Accessing the Influences of Weather and Environment Factors on Traffic Speed of Freeway
Traffic speed has been traditionally used as a measure of traffic performance. Predicting the traffic speed is fundamental for efficient traffic management and control strategy. This study explores the influences of freeway attributes, weather, and air condition on traffic speed. A quantitative model is also introduced to predict the traffic speed as per the identified influencing factors. Empirical data of traffic flow and potential influencing factors are collected from multiple sources for analysis and model calibration. The principal component analysis is firstly conducted to select the significant variables influencing the traffic speed. Afterward, a multiple linear regression model is calibrated to quantitatively model the impacts of different factors and investigate their weights. The results show that the attributes of freeway, the humidity of the area, the temperature, the horizontal visibility, the station maker, the air quality, and the PM quality have influences on the traffic speed. Among all of the variables, the weight of the existence of toll station is highest, indicating the largest influence on the traffic speed.
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Availability:
- Find a library where document is available. Order URL: http://worldcat.org/isbn/9789811552694
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Supplemental Notes:
- © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2020.
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Corporate Authors:
Springer Singapore
152 Beach Road
Singapore, 189721 -
Authors:
- Cao, Danni
- Wu, Jianjun
- Zeng, Ziling
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Conference:
- 3rd KES International Symposium on Smart Transportation Systems (KES-STS 2020)
- Date: 2020-6-17 to 2020-6-19
- Publication Date: 2020-5
Language
- English
Media Info
- Media Type: Web
- Features: References;
- Pagination: pp 53-67
- Monograph Title: Smart Transportation Systems 2020: Proceedings of 3rd KES-STS International Symposium
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Serial:
- Smart Innovation, Systems and Technologies
- Volume: 185
- Publisher: Springer Singapore
- ISSN: 2190-3018
- Serial URL: https://www.springer.com/series/8767
Subject/Index Terms
- TRT Terms: Environment; Freeways; Linear regression analysis; Traffic data; Traffic speed; Weather conditions
- Identifier Terms: Principal Component Analysis
- Subject Areas: Environment; Highways; Operations and Traffic Management;
Filing Info
- Accession Number: 01896963
- Record Type: Publication
- ISBN: 9789811552694
- Files: TRIS
- Created Date: Oct 23 2023 3:06PM