Enhancing pedestrian mobility in Smart Cities using Big Data
Author:
Affiliation:
1. Faculty of Business and Law, Swinburne University, Hawthorn, Australia
2. Swinburne University of Technology
3. Defence Science & Technology Group, Melbourne, Australia
Publisher
Informa UK Limited
Subject
Statistics, Probability and Uncertainty,Business, Management and Accounting (miscellaneous),Statistics and Probability
Link
https://www.tandfonline.com/doi/pdf/10.1080/23270012.2020.1741039
Reference20 articles.
1. Data Science
2. Big data analytics and business analytics
3. Calibration and validation of a simulation model for predicting pedestrian fatalities at unsignalized crosswalks by means of statistical traffic data
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5. Pedestrian road safety in relation to urban road type and traffic flow
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2. City Mobility and Night Life Monitor;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2023-12-12
3. Mining Tourists’ Movement Patterns in a City;Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering;2023-12-12
4. A sustainable smart mobility? Opportunities and challenges from a big data use perspective;Sustainable Futures;2023-12
5. Revealing social dimensions of urban mobility with big data: A timely dialogue;Journal of Transport and Land Use;2023-11-20
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