AI Perspectives in Smart Cities and Communities to Enable Road Vehicle Automation and Smart Traffic Control

Smart cities and communities (SCC) constitute a new paradigm in urban development. SCC ideate a data-centered society aimed at improving efficiency by automating and optimizing activities and utilities. Information and communication technology along with Internet of Things enables data collection an...

Celý popis

Uloženo v:
Podrobná bibliografie
Vydáno v:Smart cities (Basel) Ročník 4; číslo 2; s. 783 - 802
Hlavní autoři: Englund, Cristofer, Aksoy, Eren Erdal, Alonso-Fernandez, Fernando, Cooney, Martin Daniel, Pashami, Sepideh, Åstrand, Björn
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 2021
Témata:
Advanced driver assistance systems
Annotations
Artificial intelligence
Automation
Automobile safety
Business operations
Business services
COVID-19
Data collection
driver modeling
Energy consumption
Energy efficiency
Fatalities
Industrial plant emissions
Internet of Things
perception
Renewable resources
Situational awareness
Smart cities
smart traffic control
Standardization
Traffic accidents & safety
Traffic control
Traffic models
Trends
Urban development
Utilities
Europe
ISSN:2624-6511, 2624-6511
On-line přístup:Získat plný text
Tagy: Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
Popis
Shrnutí:Smart cities and communities (SCC) constitute a new paradigm in urban development. SCC ideate a data-centered society aimed at improving efficiency by automating and optimizing activities and utilities. Information and communication technology along with Internet of Things enables data collection and with the help of artificial intelligence (AI) situation awareness can be obtained to feed the SCC actors with enriched knowledge. This paper describes AI perspectives in SCC and gives an overview of AI-based technologies used in traffic to enable road vehicle automation and smart traffic control. Perception, smart traffic control and driver modeling are described along with open research challenges and standardization to help introduce advanced driver assistance systems and automated vehicle functionality in traffic. To fully realize the potential of SCC, to create a holistic view on a city level, availability of data from different stakeholders is necessary. Further, though AI technologies provide accurate predictions and classifications, there is an ambiguity regarding the correctness of their outputs. This can make it difficult for the human operator to trust the system. Today there are no methods that can be used to match function requirements with the level of detail in data annotation in order to train an accurate model. Another challenge related to trust is explainability: models can have difficulty explaining how they came to certain conclusions, so it is difficult for humans to trust them.
Bibliografie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:2624-6511
2624-6511
DOI:10.3390/smartcities4020040