters. DSRC is designed to provide low-latency, high-reliability, and secure communication for V2I and vehicle-to-vehicle (V2V) applications.
Review of the potential benefits of self-driving cars and vehicle-to-infrastructure communication, such as improving road safety, reducing congestion, lowering carbon emissions, and increasing efficiency and comfort for travelers.
Self-driving cars and V2I communication have the potential to provide significant benefits for the transportation system and the society, such as:
- Improving road safety: Self-driving cars and V2I communication can reduce the number and severity of traffic accidents, which are mainly caused by human errors, such as speeding, distraction, fatigue, and impairment. Self-driving cars can avoid human errors by using sensors, cameras, and artificial intelligence to monitor the environment and make decisions. V2I communication can provide self-driving cars with additional information and guidance from the road infrastructure, such as warning about road hazards, changing the traffic signals, and coordinating the movements of self-driving cars. According to a study by the RAND Corporation, self-driving cars could prevent 90% of the crashes that occur in the U.S. every year, saving thousands of lives and billions of dollars.
- Reducing congestion: Self-driving cars and V2I communication can reduce the traffic congestion, which is caused by factors such as inefficient driving behavior, uneven traffic demand, and road incidents. Self-driving cars can reduce congestion by driving more smoothly, efficiently, and cooperatively, such as maintaining optimal speed and distance, changing lanes and merging smoothly, and forming platoons. V2I communication can reduce congestion by providing self-driving cars with real-time and accurate information about the traffic conditions, and by managing the traffic flow, such as adjusting the speed limits, optimizing the traffic signals, and rerouting the traffic. According to a study by the Boston Consulting Group, self-driving cars and V2I communication could reduce the travel time and the fuel consumption by 40% in urban areas.
- Lowering carbon emissions: Self-driving cars and V2I communication can lower the carbon emissions, which are caused by the combustion of fossil fuels in the transportation sector. Self-driving cars can lower the carbon emissions by driving more efficiently, reducing the fuel consumption and the engine idling, and by choosing the optimal routes and modes of transportation. V2I communication can lower the carbon emissions by providing self-driving cars with information and incentives to reduce the fuel consumption and the engine idling, such as changing the traffic signals, adjusting the speed limits, and promoting the use of public transportation and electric vehicles. According to a study by the International Transport Forum, self-driving cars and V2I communication could reduce the carbon emissions by 60% in urban areas.
- Increasing efficiency and comfort for travelers: Self-driving cars and V2I communication can increase the efficiency and comfort for travelers, by providing them with more options, convenience, and enjoyment. Self-driving cars can increase the efficiency and comfort for travelers by allowing them to choose the level of automation, the type of vehicle, and the mode of transportation, according to their preferences, needs, and budget. Self-driving cars can also provide travelers with more convenience and enjoyment, by allowing them to use the travel time for other activities, such as working, reading, or relaxing. V2I communication can increase the efficiency and comfort for travelers by providing them with information and services from the road infrastructure, such as navigation, entertainment, and payment. V2I communication can also provide travelers with more options and convenience, by enabling the integration and coordination of different modes of transportation, such as public transportation, car-sharing, bike-sharing, and ride-hailing. According to a study by the World Economic Forum, self-driving cars and V2I communication could increase the mobility and accessibility of travelers by 40% in urban areas.
Highlighting the challenges and risks associated with self-driving cars and vehicle-to-infrastructure communication, such as ethical, legal, social, security, technological, and economic issues.
Self-driving cars and V2I communication also pose significant challenges and risks that need to be addressed before they can be widely adopted and accepted, such as:
- Ethical issues: Self-driving cars and V2I communication raise ethical questions and dilemmas, such as who is responsible for the actions and decisions of self-driving cars, how to ensure the fairness and transparency of the algorithms and data used by self-driving cars and V2I communication, and how to balance the trade-offs between the individual and the collective interests and values. For example, how should a self-driving car react in a situation where it has to choose between saving its passengers or saving other road users, such as pedestrians or cyclists? How should a V2I communication system prioritize and allocate the road resources among different self-driving cars, such as public or private, shared or personal, electric or conventional?
