Dissolving Boundaries with Autonomous Driving: An Engineer's Perspective on Real Estate 'Mobilization' and Tokyo's Transformation

"Real Estate Becoming Mobile Property"—The Paradigm Shift Brought by Autonomous Driving

When I began thinking about the future of autonomous driving, what came to mind was the seemingly contradictory concept of "real estate becoming mobile property." This is not merely wordplay, but a profound question suggesting that the evolution of technology may fundamentally change the foundations of society.

Recently, during a conversation with an investor, I was asked, "What impact will autonomous driving have on Tokyo?" Despite having some ideas, I couldn't immediately answer. While I could imagine the technological implications, how they would transform real estate values, urban structure, and even lifestyles was more complex and far-reaching than anticipated. So I decided to research deeply and compile my thoughts.

Particularly as a new father, I've also become interested in the intersection of childcare and autonomous driving. Just as I was contemplating intimate parenting and work coexistence in the AI era, I began wondering how autonomous driving might influence childcare environments and family mobility.

Reexamining the Boundaries Between Mobility and Housing

Automobiles have had a decisive influence on urban formation over the past 100 years. Urban planning in the 20th century was reconstructed based on the proliferation of private cars—the development of suburbs, the maintenance of highway networks, and the securing of vast parking spaces. All of these were designed around human-driven cars.

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However, when humans are liberated from driving, this relationship is fundamentally overturned. I see this change not as "liberation from automobiles" but as "a new symbiosis with automobiles."

Since becoming a parent, I've experienced a shift in my perception of mobility. Moving with children involves far more preparation and constraints than I imagined. Even a seemingly simple act like "taking a child on the train" requires surprisingly much effort. From this experience, I strongly feel that the changes brought by autonomous driving go beyond mere convenience improvements—they represent a fundamental transformation in our way of living.

The Current State and Future of Autonomous Driving Technology

Before considering the social transformation that autonomous driving will bring, we need to understand the current state of the technology and its future prospects accurately. As an engineer, and as someone standing at the intersection of technology and society, I want to assess this evolutionary process objectively.

I believe that it's important to maintain a realistic outlook between excessive expectations and pessimism about autonomous driving. How can we have a meaningful discussion between idealistic future predictions and skepticism that says "it's still far off"? This requires a calm analytical approach from both technical feasibility and social acceptability perspectives.

SAE Levels and the Boundaries of System Responsibility

The most widely accepted framework for understanding the developmental stages of autonomous driving technology is the level classification by the Society of Automotive Engineers (SAE). Defined in six stages from Level 0 (completely manual) to Level 5 (fully autonomous), this framework clarifies the division of responsibility between systems and drivers¹.

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As this diagram shows, responsibility begins to shift from humans to systems starting at Level 3. This is not merely a technological evolution but represents a fundamental change in legal and social frameworks. I particularly focus on this "transfer of responsibility" because it harbors the most complex challenges at the intersection of technology and society.

Currently, most vehicles on the market are classified from Level 0 to Level 2. Advanced systems like Tesla's "Autopilot" and GM's "Super Cruise" are legally Level 2². It's important to remember that with these systems, the ultimate responsibility still lies with the driver.

There is a significant gap, both technically and legally, between Level 2 and Level 3. This gap is not just technological but also legal and social. While Level 2 requires drivers to maintain constant supervisory responsibility, Level 3 transfers responsibility to the system under specific conditions. This transfer of responsibility creates complex issues such as legal liability in accidents and establishing safe control transfers from systems to drivers.

As I've deepened my understanding of this field, I've realized that one of the most important concepts is "ODD" (Operational Design Domain). ODD refers to the specific set of conditions under which an autonomous driving system is designed to function safely. These include constraints such as "highways only," "fair weather only," or "speeds below 60 km/h"³. Level 3 and Level 4 systems function only within their defined ODDs.

The real social transformation from autonomous driving will likely come with the realization of Level 4 and Level 5. These levels, where systems can complete driving tasks without driver intervention, will be the critical threshold that triggers the "mobilization of real estate" and changes in urban structure.

The Reality of Global Competition: Comparison of Four Strategic Approaches

Fierce competition in autonomous driving technology development is taking place around the world. However, strategies and progress vary significantly by region. It's important to focus not only on technological superiority but also on the speed and direction of social implementation.

