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題名 物聯網架構下運用路程與停車場車流量實現停車推薦系統
An IoT based parking recommendation system considering distance and parking lot flow作者 陳遠
Chen, Yuan貢獻者 蔡子傑
Tsai, Tzu-Chieh
陳遠
Chen, Yuan關鍵詞 物聯網
智慧城市
智慧停車
停車建議
等候理論
Internet of Things
Smart city
Smart parking
Parking recommendation
Queueing theory日期 2021 上傳時間 2-Mar-2021 14:33:52 (UTC+8) 摘要 在現今資訊爆炸且硬體發展日益先進的時代中，使用物聯網技術以其硬體與軟體架構進行應用並達到智慧城市目的之相關開發與建置正快速地發展中，而其中都市利用多種不同感測器與資料來進行停車行為的優化則成為相當熱門的議題，尤其在人口密集區域大量停車需求與眾多停車區域的環境中，停車行為的分配顯得更為重要。在本篇論文當中，我們建立出一套較符合真實情況的停車推薦系統解決都市中有停車需求者無法有效的利用城市中剩餘的停車空位，同時也可以避免都市中原已壅塞的交通量更加惡化，降低城市車流量負載，本研究透過將停車行為拆分成兩個部分並運用等候理論的公式模型推導進行真實情況的預測，第一部分為估計出有停車需求的使用者發出停車請求後直到經過系統分配到達推薦的停車場中間路途所需耗費的時間，並且將其時間用於第二部分預估停車場在經過路途預估所需時間後能保有空位之機率，藉此達到良好的停車成功率，減少車輛在經過漫漫長路到達後卻無位可停的機率最後使用SUMO交通模擬器進行實驗模擬，結果顯示在壅塞的都市交通環境中，使用本論文方法相較於傳統的決策方法能有效降低使用者停車總花費時間與到達後因車位已滿而失敗的機率。
In the age of information explosion and advanced hardware development, the related exploitation and construction of using IoT (Internet of Things) technology with its hardware and software framework application to achieve the purpose of “smart city” is developing rapidly. The optimization of parking behavior using a variety of different sensors and data in cities has become a very popular and important issue. Especially in the environment of a large number of parking needs in densely populated areas with many parking areas, the allocation of parking behaviors is more important.In this thesis, we propose a parking recommendation system that conforms with the real situation to solve the parking problem by effectively using remaining parking space in the city. At the same time, it can also avoid worsening the traffic jam and thus, balance the traffic flow in the city. This research proposes the recommendation method by analyzing the parking behavior with two parts, and using the model of queuing theory. The first part is to estimate the time consumption from the parking request generated by the user to reaching the candidate parking lot. The time consumption from the first part will be used in the second part to calculate the probability of getting a free parking then. By this calculation, we can expect to achieve the better parking success rate,and avoid the cars to circle around for free parking space.To validation our model, we use the SUMO traffic simulator for experimental simulation. The results show that in a congested urban traffic environment, our method can effectively reduce the total time spent on parking and the failure probability of the parking space after arrival.參考文獻 [1] M. Caliskan, A. Barthels, B. Scheuermann and M. Mauve, "Predicting Parking Lot Occupancy in Vehicular Ad Hoc Networks," 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring, Dublin, 2007, pp. 277-281,doi:10.1109/VETECS.2007.69.[2] Y. Geng and C. G. Cassandras, "New “Smart Parking” System Based on Resource Allocation and Reservations," in IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 3, pp. 1129-1139, Sept. 2013, doi: 10.1109/TITS.2013.2252428.[3] Ma, J., Clausing, E., and Liu, Y., "Smart On-Street Parking System to Predict Parking Occupancy and Provide a Routing Strategy Using Cloud-Based Analytics," SAE Technical Paper 2017-01-0087, 2017, http://doi.org/10.4271/2017-01-0087.[4] C. Tang, X. Wei, C. Zhu, W. Chen and J. J. P. C. Rodrigues, "Towards Smart Parking Based on Fog Computing," in IEEE Access, vol. 6, pp. 70172-70185, 2018, doi: 10.1109/ACCESS.2018.2880972.[5] T. N. Pham, M. Tsai, D. B. Nguyen, C. Dow and D. Deng, "A Cloud-Based Smart-Parking System Based on Internet-of-Things Technologies," in IEEE Access, vol. 3, pp. 1581-1591, 2015, doi: 10.1109/ACCESS.2015.2477299.