- Legal issues: Self-driving cars and V2I communication create legal challenges and uncertainties, such as how to define and regulate the liability and accountability of the manufacturers, operators, owners, and users of self-driving cars and V2I communication, how to protect the privacy and security of the data and information exchanged by self-driving cars and V2I communication, and how to harmonize the laws and standards across different jurisdictions and regions. For example, who should be held liable in case of a crash involving a self-driving car, the manufacturer, the operator, the owner, or the user? How should the data and information collected and shared by self-driving cars and V2I communication be stored, processed, and accessed, and by whom? How should the laws and standards for self-driving cars and V2I communication be aligned and coordinated among different countries and regions?
- Social issues: Self-driving cars and V2I communication have social implications and impacts, such as how to ensure the social acceptance and trust of the public and the stakeholders towards self-driving cars and V2I communication, how to address the potential social and cultural changes and conflicts caused by self-driving cars and V2I communication, and how to promote the social inclusion and equity of the diverse and vulnerable groups and communities affected by self-driving cars and V2I communication. For example, how to increase the public and the stakeholders' awareness and understanding of the benefits and risks of self-driving cars and V2I communication, and how to involve them in the design and development of self-driving cars and V2I communication? How to cope with the possible changes and conflicts in the social and cultural norms and values, such as the sense of ownership, identity, and responsibility, caused by self-driving cars and V2I communication? How to ensure that self-driving cars and V2I communication are accessible and affordable for everyone, regardless of their age, gender, income, location, or disability?
- Security issues: Self-driving cars and V2I communication face security threats and risks, such as how to prevent and protect self-driving cars and V2I communication from cyberattacks, hacking, and sabotage, how to detect and respond to the security incidents and breaches involving self-driving cars and V2I communication, and how to ensure the resilience and recovery of the self-driving cars and V2I communication systems in case of emergencies and disasters. For example, how to secure the communication channels and networks used by self-driving cars and V2I communication, and how to encrypt and authenticate the data and information exchanged by self-driving cars and V2I communication? How to monitor and identify the potential security vulnerabilities and attacks on self-driving cars and V2I communication, and how to alert and notify the relevant authorities and parties? How to restore and resume the normal operation and function of self-driving cars and V2I communication in case of disruptions and damages caused by natural or human-made hazards?
- Technological issues: Self-driving cars and V2I communication require technological innovations and advancements, such as how to improve the performance and reliability of the sensors, cameras, and artificial intelligence used by self-driving cars and V2I communication, how to ensure the interoperability and compatibility of the different technologies and systems used by self-driving cars and V2I communication, and how to test and validate the safety and functionality of self-driving cars and V2I communication. For example, how to enhance the accuracy and robustness of the sensors, cameras, and artificial intelligence that enable self-driving cars and V2I communication to perceive and understand the environment and make decisions? How to ensure that self-driving cars and V2I communication can communicate and cooperate with each other and with other road users, such as human drivers, pedestrians, cyclists, and animals, using different communication technologies and protocols? How to design and conduct rigorous and realistic experiments and simulations to evaluate and verify the safety and functionality of self-driving cars and V2I communication under various scenarios and conditions?
- Economic issues: Self-driving cars and V2I communication have economic implications and impacts, such as how to estimate and justify the costs and benefits of self-driving cars and V2I communication, how to allocate and distribute the costs and benefits of self-driving cars and V2I communication among different actors and sectors, and how to manage the potential economic changes and transitions caused by self-driving cars and V2I communication. For example, how to measure and compare the costs and benefits of self-driving cars and V2I communication, such as the initial investment, the operational and maintenance costs, the environmental and social benefits, and the revenue and profit? How to share and balance the costs and benefits of self-driving cars and V2I communication among different actors and sectors, such as the manufacturers, operators, owners, users, governments, and society? How to deal with the possible changes and transitions in the economic structure and activities, such as the employment, the productivity, and the competitiveness, caused by self-driving cars and V2I communication?