I'm particularly interested in who, why, and how different entities are trying to implement autonomous driving. The differences in motivations among countries and companies significantly influence the direction of technological development and the form of social implementation. We need a multifaceted comparison rather than a one-dimensional assessment of "who is ahead."

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As this diagram illustrates, each region is advancing the development and deployment of autonomous driving technology with different approaches. I believe this diversity itself is driving the global development of autonomous driving. Rather than a single correct answer, diverse solutions emerging from different contexts stimulate each other as they evolve.

Japan's strategic characteristic lies in its social problem-solving approach. Its motivations include securing transportation means in an aging society and addressing the serious driver shortage. In 2020, Honda Legend received type approval as the world's first Level 3 vehicle⁴, and in April 2023, the revised Road Traffic Act institutionalized Level 4-equivalent "specified autonomous operation"⁵. The focus is shifting to the practical implementation of Level 4 services in specific regions.

I empathize with Japan's social approach. Rather than technology for technology's sake, it focuses on solving specific social challenges such as population decline, rural depopulation, and driver shortages—this represents one model of a healthy relationship between technology and society. On the other hand, from a global competitiveness perspective, more bold vision and scalability remain challenges.

Critical Threshold for Realization: What are the Barriers to Level 4/5?

What is the most important threshold in the evolution of autonomous driving? As many experts point out, it's the transition from Level 2 to Level 4. Level 3 is sometimes even referred to as the "non-existent level." This is because the "partial transfer of responsibility" represents an ambiguous state that could potentially increase risks.

The technical barriers to reaching Level 4 include:

1. Difficulty in edge case processing: Systems that function well in standard situations face challenges in unpredictable scenarios (construction sites, unusual weather, unexpected road conditions).
2. Sensor fusion challenges: Technical difficulties in integrating data from multiple sensors such as cameras, radar, and LiDAR to build a consistent world model.
3. Explainability and verification of AI decisions: Insufficient methodologies for explaining machine learning model decisions in human-understandable forms and systematically verifying their safety.

Important social barriers include:

1. Underdeveloped legal responsibility frameworks: New legal systems are needed for responsibility allocation in accidents, data access rights, and privacy protection⁶.
2. Building social trust: Transparent information disclosure and gradual demonstration are essential to gain public trust in the technology's safety.
3. Economic feasibility: Initial Level 4 systems will be expensive, requiring cost reduction and clear business models for market introduction.

I believe the key to overcoming these barriers is not a leap-frog approach but a gradual expansion from specific ODDs. For example, in the initial stages, it would be realistic to start with services limited to relatively predictable environments like highways or specific urban areas, then expand the ODD while accumulating data and experience.

The Transformation Awaiting Tokyo's Urban Space

How will autonomous driving technology, especially from advanced companies, affect Tokyo—a high-density, sophisticated city? This theme requires consideration of the dynamics of the entire social system, not just technological predictions.

Dramatic Change in Mobility Burden and Urban Transportation

One of the biggest changes autonomous driving will bring is the dramatic reduction in physical and mental burden associated with mobility. This is not just a superficial change of "becoming easier" but will deeply influence lifestyles and urban functions.

Consider Tokyo's commuting rush. Currently, many people are forced to endure long commutes on crowded trains. This is not only a source of physical fatigue but also psychological stress. With the proliferation of autonomous vehicles, this travel time can be transformed into valuable time for rest, work, or self-improvement.

"Commuting time" becomes "personal time." This change is more significant than one might imagine. Being freed from driving during movement creates approximately one hour of effective time per day. This time could be used in various ways—reading, thinking, online meetings, and more.

However, an important question arises: How will increased automobile use affect overall urban transportation?

The improved convenience of mobility through autonomous driving may lead to a shift of users from public transportation and an increase in total travel distance⁷. Furthermore, "zero-occupant trips" (e.g., moving to parking lots) could increase traffic volume.

If these factors are not managed, ironically, the increase in autonomous vehicles could worsen congestion in urban centers. This concern cannot be ignored, especially in high-density cities like Tokyo. In fact, I'm focusing on the "paradox of convenience." As things become more convenient, usage increases, potentially worsening overall congestion.

Therefore, the effects of introducing autonomous driving depend greatly on policy decisions about how to incorporate it into urban transportation systems, not just the technology itself. Prioritizing shared autonomous driving services, strengthening connections with public transportation, and usage restrictions in urban centers will be key to maximizing the benefits of autonomous driving while minimizing negative impacts.