[6] L. CODECÁ, J. ERDMANN and J. HÄRRI, "A SUMO-Based Parking Management Framework for Large-Scale Smart Cities Simulations," 2018 IEEE Vehicular Networking Conference (VNC), Taipei, Taiwan, 2018, pp. 1-8, doi: 10.1109/VNC.2018.8628417.[7] SUMO User Documentationhttps://sumo.dlr.de/docs/index.html[8] Takács, Lajos, . Introduction to the Theory of Queues. Vol. 584. New York: Oxford University Press, 1962.[9] T. Lin, H. Rivano and F. Le Mouël, "A Survey of Smart Parking Solutions," in IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 12, pp. 3229-3253, Dec. 2017, doi: 10.1109/TITS.2017.2685143.[10] Tsai, MF., Kiong, Y.C. & Sinn, A. Smart service relying on Internet of Things technology in parking systems. J Supercomput 74, 4315–4338 (2018). https://doi.org/10.1007/s11227-016-1875-8[11] K. S. Liu, J. Gao, X. Wu and S. Lin, "On-Street Parking Guidance with Real-Time Sensing Data for Smart Cities," 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), Hong Kong, China, 2018, pp. 1-9, doi: 10.1109/SAHCN.2018.8397113.[12] 停車大聲公:https://tw.parkinglotapp.com/[13] 北市好停車:https://tpis.pma.gov.tw/ParkInfo/taipeiparking[14] INRIX Parkme:https://www.parkme.com/operators 描述 碩士
國立政治大學
資訊科學系
107753040資料來源 http://thesis.lib.nccu.edu.tw/record/#G0107753040 資料類型 thesis dc.contributor.advisor 蔡子傑 zh_TW dc.contributor.advisor Tsai, Tzu-Chieh en_US dc.contributor.author (Authors) 陳遠 zh_TW dc.contributor.author (Authors) Chen, Yuan en_US dc.creator (作者) 陳遠 zh_TW dc.creator (作者) Chen, Yuan en_US dc.date (日期) 2021 en_US dc.date.accessioned 2-Mar-2021 14:33:52 (UTC+8) - dc.date.available 2-Mar-2021 14:33:52 (UTC+8) - dc.date.issued (上傳時間) 2-Mar-2021 14:33:52 (UTC+8) - dc.identifier (Other Identifiers) G0107753040 en_US dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/134088 - dc.description (描述) 碩士 zh_TW dc.description (描述) 國立政治大學 zh_TW dc.description (描述) 資訊科學系 zh_TW dc.description (描述) 107753040 zh_TW dc.description.abstract (摘要) 在現今資訊爆炸且硬體發展日益先進的時代中，使用物聯網技術以其硬體與軟體架構進行應用並達到智慧城市目的之相關開發與建置正快速地發展中，而其中都市利用多種不同感測器與資料來進行停車行為的優化則成為相當熱門的議題，尤其在人口密集區域大量停車需求與眾多停車區域的環境中，停車行為的分配顯得更為重要。在本篇論文當中，我們建立出一套較符合真實情況的停車推薦系統解決都市中有停車需求者無法有效的利用城市中剩餘的停車空位，同時也可以避免都市中原已壅塞的交通量更加惡化，降低城市車流量負載，本研究透過將停車行為拆分成兩個部分並運用等候理論的公式模型推導進行真實情況的預測，第一部分為估計出有停車需求的使用者發出停車請求後直到經過系統分配到達推薦的停車場中間路途所需耗費的時間，並且將其時間用於第二部分預估停車場在經過路途預估所需時間後能保有空位之機率，藉此達到良好的停車成功率，減少車輛在經過漫漫長路到達後卻無位可停的機率最後使用SUMO交通模擬器進行實驗模擬，結果顯示在壅塞的都市交通環境中，使用本論文方法相較於傳統的決策方法能有效降低使用者停車總花費時間與到達後因車位已滿而失敗的機率。 zh_TW dc.description.abstract (摘要) In the age of information explosion and advanced hardware development, the related exploitation and construction of using IoT (Internet of Things) technology with its hardware and software framework application to achieve the purpose of “smart city” is developing rapidly. The optimization of parking behavior using a variety of different sensors and data in cities has become a very popular and important issue. Especially in the environment of a large number of parking needs in densely populated areas with many parking areas, the allocation of parking behaviors is more important.In this thesis, we propose a parking recommendation system that conforms with the real situation to solve the parking problem by effectively using remaining parking space in the city. At the same time, it can also avoid worsening the traffic jam and thus, balance the traffic flow in the city. This research proposes the recommendation method by analyzing the parking behavior with two parts, and using the model of queuing theory. The first part is to estimate the time consumption from the parking request generated by the user to reaching the candidate parking lot. The time consumption from the first part will be used in the second part to calculate the probability of getting a free parking then. By this calculation, we can expect to achieve