Review of the latest developments and innovations in the field of self-driving cars and vehicle-to-infrastructure communication, such as the ability to see beyond the corner, creating an integrated ecosystem, and new applications in areas such as freight and emergency transportation.
Self-driving cars and V2I communication are constantly evolving and improving, thanks to the efforts and collaborations of various actors and sectors, such as the academia, the industry, the government, and the society. Some of the latest developments and innovations in the field of self-driving cars and V2I communication are:
- The ability to see beyond the corner: Researchers from the Massachusetts Institute of Technology (MIT) have developed a system that enables self-driving cars to see around corners and detect hidden objects, such as pedestrians, cyclists, or animals, using wireless signals. The system, called CornerCameras, uses a camera and a computer to capture and analyze the changes in the shadows and reflections of the wireless signals on the ground or on the walls, caused by the movements of the hidden objects. The system can then reconstruct the shape, size, and speed of the hidden objects, and alert the self-driving car to avoid potential collisions. The system can work in different weather and lighting conditions, and can complement the existing sensors and cameras used by self-driving cars.
- Creating an integrated ecosystem: A consortium of companies and organizations, led by the Toyota Research Institute, have launched a project to create an integrated ecosystem for self-driving cars and V2I communication, called the Automated Vehicle Interaction and Data Exchange (AVIDE) platform. The platform aims to enable the seamless and secure exchange of data and information among self-driving cars, road infrastructure, and other road users, using blockchain and cloud technologies. The platform also aims to provide various services and applications for self-driving cars and V2I communication, such as navigation, entertainment, payment, and insurance. The platform is expected to enhance the safety, efficiency, and sustainability of the transportation system, and to create new business opportunities and value for the stakeholders.
- New applications in areas such as freight and emergency transportation: Self-driving cars and V2I communication have the potential to transform and improve various areas and sectors, such as freight and emergency transportation. For example, self-driving trucks and vans can deliver goods and packages more efficiently, reliably, and cost-effectively, using V2I communication to optimize the routes and schedules, and to coordinate with other vehicles and infrastructure. Self-driving ambulances and fire trucks can respond to emergencies faster and safer, using V2I communication to clear the traffic and access the scene, and to communicate with the hospitals and the fire stations. Self-driving cars and V2I communication can also enable new modes and models of transportation, such as autonomous ride-hailing, car-sharing, and mobility-as-a-service. These new modes and models of transportation can provide more convenience, flexibility, and affordability for travelers, and can also create new business opportunities and value for the service providers and the platform operators.
Analysis of the factors influencing the diffusion and acceptance of self-driving cars and vehicle-to-infrastructure communication, such as trust, awareness, regulation, cost, infrastructure, and collaboration among stakeholders.
The diffusion and acceptance of self-driving cars and V2I communication depend on various factors, such as:
- Trust: Trust is the degree of confidence and willingness of the public and the stakeholders to use and support self-driving cars and V2I communication, based on their perception of the benefits, risks, and reliability of these technologies. Trust is influenced by factors such as the level of automation, the user experience, the media coverage, the social influence, and the personal characteristics of the public and the stakeholders. Trust is essential for the diffusion and acceptance of self-driving cars and V2I communication, as it affects the adoption and usage behavior, the satisfaction and loyalty, and the advocacy and recommendation of these technologies.
- Awareness: Awareness is the degree of knowledge and understanding of the public and the stakeholders about the features, functions, and impacts of self-driving cars and V2I communication, based on their exposure to and interaction with these technologies. Awareness is influenced by factors such as the availability and accessibility of information, the quality and credibility of information, the frequency and intensity of communication, and the diversity and relevance of communication channels. Awareness is important for the diffusion and acceptance of self-driving cars and V2I communication, as it affects the perception and attitude, the curiosity and interest, and the learning and feedback of these technologies.