Urban Design in the Era of "Mobile Property"

The concept of "mobile property" brought by autonomous driving has the potential to fundamentally transform urban design. The "mobile property" I'm considering here is not simply "moving real estate" but a new spatial concept where the boundaries between fixed and fluid dissolve.

Since becoming a father, I've strongly felt the need to reconsider the relationship between space and function. In conventional cities, "sleeping places," "working places," "learning places," and "playing places" are fixed, and we move between them. However, autonomous driving technology enables the reverse concept—bringing functions to us.

First, let's consider the transformation of parking lots. With the proliferation of autonomous vehicles, the vast parking lots occupying valuable land in urban centers will become unnecessary⁸. Cars can automatically move to less expensive locations in the suburbs after dropping off passengers. The urban space thus freed could be converted to higher-value uses such as housing, green spaces, or cultural facilities.

Next, there's the redefinition of road space. Currently, roads are mostly used only for vehicle transit and parking. However, as cars operate more efficiently, part of the road space could be repurposed for pedestrians, bicycles, or even outdoor cafes and markets—spaces for human interaction.

Even more interesting is the emergence of mobile functional spaces. Functions that were traditionally fixed—offices, stores, medical facilities, and educational facilities—could be mounted on autonomous vehicles and moved as needed. For example, we might see mobile clinics regularly touring different areas or mobile retail stores changing locations according to demand.

From a parenting perspective, this concept of "mobile property" is attractive. If children's medical care, educational activities, and leisure—things families currently must go out for—could be "delivered" near home, the burden on families with children would be greatly reduced.

I've thought about how Tokyo might change with the proliferation of autonomous driving technology over time. This timeline is not a definitive prediction but one vision of the possibilities that could emerge from the co-evolution of technology and society.

Such changes overturn the fundamental premises of urban planning. While urban planning has traditionally been based on "zoning" with fixed uses and functions, we now need to design cities where functions move fluidly. This will require a new process of urban creation involving not only urban planning specialists but also architects, designers, IT engineers, and citizens.

Here, I find an interesting parallel between AI and autonomous driving. As I experienced in AI collaborative development, technology not only makes existing processes more efficient but brings about fundamental redefinition of those processes. Autonomous driving, too, is not just "better cars" but a catalyst that fundamentally questions the relationship between cities and humans.

Redefinition of Real Estate Value: From "Station Proximity" to "Quality of Mobility"

In the Japanese real estate market, "proximity to stations" has long been an absolute value criterion. This is because daily life activities like commuting and shopping have depended on access to public transportation. However, the spread of autonomous driving has the potential to fundamentally change this criterion.

As the temporal and psychological costs of mobility are reduced through autonomous driving, the quality of the mobility experience may become more important than physical distance. For example, there is currently a significant price difference between properties 15 minutes and 30 minutes' walk from a station, but with the spread of door-to-door mobility services, this difference might diminish.

This could relatively enhance the attractiveness of suburbs and rural areas⁹. As commuting pain is reduced and travel time can be used effectively, the barriers to living away from urban centers will lower. In fact, the spread of remote work during the COVID-19 pandemic has already strengthened a suburban orientation, and autonomous driving will likely further encourage this trend.

On the other hand, I predict that urban-specific attractions (employment concentration, cultural and commercial facilities, diverse amenities) will continue to exert strong appeal. The fact that real estate prices in central Tokyo did not significantly decline during the pandemic suggests persistent demand for urban centers.

However, it's important to note that if autonomous driving is introduced without proper management, it could worsen urban traffic congestion, potentially negatively affecting livability and real estate values.

In the autonomous driving era's real estate market, value will be determined by diverse factors such as quality of accessibility and possibility of time utilization during travel, rather than single indicators like "distance to station." For example, new value indicators might emerge, such as proximity to autonomous driving priority lanes or distance from mobility hubs.

Reorganization of Industrial Structures

The spread of autonomous driving has the potential to fundamentally change many existing industries, not just modes of transportation. This is a typical example of disruptive innovation, but by calmly analyzing the process of destruction and creation, we can identify new business opportunities and social values.

