Research Topic

Changes in Transportation Systems in the Era of Artificial Intelligence and Robotics: From Vehicle Technology to Traffic Management

About this Research Topic

Intelligent Transportation Systems (ITS) have been introduced as a key term in the transportation field in the 20th century. It was predicted that ITS will change the future of transportation operation and control and increase the efficiency of transportation networks in terms of mobility and safety. More recently, further developments in sensing (examples: LIght Detection And Ranging – LIDAR - sensors, video processing/vision recognition), computational (example: Graphical Processing Units – GPUs) and control (for example: automated Unmanned Aerial Vehicles – UVAs and Automated Vehicles - AVs) technologies have allowed the production of a wealth of data making transportation a key source associated with the Big Data and a key domain associated with Smart Cities. Such data availability resulted in the use of Artificial Intelligence (AI) as a tool to model, analyze and predict different transportation processes. How will AI be used in the transportation field? What are the associated applications, risks and benefits?

Answering the aforementioned two questions, the goal of this special issue is to explore the role of AI in the transportation sector. In particular, we focus on three aspects: 1) the products associated with the use of AI and their performance; 2) the responsiveness of travelers to such products; and 3) the implications of the interaction between such products and their users on the transportation network of interest. Realizing such goal is crucial to understanding the prospects and the limitations associated with the use of AI to solve transportation problems. AI remains a controversial term in the scientific and the engineering community: despite being adopted by both researchers in different domains to answer multiple questions, there are no guidelines provided to avoid the misuse of AI. Decision makers are not fully informed to develop policies associated with the use of AI (for example: policies associated with liability, privacy and security) and career professionals are still debating the best practices in order to deploy products leveraging AI to make ethical decisions.

Given the goal of this special issue, we seek manuscripts that deal with different transportation modes (pedestrian/walking, e-scooters, bicycles, transit, personal vehicles, etc.) at different geographical scales (ranging from a link/node level to a city/country level). The focus remains on the technologies/models being developed/analyzed and their impacts on the surrounding environments. Special attention should be given to presenting the best practices and the challenges associated with the use of AI if compared to existing conventional ITS technologies:
- Incorporation of Ethics and Morality in AI decisions
- AI use in Connected and Automated Vehicles (CAVs)
- Video Detection in Transportation
- The Use of UAVs in Traffic Sensing
- AI in Collision Prediction and Traffic Control
- AI to Extract Travel Trends from Crowdsourced Data (i.e. cell phones and social networks)
- Guidelines on AI use/adoption for policy development and deployment


Keywords: Artificial Intelligence, Deep Learning, Autonomous Vehicles, Traffic Control, Smart Sensing


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.

Intelligent Transportation Systems (ITS) have been introduced as a key term in the transportation field in the 20th century. It was predicted that ITS will change the future of transportation operation and control and increase the efficiency of transportation networks in terms of mobility and safety. More recently, further developments in sensing (examples: LIght Detection And Ranging – LIDAR - sensors, video processing/vision recognition), computational (example: Graphical Processing Units – GPUs) and control (for example: automated Unmanned Aerial Vehicles – UVAs and Automated Vehicles - AVs) technologies have allowed the production of a wealth of data making transportation a key source associated with the Big Data and a key domain associated with Smart Cities. Such data availability resulted in the use of Artificial Intelligence (AI) as a tool to model, analyze and predict different transportation processes. How will AI be used in the transportation field? What are the associated applications, risks and benefits?

Answering the aforementioned two questions, the goal of this special issue is to explore the role of AI in the transportation sector. In particular, we focus on three aspects: 1) the products associated with the use of AI and their performance; 2) the responsiveness of travelers to such products; and 3) the implications of the interaction between such products and their users on the transportation network of interest. Realizing such goal is crucial to understanding the prospects and the limitations associated with the use of AI to solve transportation problems. AI remains a controversial term in the scientific and the engineering community: despite being adopted by both researchers in different domains to answer multiple questions, there are no guidelines provided to avoid the misuse of AI. Decision makers are not fully informed to develop policies associated with the use of AI (for example: policies associated with liability, privacy and security) and career professionals are still debating the best practices in order to deploy products leveraging AI to make ethical decisions.

Given the goal of this special issue, we seek manuscripts that deal with different transportation modes (pedestrian/walking, e-scooters, bicycles, transit, personal vehicles, etc.) at different geographical scales (ranging from a link/node level to a city/country level). The focus remains on the technologies/models being developed/analyzed and their impacts on the surrounding environments. Special attention should be given to presenting the best practices and the challenges associated with the use of AI if compared to existing conventional ITS technologies:
- Incorporation of Ethics and Morality in AI decisions
- AI use in Connected and Automated Vehicles (CAVs)
- Video Detection in Transportation
- The Use of UAVs in Traffic Sensing
- AI in Collision Prediction and Traffic Control
- AI to Extract Travel Trends from Crowdsourced Data (i.e. cell phones and social networks)
- Guidelines on AI use/adoption for policy development and deployment


Keywords: Artificial Intelligence, Deep Learning, Autonomous Vehicles, Traffic Control, Smart Sensing


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

29 October 2020 Abstract
21 March 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

29 October 2020 Abstract
21 March 2021 Manuscript

Participating Journals

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

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