- Regulation: Regulation is the degree of control and guidance of the authorities and the regulators over the development and deployment of self-driving cars and V2I communication, based on their evaluation of the legal, ethical, social, and economic implications and impacts of these technologies. Regulation is influenced by factors such as the policy objectives and priorities, the legal frameworks and standards, the enforcement mechanisms and incentives, and the stakeholder participation and consultation. Regulation is crucial for the diffusion and acceptance of self-driving cars and V2I communication, as it affects the safety and security, the privacy and accountability, and the innovation and competition of these technologies.
- Cost: Cost is the degree of affordability and profitability of self-driving cars and V2I communication, based on their comparison of the expenses and revenues of these technologies. Cost is influenced by factors such as the initial investment and installation, the operational and maintenance, the environmental and social, and the revenue and profit. Cost is significant for the diffusion and acceptance of self-driving cars and V2I communication, as it affects the demand and supply, the value and quality, and the sustainability and scalability of these technologies.
- Infrastructure: Infrastructure is the degree of availability and suitability of the physical and digital facilities and networks that support and enable the operation and function of self-driving cars and V2I communication, based on their assessment of the capacity and compatibility of these technologies. Infrastructure is influenced by factors such as the design and construction, the upgrade and maintenance, the integration and interoperability, and the resilience and recovery. Infrastructure is vital for the diffusion and acceptance of self-driving cars and V2I communication, as it affects the performance and reliability, the efficiency and convenience, and the flexibility and adaptability of these technologies.
- Collaboration: Collaboration is the degree of cooperation and coordination among the various actors and sectors involved in and affected by self-driving cars and V2I communication, based on their recognition of the interdependence and complementarity of these technologies. Collaboration is influenced by factors such as the vision and strategy, the roles and responsibilities, the communication and information, and the trust and commitment. Collaboration is beneficial for the diffusion and acceptance of self-driving cars and V2I communication, as it affects the alignment and harmonization, the innovation and learning, and the synergy and value of these technologies.
Prediction of the possible future of self-driving cars and vehicle-to-infrastructure communication, and evaluation of the opportunities and challenges that await us in this field, and providing recommendations or suggestions for achieving the best outcomes.
Self-driving cars and V2I communication are expected to have a profound and transformative impact on the future of transportation and society, creating new opportunities and challenges that require careful and proactive planning and management. Some of the possible scenarios and implications of self-driving cars and V2I communication are:
- A safer and smarter transportation system: Self-driving cars and V2I communication could create a safer and smarter transportation system, where traffic accidents, congestion, and emissions are significantly reduced, and where travelers can enjoy more options, convenience, and comfort. Self-driving cars and V2I communication could also enable new modes and models of transportation, such as autonomous ride-hailing, car-sharing, and mobility-as-a-service, that could provide more accessibility and affordability for travelers, and create new business opportunities and value for service providers and platform operators.
- A more connected and integrated society: Self-driving cars and V2I communication could create a more connected and integrated society, where people can communicate and interact with each other and with the environment more easily and efficiently, and where the physical and digital worlds are seamlessly blended. Self-driving cars and V2I communication could also enable new forms and functions of social and cultural activities, such as entertainment, education, and health, that could enhance the quality of life and well-being of people, and create new social and cultural values and norms.
- A more dynamic and diverse economy: Self-driving cars and V2I communication could create a more dynamic and diverse economy, where the productivity and competitiveness of various sectors and industries are improved, and where new markets and opportunities are created and explored. Self-driving cars and V2I communication could also enable new sources and streams of data and information, that could generate new insights and knowledge, and create new value and innovation.
However, self-driving cars and V2I communication also pose significant challenges and risks that need to be addressed and mitigated, such as:
- Ethical, legal, and social issues: Self-driving cars and V2I communication raise ethical, legal, and social issues that need to be resolved and regulated, such as the responsibility and accountability of the actions and decisions of self-driving cars and V2I communication, the privacy and security of the data and information exchanged by self-driving cars and V2I communication, and the fairness and transparency of the algorithms and data used by self-driving cars and V2I communication. Self-driving cars and V2I communication also have social implications and impacts that need to be considered and managed, such as the social acceptance and trust of the public and the stakeholders, the social and cultural changes and conflicts, and the social inclusion and equity of the diverse and vulnerable groups and communities.
