Next Generation of Intelligent Transportation Systems and Vehicles: Combining Human and Engineering Factors

Dear Colleagues,

The much-promised adoption of so-called driverless cars or automated vehicles (AV) at SAE level 3 and above has been slow. In spite of initial optimism and having received considerable investment, concepts considered exciting in 2010s have seldom advanced to high technology readiness levels (TRLs) or progressed beyond proof of concept demonstrators. The economic underpinnings of such technologies remain uncertain. Moreover, the potential of automated aviation services, such as drone deliveries or automated passenger services, appears to be on the cusp of suffering this same fate. This course of events may be attributable to hard robotics problems emerging from the application of general artificial intelligence and robotic methods which are required to tackle the real world of transportation. Alternatively, this slowdown may be due to the problems of designing automation with a human in the loop, such as safety issues arising from takeover requests (TORs).

On the other hand, the promise of automation in some domains is gradually being realized using achievable automation as a means to address clearly identifiable existing transportation needs or new opportunities emerging from technologies such as convolution neural networks, sensor fusion, and workload support for pilots. These new integrated technologies require proven interface designs, safe and serviceable equipment, and realizable economic models at higher TRLs. Importantly, they must also address demanding legal certification and regulatory requirements.

Irrespective of the potential of emerging technologies, one common factor that has arisen is the set of difficulties arising from failures to properly consider the human context of use, at the individual, passenger, and also at the social level. Engineering often misses the societal context of new technology and its implications for human behavior and infrastructure. There is a dearth of research looking at factors ranging from the economic to stakeholder-based, societal, decarbonization-focused, and human factors; acting in conjunction with proposed new configurations of technologies. Hence, this special Issue seeks to attract papers addressing solutions in novel areas combining precisely scoped and engineered automation, electrification, disabled access, net-zero power sources, and specific engineering problems—such as those tackling issues of highway driving, rural mobility, or sub-regional aviation. Papers should detail applications for real-world usage cases with a prospect of implementation in the near future (i.e., within the next five years).

Topics of interest for this Special Issue include, but are not restricted to:

Applications

1. The case for self-driving public transport and shared vehicles, including buses and cars;
2. Unmanned aerial vehicles (UAVs) for the transport of goods and medical supplies or for emergency response;
3. Business models for automated aviation; advanced air mobility (AAM), and sub-regional air transport;
4. Inclusion through automated support of driving and mobility—i.e. essential travel.

Human Behavior

5. User acceptance and the perceived need for automation;
6. Behavioral approaches to mode shifting towards sustainable and active travel;
7. Training people to use and understand automated technologies.

Infrastructure

8. Barriers and facilitators for automated vehicle infrastructure—citing issues that include power, the built environment, and local governance;
9. Designing automated transportation into smart cities; intelligent or AI-facilitated control for road infrastructure;
10. Communication strategies for vehicles, road infrastructure, and traffic management.

Prof. Dr. Pat Langdon
Dr. Grigorios Fountas
Guest Editors

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• intelligent transport
• autonomous vehicles
• UAVs
• AAM
• inclusive transport
• user acceptance
• mode shifting
• automation training
• automated vehicle infrastructure
• smart city transportation
• communication for traffic management