As an engineer, I strongly recognize that such transformation is not a simple schema of "victory of new technology" and "defeat of old industries." Rather, I focus on the possibility that a richer industrial ecosystem might emerge from the fusion of existing knowledge and new possibilities.

From Taxis to Parking Lots: From Fragmentation to Integration

The taxi industry will be among the first to experience major impact. The emergence of Level 4/5 autonomous taxis (robotaxis) will eliminate labor costs—the largest cost factor—fundamentally changing fee structures and revenue models¹⁰. Existing taxi companies will be forced to either ride this wave or transition to specialized services.

The current taxi industry is centered around drivers with driving skills and geographical knowledge. However, in the autonomous driving era, the sources of competitiveness will be fleet management and operation technology and the ability to provide value-added services.

As a frequent taxi user, I've found value in drivers beyond mere driving service—suggestions of hidden local attractions or routes to avoid congestion, services unique to humans. A challenge for the taxi industry in the autonomous driving era will be how to preserve and leverage such "human touch."

Next to consider is the transformation of the parking lot business. Parking lots that have occupied valuable urban land may see their necessity greatly reduced¹¹. However, this is not merely a decline but an opportunity for business model transformation.

In the future, parking lots may evolve from simply "places to park cars" to management bases for autonomous fleets. They could potentially create new value as "mobility hubs" with functions such as charging, simple maintenance, cleaning, and data collection. Alternatively, conversion to completely different uses could be an option.

The relationship with public transportation will also change in complex ways. Autonomous shuttles could function as automation of existing bus routes or as last-mile transportation from railway stations, contributing to improved public transportation convenience¹². Conversely, affordable and convenient robotaxis might draw users away from public transportation.

The important point here is breaking away from confrontational structures. Rather than binary oppositions like taxi vs. robotaxi, parking lot vs. autonomous driving, or public transportation vs. individual mobility, the ideal would be the construction of an integrated mobility ecosystem where each complements the others.

The key to this is the concept of MaaS (Mobility as a Service). This approach, which integrates diverse means of transportation such as public transit, sharing services, and autonomous mobility to provide seamless mobility experiences, can be a catalyst for integrating fragmented industries.

Having observed the development of various technologies including AI and autonomous driving, I find it particularly impressive that excellent innovation doesn't "destroy" existing values but "reorganizes" them. For example, smartphones didn't simply replace landline phones but changed the meaning of the act of calling itself, creating a new communication ecosystem. Similarly, autonomous driving has the potential not to destroy existing transportation industries but to reorganize their value, creating a new mobility ecosystem.

Such transformation represents both a threat and a new business opportunity for existing players. Companies that can fearlessly offer innovative value propositions will survive and grow through this transition period.

Insurance and Liability: New Frameworks for Data and Control

I predict that one of the areas facing the most fundamental transformation in the autonomous driving era will be automobile insurance and accident liability frameworks¹³. As an engineer, I believe this issue is not merely a legal or institutional challenge but an important topic related to technical design itself.

Current automobile insurance is based on the premise of "driver fault." However, with Level 3 and higher autonomous driving, the system becomes the driving entity. This transfer of agency makes accident liability ambiguous and necessitates the redesign of insurance systems.

The most important challenge is answering the question of "whose responsibility is it?" The driver? The vehicle manufacturer? The software developer? The infrastructure provider? This delineation is complex both technically and legally. Especially during the transition period, the boundary of responsibility between humans and systems tends to be unclear.

The psychological barrier of "entrusting one's life to others" cannot be ignored either. This psychological hurdle becomes even higher when children are passengers. The issue of psychological trust, not just technical safety, will be a significant challenge for the spread of autonomous driving.

The key here is access to and interpretation of data¹⁴. Autonomous vehicles generate vast amounts of sensor data and system logs. In the event of an accident, this data becomes decisive evidence for determining liability. However, this data is primarily managed by automobile manufacturers, and there are various barriers to its disclosure.

From my perspective, I've analyzed the accident liability and insurance system in the autonomous driving era. The following diagram shows the key elements of this complex challenge and their interrelationships.

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As this diagram shows, the framework for responsibility and insurance in the autonomous driving era has three main aspects: data, location of responsibility, and insurance models. These are intricately intertwined, ultimately working toward the goal of "clarification of responsibility and prompt victim relief." In this challenge, I particularly focus on the role of data. Without a transparent and standardized data management system, it will be difficult to realize a fair and efficient responsibility allocation and insurance system.

