Deep understanding of big geospatial data for self-driving cars

Shuo Shang, Jianbing Shen, Ji Rong Wen, Panos Kalnis

Research output: Contribution to journalArticlepeer-review

4 Scopus citations


Self-driving cars are capable of sensing environment and moving with little or no human input. Effective control of self-driving cars based on big geospatial data is one of the promising future directions of intelligent transportation. Specifically, big geospatial data understanding is helpful in acquiring travel behavior, vehicle mobility, traffic flow, nearby environment, and traffic-aware navigation. This special issue contains 10 research articles that present solid and novel research studies in the area of geospatial data analytics for self-driving applications, and 1survey article that investigates existing studies related to self-driving cars. All of the 11 papers went through at least two rounds of rigorous reviews by the guest editors and invited reviewers.
Original languageEnglish (US)
StatePublished - Jul 28 2020

Bibliographical note

KAUST Repository Item: Exported on 2020-10-01


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