Research Topic

AI and Safe Autonomous Driving

About this Research Topic

Current transportation and mobility systems will soon be transformed to a new era by the advent of new technologies associated with connectivity and automation in vehicles. Connectivity enables the flow refinement of data, leading to better information and smoother journeys for the travelling public. At the same time, automation yields increased safety and new ways of helping people become more productive. The combination of these two advance technologies will result in the appearance of connected automated vehicles which utilise communication systems to enhance the performance of automated vehicles, and consequently improve transportation by enabling cooperative functionalities, namely, cooperative sensing and cooperative manoeuvring.

However, although connected and autonomous vehicles have the potential to lower the number of road fatalities, casualties, and traffic congestion, the eradication, or near eradication, of human error and traffic load will only be realised with full automation. Major international automotive industries believe artificial intelligence will be the bridge between current automated vehicles and fully autonomous vehicles. To this end, the aim of this Research Topic is to highlight i) the potentials of using machine learning and AI techniques in transforming current automated vehicles to fully autonomous vehicles, ii) the concerns regarding the explainability of AI techniques and potential solutions for it and iii) the safety assurance of AI-enabled functionalities for autonomous driving.

The safety impacts of automated vehicle technology occur primarily due to the fundamental change in the driving principle, i.e., a shift of perception and decision-making from the human to the machine. Further, the connectivity among vehicles and between vehicle infrastructure will influence the performance of the technology as well as its user acceptance. This Research Topic encourages authors from academia and industry to submit new research results about technological innovations and novel ideas for connected automated vehicles (CAVs), with special interest for artificial intelligence and their safety impacts as well as the explainability of AI systems.

Potential topics include, but are not limited to, the following with respect to automated vehicles:
• AI and deep learning
• Reinforcement learning
• Control, optimisation, and prediction
• Vision and environment perception
• Big data and data analysis
• AI transparency
• Vehicle localisation and autonomous navigation
• Human factors and HMI
• Security, privacy, and safety systems
• Sensors and detectors


Keywords: Artificial Intelligence, Perception, Control, Decision-Making, Autonomous Vehicle


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

Current transportation and mobility systems will soon be transformed to a new era by the advent of new technologies associated with connectivity and automation in vehicles. Connectivity enables the flow refinement of data, leading to better information and smoother journeys for the travelling public. At the same time, automation yields increased safety and new ways of helping people become more productive. The combination of these two advance technologies will result in the appearance of connected automated vehicles which utilise communication systems to enhance the performance of automated vehicles, and consequently improve transportation by enabling cooperative functionalities, namely, cooperative sensing and cooperative manoeuvring.

However, although connected and autonomous vehicles have the potential to lower the number of road fatalities, casualties, and traffic congestion, the eradication, or near eradication, of human error and traffic load will only be realised with full automation. Major international automotive industries believe artificial intelligence will be the bridge between current automated vehicles and fully autonomous vehicles. To this end, the aim of this Research Topic is to highlight i) the potentials of using machine learning and AI techniques in transforming current automated vehicles to fully autonomous vehicles, ii) the concerns regarding the explainability of AI techniques and potential solutions for it and iii) the safety assurance of AI-enabled functionalities for autonomous driving.

The safety impacts of automated vehicle technology occur primarily due to the fundamental change in the driving principle, i.e., a shift of perception and decision-making from the human to the machine. Further, the connectivity among vehicles and between vehicle infrastructure will influence the performance of the technology as well as its user acceptance. This Research Topic encourages authors from academia and industry to submit new research results about technological innovations and novel ideas for connected automated vehicles (CAVs), with special interest for artificial intelligence and their safety impacts as well as the explainability of AI systems.

Potential topics include, but are not limited to, the following with respect to automated vehicles:
• AI and deep learning
• Reinforcement learning
• Control, optimisation, and prediction
• Vision and environment perception
• Big data and data analysis
• AI transparency
• Vehicle localisation and autonomous navigation
• Human factors and HMI
• Security, privacy, and safety systems
• Sensors and detectors


Keywords: Artificial Intelligence, Perception, Control, Decision-Making, Autonomous Vehicle


Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.

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Submission Deadlines

31 July 2021 Abstract
30 November 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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Topic Editors

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Submission Deadlines

31 July 2021 Abstract
30 November 2021 Manuscript

Participating Journals

Manuscripts can be submitted to this Research Topic via the following journals:

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