 |
English
|
正體中文
|
简体中文
|
Post-Print筆數 : 27 |
Items with full text/Total items : 113303/144284 (79%)
Visitors : 50803083
Online Users : 790
|
|
|
Loading...
|
Please use this identifier to cite or link to this item:
https://nccur.lib.nccu.edu.tw/handle/140.119/135219
|
| Title: | CAR: The Clean Air Routing Algorithm for Path Navigation With Minimal PM2.5 Exposure on the Move |
| Authors: | 蔡子傑
Tsai, Tzu-Chieh
Mahajan, Sachit
Tang, Yu-Siou
Wu, Dong-Yi
Chen, Ling-Jyh |
| Contributors: | 資科系 |
| Keywords: | Roads , Navigation , Routing , Predictive models , Pollution , Real-time systems , Sensors |
| Date: | 2019-01 |
| Issue Date: | 2021-05-27 11:41:12 (UTC+8) |
| Abstract: | Transport related pollution is becoming a major issue as it adversely affects human health and one way to lower the personal exposure to air pollutants is to choose a health-optimal route to the destination. Current navigation systems include options for the quickest paths (distance, traffic) and least expensive paths (fuel costs, tolls). In this paper, we come up with the CAR (Clean Air Routing) algorithm and use it to build a health-optimal route recommendation system between the origin and the destination. We combine the open source PM2.5 (Fine Particulate Matter with diameter less than 2.5 micrometers) concentration data for Taiwan, with the road network graph obtained through OpenStreetMaps. In addition, spatio-temporal interpolation of PM2.5 is performed to get PM2.5 concentration for the road network intersections. Our algorithm introduces a weight function that assesses how much PM2.5 the user is exposed to at each intersection of the road network and uses it to navigate through intersections with the lowest PM2.5 exposures. The algorithm can help people reduce their overall PM2.5 exposure by offering a healthier alternative route which may be slightly longer than the shortest path in some cases. We evaluate our algorithm for different travel modes, including driving, cycling and walking. An analysis is done for more than 4,000 real-world travel scenarios. The results show that our approach can lead to an average exposure reduction of 17.1% with an average distance increase of 2.4%. |
| Relation: | IEEE Access, No.7, pp.147373-147382 |
| Data Type: | article |
| DOI 連結: | https://doi.org/10.1109/ACCESS.2019.2946419 |
| DOI: | 10.1109/ACCESS.2019.2946419 |
| Appears in Collections: | [資訊科學系] 期刊論文
|
Files in This Item:
| File |
Description |
Size | Format | |
|---|
| 178.pdf | | 9285Kb | Adobe PDF2 | 203 | View/Open |
|
All items in 政大典藏 are protected by copyright, with all rights reserved.
|
著作權政策宣告 Copyright Announcement1.本網站之數位內容為國立政治大學所收錄之機構典藏，無償提供學術研究與公眾教育等公益性使用，惟仍請適度，合理使用本網站之內容，以尊重著作權人之權益。商業上之利用，則請先取得著作權人之授權。
The digital content of this website is part of National Chengchi University Institutional Repository. It provides free access to academic research and public education for non-commercial use. Please utilize it in a proper and reasonable manner and respect the rights of copyright owners. For commercial use, please obtain authorization from the copyright owner in advance.
2.本網站之製作，已盡力防止侵害著作權人之權益，如仍發現本網站之數位內容有侵害著作權人權益情事者，請權利人通知本網站維護人員(
nccur@nccu.edu.tw)，維護人員將立即採取移除該數位著作等補救措施。
NCCU Institutional Repository is made to protect the interests of copyright owners. If you believe that any material on the website infringes copyright, please contact our staff(
nccur@nccu.edu.tw). We will remove the work from the repository and investigate your claim.