Various countries around the world are addressing this challenge with different approaches. Germany has adopted a system that maintains the vehicle owner's strict liability while allowing recourse to manufacturers when system defects are the cause¹⁵. The UK has introduced a model that places initial responsibility on autonomous driving entities.

Common to these is the principle of prioritizing prompt relief for victims. Since determining responsibility takes time, it's important to have a mechanism that first provides relief to victims and then seeks recourse among responsible parties.

As a software engineer, I'm particularly interested in this issue of responsibility. In conventional software development, the impact of bugs was primarily the loss of data or time. However, with autonomous driving AI, bugs can directly impact human lives. This represents an entirely new dimension of ethical and legal responsibility for us engineers. More rigorous processes and transparency will be required from design through implementation, testing, and operation.

For the insurance industry, this change represents both a major challenge and a new business opportunity. While the reduction in accidents due to autonomous driving may lead to decreased premium income, opportunities also arise for new product development such as cyber risk insurance and comprehensive insurance for autonomous fleets.

Insurance companies may also take on new roles such as risk assessment and data analysis, potentially becoming important players in the autonomous driving ecosystem beyond merely compensating for damages.

Throughout this transformation process, we'll need to address challenges such as privacy protection, data ownership rights, and international standardization. The construction of such social and legal frameworks, in parallel with technological development, will form the foundation for the healthy spread of autonomous driving.

As a parent, I'm convinced that this "framework of safety and trust" will be the biggest key to the spread of autonomous driving. No matter how technically excellent, if safety and accident liability remain unclear, adoption will not progress, especially in situations involving children.

Childcare and Autonomous Driving: New Possibilities and Challenges

The development of autonomous driving technology has the potential to bring particularly significant changes to the lives of families with children. Let's consider this from everyday aspects such as dropping off children, school choice, and family mobility.

Can Children Ride Alone in Autonomous Vehicles?

With the realization of autonomous driving Level 4/5, it would technically be possible to send children alone to school or extracurricular activities¹⁶. This could greatly reduce parents' burden and potentially expand children's range of activity.

However, there are important safety concerns:

1. Ensuring children's safety: Monitoring children's behavior inside the vehicle, protection from suspicious persons, emergency response, etc.
2. Safe boarding and alighting management: Monitoring and confirmation that children can safely get in and out.
3. Response to trouble: How to respond in case of accidents, mechanical failures, or children's health issues.

To address these challenges, technical measures such as in-vehicle cameras, two-way communication systems, and emergency call buttons would be essential, along with parental confirmation systems and safety education for children.

From a regulatory perspective, age restrictions for children riding alone and safety standards specific to autonomous vehicles for child transportation would need to be established. Expanding existing school bus guidelines and adapting them to the autonomous driving context could also be considered.

Socially, psychological resistance to "entrusting children to machines" would be a major barrier. Overcoming this would require not only proving the absolute safety of the technology but also transparent information disclosure and building social trust.

From my own experience, I strongly feel that there can be no compromise when it comes to children's safety. Even if technically possible, it's unlikely that children riding alone would be socially accepted immediately. Rather, this would probably be realized only after a considerable period following the general spread of Level 4/5 technology, with sufficient safety records and regulatory development.

New Options: Suburban Living × Urban School Attendance

The spread of autonomous driving will also influence families' residential location choices. In particular, the option of "living in the suburbs while attending schools in urban centers" becomes more realistic.

Currently, many families are forced to either live in urban centers to send children to prestigious urban schools or subject children to long commutes. With autonomous driving, this time could be used for learning or rest, relaxing the constraints of physical distance.

This change could also contribute to reducing educational disparities. As geographical constraints diminish, the separation of residential location and educational opportunities progresses, opening more diverse options to families.

However, there are also concerns about the impact of normalized long-distance commuting on children's daily rhythms and the weakening of relationships with local communities. If children have fewer opportunities to play with friends locally, it could potentially affect their social development. However, I hope that technological progress may comprehensively resolve such issues.

Will the Concept of Drunk Driving Disappear?

With the realization of Level 4/5 autonomous driving, the concept of "driver" itself changes. This forces a reconsideration of the legal concept of "drunk driving"¹⁷.