- Security and resilience issues: Self-driving cars and V2I communication face security and resilience issues that need to be prevented and protected, such as the cyberattacks, hacking, and sabotage of self-driving cars and V2I communication, the detection and response to the security incidents and breaches, and the resilience and recovery of the self-driving cars and V2I communication systems in case of emergencies and disasters.
- Technological and infrastructural issues: Self-driving cars and V2I communication require technological and infrastructural issues that need to be improved and maintained, such as the performance and reliability of the sensors, cameras, and artificial intelligence, the interoperability and compatibility of the different technologies and systems, and the testing and validation of the safety and functionality of self-driving cars and V2I communication. Self-driving cars and V2I communication also require the availability and suitability of the physical and digital facilities and networks that support and enable their operation and function, such as the design and construction, the upgrade and maintenance, the integration and interoperability, and the resilience and recovery.
- Economic and environmental issues: Self-driving cars and V2I communication have economic and environmental issues that need to be estimated and justified, such as the costs and benefits of self-driving cars and V2I communication, the allocation and distribution of the costs and benefits among different actors and sectors, and the management of the potential economic changes and transitions caused by self-driving cars and V2I communication. Self-driving cars and V2I communication also have environmental implications and impacts that need to be measured and mitigated, such as the carbon emissions, the energy consumption, and the resource utilization of self-driving cars and V2I communication.
To achieve the best outcomes of self-driving cars and V2I communication, some of the recommendations or suggestions are:
- Developing and implementing a clear and coherent vision and strategy for self-driving cars and V2I communication, that defines the objectives and priorities, the roles and responsibilities, the milestones and indicators, and the resources and budgets of self-driving cars and V2I communication.
- Establishing and enforcing a comprehensive and consistent legal and regulatory framework for self-driving cars and V2I communication, that addresses the ethical, legal, and social issues, protects the privacy and security of the data and information, and harmonizes the laws and standards across different jurisdictions and regions.
- Enhancing and promoting the public and stakeholder awareness and understanding of self-driving cars and V2I communication, by providing accurate and credible information, engaging and involving them in the design and development, and soliciting and incorporating their feedback and suggestions.
- Investing and supporting the technological and infrastructural innovation and advancement of self-driving cars and V2I communication, by fostering and facilitating the research and development, testing and validation, and deployment and operation of self-driving cars and V2I communication.
- Evaluating and balancing the economic and environmental costs and benefits of self-driving cars and V2I communication, by measuring and comparing the expenses and revenues, allocating and distributing the costs and benefits, and managing and mitigating the potential changes and transitions of self-driving cars and V2I communication.
- Fostering and strengthening the collaboration and coordination among the various actors and sectors involved in and affected by self-driving cars and V2I communication, by sharing and aligning the vision and strategy, communicating and exchanging the information and data, and creating and delivering the value and innovation of self-driving cars and V2I communication.
Conclusion:
Self-driving cars and V2I communication are emerging and disruptive technologies that have the potential to revolutionize and improve the transportation system and the society, by providing significant benefits, such as improving road safety, reducing congestion, lowering carbon emissions, and increasing efficiency and comfort for travelers. However, self-driving cars and V2I communication also pose significant challenges and risks that need to be addressed and mitigated, such as ethical, legal, social, security, technological, and economic issues. Therefore, it is important to conduct a comprehensive and balanced analysis of the technologies, opportunities, and risks of self-driving cars and V2I communication, and to develop and implement effective and proactive policies and measures to achieve the best outcomes of self-driving cars and V2I communication. Self-driving cars and V2I communication are not only technologies, but also visions and choices for the future of transportation and society.