Please use this identifier to cite or link to this item: https://ah.nccu.edu.tw/handle/140.119/134870


Title: 利用車載智慧物聯網路由技術以調控紅綠燈改善城市交通
A Vehicular Smart IoT Routing Technology for Urban Traffic Light Control
Authors: 林煙童
Lin, Yen-Tung
Contributors: 蔡子傑
Tsai, Tzu-Chieh
林煙童
Lin, Yen-Tung
Keywords: 物聯網
智慧紅綠燈
邊緣節點
無線隨意網路
耐延遲網路
Internet of Things
Smart Traffic Light
Edge node
Wireless ad hoc Network
Delay Tolerant Network
Date: 2021
Issue Date: 2021-05-03 10:27:38 (UTC+8)
Abstract: 塞車被視為城市交通所需面臨的嚴峻議題,嚴重的交通壅塞會造成通勤的時間增加、燃料耗損、空氣汙染、駕駛易感到憤怒和煩躁等。當前多數的紅綠燈控制系統利用道路的車流量調控,鮮少根據車輛自身資訊,以兼顧到車輛停等時間。要蒐集這些數據不是需部署大量感測裝置在路段上就是讓車主自行提供車輛資訊,前者對一座城市而言是筆龐大的成本負擔,後者則須駕駛消耗4G網路頻寬上傳即時的車況數據,在4G網路不普及的區域,用路人未必會願意協助數據的提供。
本論文探討當一些車輛願意自主提供自身資訊時,在僅利用這些車輛資訊改善城市交通壅塞的惡況,提升交通流暢度。雖然車輛資訊有時效性的問題,但在本研究提出的Hybrid routing概念中,在不利用4G網路上傳數據的前提下,結合無線隨意網路和耐延遲網路的特性,設計一個車載智慧物聯網路由技術將這些車輛資訊繞送到周遭的任一邊緣節點以供路口紅綠燈動態的調控,讓這些數據在本研究中只要“及時”而非“即時”仍可達到相同的效用,以改善城市交通壅塞的現象。
最後使用SUMO交通模擬器進行模擬,其結果顯示在車道約80%的壅塞程度下,即使只有30%的車輛願意參與本研究的數據提供和轉發,其車輛平均等待時間仍可少於傳統的車流計數方法。
Traffic congestion is regarded as a severe issue in urban traffic, which causes increased commuting time, fuel consumption, air pollution, and driving anger and irritability, etc. At present, traffic light control systems are mostly based on traffic flow and rarely utilize the vehicle's own information to give consideration to vehicle’s waiting time. To collect vehicle information, it is either to deploy a large amount of sensing devices on the roads or drivers need to upload real-time vehicle information by themselves. The former is a huge cost burden for a city, the latter consumes extra 4G bandwidth which drivers may be reluctant to do so.
In this thesis, we study how to use only vehicle information to improve urban traffic congestion when some drivers are willing to provide their vehicle data. Since the vehicle information is time-sensitive, we propose a hybrid routing to deliver these data “in-time” rather than “real-time” to any one of the surrounding edge nodes, even without 4G networks involved. Based on characteristics of vehicular ad hoc networks and delay tolerant networks (DTNs), we develop a vehicular smart IoT routing technology for anycast to edge server for dynamic traffic light control and improving traffic congestion.
To validate our model, we use the SUMO traffic simulator for the experimental simulation. The results show that under about more than 80% congested traffic lanes, our method achieves less the average waiting time compared to the traffic flow count method even only 30% of vehicles are willing to provide and forward data.
Reference: [1]. R. P. Laufer, P. B. Velloso, L. F. M. Vieira, and L. Kleinrock, “PLASMA: A new routing paradigm for wireless multihop networks,” in Proc. IEEE Conf. INFOCOM, 2012, pp. 2706–2710.

[2]. B. Zhou, J. Cao, and H. Wu, “Adaptive traffic light control of multiple intersections in WSN-based ITS,” in Vehicular Technology Conference (VTC Spring), 2011 IEEE 73rd, May 2011, pp. 1–5.

[3]. D. Zhu, G. Cui, Z. Fu, “DT-AODV: An On-Demand Routing Protocol based DTN in VANET” Appl. Math. Inf. Sci. 8, No. 6, 2955-2963 2014.

