1. Introduction

Public transport is a cornerstone of sustainable urban living, supporting economic growth, reducing congestion, and lowering emissions. The integration of autonomous technologies into public transport systems introduces promising opportunities to enhance safety, efficiency, and accessibility. As cities worldwide explore smart transport solutions, autonomous public transport has emerged as a viable, long-term investment. From self-driving buses to automated metros, this technological evolution is central to modern urban planning ^[1].

Autonomous public transport refers to systems where vehicles operate without direct human control, guided by advanced technologies such as artificial intelligence (AI), machine learning (ML), LiDAR, GPS, and vehicle-to-everything (V2X) communication. The goal is to provide reliable, safe, and cost-effective mobility for a growing urban population.

2. Technological Foundations of Autonomous Public Transport

The backbone of autonomous public transport consists of multiple interrelated technologies:

• Sensor Systems: Cameras, LiDAR, ultrasonic sensors, and radar detect obstacles, monitor surroundings, and interpret road signs.

• Global Positioning Systems (GPS) and Inertial Measurement Units (IMUs) provide real-time location data.

• Artificial Intelligence and Machine Learning: AI algorithms interpret sensor data, make driving decisions, and adapt to complex environments.

• V2X Communication: Vehicle-to-infrastructure and vehicle-to-vehicle communication allows for predictive routing and accident avoidance.

These technologies enable autonomous vehicles (AVs) to perform tasks such as lane keeping, obstacle avoidance, adaptive cruising, and precise stopping, essential for urban public transport scenarios.

Examples of implementations include the Navya and EasyMile autonomous shuttles, which are already in pilot phases across Europe, North America, and parts of Asia.

3. Benefits of Autonomous Public Transport

3.1. Environmental Impact

Autonomous public transport systems are frequently electric, contributing to lower greenhouse gas emissions ^[2]. Efficient driving patterns enabled by automation (e.g., smooth acceleration, predictive braking) reduce energy use. According to a study by Fagnant & Kockelman, autonomous electric fleets could reduce CO₂ emissions by up to 50% in urban areas ^[3].

3.2. Reduced Congestion and Optimized Traffic Flow

Autonomous public transport can dynamically respond to real-time traffic conditions, enabling smoother flow and better congestion management. Platooning and connected vehicle technology allow AVs to maintain optimal spacing, improving road capacity and reducing travel times.

3.3. Accessibility and Inclusivity

By reducing reliance on human drivers, autonomous public transport systems can provide mobility solutions for elderly individuals, persons with disabilities, and those without driver's licenses. The design of AVs also allows for custom configurations to meet accessibility standards.

3.4. Operational Efficiency and Cost Reduction

Automation eliminates the need for a human driver, potentially reducing labor costs. Maintenance can also be streamlined through predictive diagnostics, and 24/7 operations can be achieved without fatigue limitations.

4. Current Global Implementations

Several cities have begun testing or deploying autonomous public transport:

• Helsinki, Finland: The Sohjoa project introduced driverless minibuses to public roads, focusing on first- and last-mile connectivity.

• Singapore: Autonomous buses are tested on fixed routes with dedicated lanes, supported by strong regulatory frameworks and smart infrastructure.

• Phoenix, USA: Waymo’s autonomous fleet operates a ride-hailing service with potential integration into public transport.

• China: Baidu’s Apollo Go initiative is developing autonomous bus networks in urban centers, particularly in cities like Wuhan and Chongqing.

These initiatives are generally structured around limited geofenced areas and under the supervision of safety operators.

5. Urban Planning and Infrastructure

For successful integration, autonomous public transport requires urban environments tailored to their operation:

• Dedicated Lanes: Reduces interaction with human-driven vehicles and increases safety.

• Smart Traffic Signals: Adjust to the presence of autonomous fleets.

• Charging Stations: Widespread electric charging infrastructure must support AV operations.

• Digital Infrastructure: Includes high-speed networks for communication, cloud computing resources, and centralized fleet management systems.

City planners must consider new zoning laws, reallocation of road space, and data privacy policies to accommodate AVs ^[4].

6. Safety and Regulatory Challenges

Autonomous public transport introduces novel safety and legal considerations ^[5]:

6.1. Technical Reliability

While AVs have made significant progress, adverse weather, unpredictable pedestrian behavior, and complex traffic scenarios remain challenges. Fail-safe systems and real-time human override mechanisms are crucial.

6.2. Cybersecurity and Data Protection

AVs generate and transmit vast quantities of data, making them vulnerable to hacking. Robust cybersecurity protocols must be established to protect users and maintain public trust.

6.3. Ethical Decision-Making

Autonomous systems face ethical dilemmas in emergency scenarios. Algorithms must be transparent and aligned with societal norms, prompting debate on “machine ethics.”

6.4. Legal and Liability Frameworks

Who is responsible in case of an accident—manufacturer, operator, or software developer? Laws are evolving but remain inconsistent across jurisdictions. Harmonized global standards are necessary.

7. Economic and Social Implications

7.1. Employment Displacement

Widespread automation in public transport may displace professional drivers. However, it also creates new jobs in AI development, fleet maintenance, cybersecurity, and infrastructure management.

7.2. Public Acceptance

Public perception remains a barrier. Concerns over safety, privacy, and reliability hinder adoption. Pilot programs, education campaigns, and user trials are important for building trust.

7.3. Equity Considerations

Autonomous services must be designed inclusively to avoid widening the mobility gap. Pricing, service coverage, and accessibility features must be carefully planned to benefit all social groups.

8. Environmental Considerations and Lifecycle Analysis

Although AVs may reduce direct emissions, their environmental benefits must be considered across the full lifecycle:

• Manufacturing Footprint: AVs require rare earth metals and advanced electronics that have higher production footprints.

• Battery Recycling: Proper end-of-life management is crucial for electric AV sustainability.

• Energy Source: The net benefit depends on whether electricity is sourced from renewables.

9. Future Outlook and Innovation Trends

The next decade is poised to witness significant progress:

• Level 5 Autonomy: Full autonomy in public transport with no human oversight.

• Mobility-as-a-Service (MaaS): Seamless integration of AVs into multimodal mobility platforms.

• AI Improvements: More robust deep learning systems for navigating unstructured environments.

• Green Technologies: Hydrogen-powered AVs and carbon-neutral materials in construction.

Countries leading in autonomous innovation (e.g., Germany, South Korea, the USA, and Japan) are investing heavily in R&D, pilot programs, and cross-sector collaborations to shape this future.

10. Conclusion

Autonomous public transport holds the potential to revolutionize urban mobility by enhancing sustainability, safety, and accessibility. While the path forward involves technological, infrastructural, and regulatory hurdles, its promise is undeniable. Through thoughtful implementation, collaborative policymaking, and community engagement, autonomous public transport can be a central pillar of future smart cities.