In Level 4 autonomous vehicles, the system handles all driving tasks and fallback (emergency response) within the defined ODD. Therefore, the human's condition (whether intoxicated or not) does not directly affect the safe operation of the vehicle. Logically, with a Level 4 system functioning normally within its ODD, there should be no safety issue even with intoxicated passengers, but since drivers might still need to handle emergencies, drunk driving would not be permitted with Level 4.

With Level 5, humans become completely passengers, bearing no responsibility related to driving. In this situation, the concept of "drunk driving" itself loses meaning.

However, legal system changes tend to proceed more cautiously than technological evolution. Reconsideration of drunk driving prohibition regulations would involve the following issues:

1. Ensuring system reliability: Methods to verify that it is functioning correctly as Level 4/5
2. Responsibilities beyond driving: How to define responsibilities such as emergency response or as a "manager" of the vehicle
3. Social acceptability: Social resistance to having intoxicated people in vehicles

Discussions on revising such traffic rules have begun in Japan and around the world, but for issues with significant social impact like drunk driving, there is likely to be a time lag between technical possibility and legal permissibility.

From Real Estate to Mobile Property—A New Future Brought by Technology

The thought experiment that began with "real estate becoming mobile property" ultimately led to an exploration of a new relationship between technology and humanity. In the future city where autonomous vehicles run, what values do we want to cherish, and what kind of life do we want to realize? The journey to find answers to these questions has only just begun.

As we've seen throughout this article, the realization of autonomous driving technology, especially Level 4/5, has the potential to promote fundamental reorganization not just of means of transportation but of urban structure, residential patterns, industrial structure, and daily life.

Our responsibility as engineers is to understand the possibilities of such changes and guide the direction of technological development not just toward efficiency and convenience improvements but toward human-centered value creation. Through dialogue with diverse stakeholders, we need to direct autonomous driving technology to contribute to the realization of a more equitable, sustainable, and creative society.

As a parent and as an engineer, I feel both excitement and caution about the future that autonomous driving will bring. While believing in the power of technology, I want to consider its impacts from multiple angles and aim for technological development that leads to human-like living and a sustainable society.

In an era where the boundaries between "real estate" and "mobile property" begin to dissolve, what new values can we create? The journey to find that answer has just begun.

References

Footnotes

1. Classification and Definition of Automated Driving Systems for Automobiles - SAE J3016:2021 Japanese Reference Translation ↩

2. What Level is Tesla's Autonomous Driving? A Thorough Explanation - Solar Power ↩

3. What are Autonomous Driving Levels? An Easy Explanation in 10 Minutes - Net Attest ↩

4. Progress of Initiatives Related to Autonomous Driving - Ministry of Land, Infrastructure, Transport and Tourism ↩

5. FY 2024 Research Report on the Expansion of Autonomous Driving - National Police Agency ↩

6. Transformation of the Insurance Industry Caused by Autonomous Driving and Its Response - Japan Society of Insurance Science ↩

7. Research on the Impact of Autonomous Driving on Urban Development - Japan Urban Planning Association ↩

8. Urban Planning Changes with the Spread of Autonomous Unmanned Taxis: The Future of Parking Lots and New Business Opportunities - note ↩

9. Good Timing for Early Acquisition? How Autonomous Driving and COVID are Changing the Value of Regional Real Estate - Autonomous Driving Lab ↩

10. Funai Soken: Future Points and Outlook for the Transportation and Taxi Industry in 2025 - Jinzai Business ↩

11. How Will Demand for Coin Parking Change When Autonomous Vehicles Become Widespread - Showa Park ↩

12. Demand Analysis for Terminal-Type Autonomous Driving Services to Public Transportation Networks - Institute of Transportation Economics ↩

13. Emerging Risks in the Non-Life Insurance Industry Brought by Autonomous Driving Technology - Accenture ↩

14. Research Report on Civil Liability and Social Acceptability of Autonomous Driving - Ministry of Economy, Trade and Industry ↩

15. Survey on the Latest Trends in Legislation of Autonomous Driving Overseas - Ministry of Land, Infrastructure, Transport and Tourism ↩

16. Guidelines for Improving Vehicle Safety of Child-Specific Vehicles - Ministry of Land, Infrastructure, Transport and Tourism ↩

17. X-Day for "Zero Drunk Driving" with Autonomous Driving - Autonomous Driving Lab ↩