[4]. F. Sato, R. Kikuchi, “Hybrid routing scheme combining with geo-routing and DTN in VANET. ” In: Proceedings of the 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS-2016), pp. 250–255, July 2016

[5]. M. L. Suarez, L. E. Alvarez, P. A. Camacho, L. C. Marin, B. Vasquez, G. Gutierrez, R. A. Aranzazu, M. Carranza, F. G. Montoya, A. Valdes, C. Gonzalez, M. Jaramillo, S. Henao, "Dynamic allocation of traffic light plans as a traffic reduction strategy", in MOVICI-MOYCOT 2018: Joint Conference for Urban Mobility in the Smart City (Medellin, 2018), pp. 1–7.

[6]. Q. T. Minh, C. M. Tran, T. A. Le, B. T. Nguyen, T. M. Tran, and R. K. Balan, "FogFly: A traffic light optimization solution based on fog computing, " in Proc. ACM Int. Joint Conf. Int. Symp. Pervasive Ubiquitous Comput. Wearable Comput. (UbiComp), 2018, pp. 1130–1139.

[7]. N. Indra Er, K. D. Singh, and J.-M. Bonnin, “DC4LED: A Hierarchical VDTN Routing for Data Collection in Smart Cities,” in 2019 16th IEEE Annual Consumer Communications and Networking Conference (CCNC), pp. 1-4

[8]. C. Giannini, P. Calegari, C. Buratti, and R. Verdone, “Delay tolerant network for smart city: Exploiting bus mobility,” in Proc. AEIT Int. Annu. Conf., Apr. 2016, pp. 1–6.

[9]. J. G. Filho, A. Patel, B. L. A. Batista, and J. Celestino, Jr., ‘‘A systematic technical survey of DTN and VDTN routing protocols,’’ Computer. Standards Interfaces, vol. 48, no. 1, pp. 139–159, Nov. 2016.

[10]. Y. Zguira, H. Rivano, A. Meddeb “IoB-DTN: A lightweight DTN protocol for mobile IoT applications to smart bike sharing systems” 2018 Wireless Days (WD), IEEE (2018), pp. 131-136


[11]. J. Lee and B. Park, “Development and evaluation of a cooperative vehicle intersection control algorithm under the connected vehicles environment,” IEEE Trans. Intell. Transp. Syst., vol. 13, no. 1, pp. 81–90, Mar. 2012.

[12]. M. A. S. Kamal, T. Hayakawa, and J.-I. Imura, “Development and evaluation of an adaptive traffic signal control scheme under a mixedautomated traffic scenario,” IEEE Trans. Intell. Transp. Syst., vol. 21, no. 2, pp. 590–602, Feb. 2020

[13]. S. Garg et al., “Edge computing-based security framework for big data analytics in VANETs,” IEEE Netw., vol. 33, no. 2, pp. 72–81, Mar./Apr. 2019

[14]. J. Liu et al., ‘‘High-efficiency urban traffic management in context-aware computing and 5G communication,’’ IEEE Commun. Mag., vol. 55, no. 1, pp. 34–40, Jan. 2017

[15]. R. Akamatsu, K. Obara, and H. Shigeno, “Road-oriented geographic routing protocol for urban vehicular ad hoc networks,” in Proc. 29th Int. IEEE Conf. Advanced Information Networking Applications Workshops, Mar. 2015, pp. 721–726.

[16]. V. K Shah, B. Luciano, S. Silvestri, S. Bhattacharjee, and S. K Das. “A diverse band-aware dynamic spectrum access network architecture for delay-tolerant smart city applications.” IEEE Transactions on Network and Service Management, 2020.

[17]. Muthanna, M.S.A., Abdukodir, K., Ateya, A.A, Al-Bahri, M. “Delay Tolerant Network model based on D2D communication.” In: 2019 4th MEC International Conference on Big Data and Smart City (ICBDSC), pp. 1–5. IEEE (2019)

[18]. 呂嘉文 (2017),“A Study on Adaptive Traffic Signal Control with Vehicular Ad-hoc Network.”, 國立成功大學,交通管理科學研究所碩士論文

[19]. 洪維駿 (2020),“Virtual Traffic Light Control Considering the Continuity of Traffic Flow” 國立中正大學,資訊工程研究所碩士論文

[20]. SUMO User Documentation
https://sumo.dlr.de/docs/index.html

[21]. 智慧紅綠燈新聞:
https://www.digitimes.com.tw/iot/article.asp?cat=158&cat1=20&cat2=35&id=0000576583_VOF6237M7GE4DX433TXCP

[22]. 交通壅塞相關新聞:
https://city.gvm.com.tw/article/68846
Description: 碩士
國立政治大學
資訊科學系
107753041
Source URI: http://thesis.lib.nccu.edu.tw/record/#G0107753041
Data Type: thesis
Appears in Collections:[資訊科學系] 學位論文

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