the better parking success rate,and avoid the cars to circle around for free parking space.To validation our model, we use the SUMO traffic simulator for experimental simulation. The results show that in a congested urban traffic environment, our method can effectively reduce the total time spent on parking and the failure probability of the parking space after arrival. en_US dc.description.tableofcontents 第一章 緒論 11.1 背景與動機 11.2 研究目的 3第二章 相關研究 42.1 智慧停車 42.2 智慧停車實際應用 6第三章 研究方法及架構 93.1物聯網環境與架構 93.2推薦方法設計 113.3路途時間計算 133.4空位率計算 17第四章 模擬實驗結果與分析 224.1 SUMO交通模擬器 224.2實驗架構設計 234.3對照組設計 264.4公式驗證實驗結果 274.5方法模擬實驗結果 29第五章 結論與未來展望 355.1結論 355.2未來展望 35參考資料 36 zh_TW dc.format.extent 1901953 bytes - dc.format.mimetype application/pdf - dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0107753040 en_US dc.subject (關鍵詞) 物聯網 zh_TW dc.subject (關鍵詞) 智慧城市 zh_TW dc.subject (關鍵詞) 智慧停車 zh_TW dc.subject (關鍵詞) 停車建議 zh_TW dc.subject (關鍵詞) 等候理論 zh_TW dc.subject (關鍵詞) Internet of Things en_US dc.subject (關鍵詞) Smart city en_US dc.subject (關鍵詞) Smart parking en_US dc.subject (關鍵詞) Parking recommendation en_US dc.subject (關鍵詞) Queueing theory en_US dc.title (題名) 物聯網架構下運用路程與停車場車流量實現停車推薦系統 zh_TW dc.title (題名) An IoT based parking recommendation system considering distance and parking lot flow en_US dc.type (資料類型) thesis en_US dc.relation.reference (參考文獻) [1] M. Caliskan, A. Barthels, B. Scheuermann and M. Mauve, "Predicting Parking Lot Occupancy in Vehicular Ad Hoc Networks," 2007 IEEE 65th Vehicular Technology Conference - VTC2007-Spring, Dublin, 2007, pp. 277-281,doi:10.1109/VETECS.2007.69.[2] Y. Geng and C. G. Cassandras, "New “Smart Parking” System Based on Resource Allocation and Reservations," in IEEE Transactions on Intelligent Transportation Systems, vol. 14, no. 3, pp. 1129-1139, Sept. 2013, doi: 10.1109/TITS.2013.2252428.[3] Ma, J., Clausing, E., and Liu, Y., "Smart On-Street Parking System to Predict Parking Occupancy and Provide a Routing Strategy Using Cloud-Based Analytics," SAE Technical Paper 2017-01-0087, 2017, http://doi.org/10.4271/2017-01-0087.[4] C. Tang, X. Wei, C. Zhu, W. Chen and J. J. P. C. Rodrigues, "Towards Smart Parking Based on Fog Computing," in IEEE Access, vol. 6, pp. 70172-70185, 2018, doi: 10.1109/ACCESS.2018.2880972.[5] T. N. Pham, M. Tsai, D. B. Nguyen, C. Dow and D. Deng, "A Cloud-Based Smart-Parking System Based on Internet-of-Things Technologies," in IEEE Access, vol. 3, pp. 1581-1591, 2015, doi: 10.1109/ACCESS.2015.2477299.[6] L. CODECÁ, J. ERDMANN and J. HÄRRI, "A SUMO-Based Parking Management Framework for Large-Scale Smart Cities Simulations," 2018 IEEE Vehicular Networking Conference (VNC), Taipei, Taiwan, 2018, pp. 1-8, doi: 10.1109/VNC.2018.8628417.[7] SUMO User Documentationhttps://sumo.dlr.de/docs/index.html[8] Takács, Lajos, . Introduction to the Theory of Queues. Vol. 584. New York: Oxford University Press, 1962.[9] T. Lin, H. Rivano and F. Le Mouël, "A Survey of Smart Parking Solutions," in IEEE Transactions on Intelligent Transportation Systems, vol. 18, no. 12, pp. 3229-3253, Dec. 2017, doi: 10.1109/TITS.2017.2685143.[10] Tsai, MF., Kiong, Y.C. & Sinn, A. Smart service relying on Internet of Things technology in parking systems. J Supercomput 74, 4315–4338 (2018). https://doi.org/10.1007/s11227-016-1875-8[11] K. S. Liu, J. Gao, X. Wu and S. Lin, "On-Street Parking Guidance with Real-Time Sensing Data for Smart Cities," 2018 15th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON), Hong Kong, China, 2018, pp. 1-9, doi: 10.1109/SAHCN.2018.8397113.[12] 停車大聲公:https://tw.parkinglotapp.com/[13] 北市好停車:https://tpis.pma.gov.tw/ParkInfo/taipeiparking[14] INRIX Parkme:https://www.parkme.com/operators zh_TW dc.identifier.doi (DOI) 10.6814/NCCU202100358 en_US
