I Takaaki Umedu / [1] [2] 142 2014 Spring / No.399
3 II IT IT Intelligent Transportation Systems, ITS VICS Vehicle Information and Communication System 4 VICS FM VICS 143
G-BOOK 5 6 CARWINGS 7 VICS 700MHz ITS ITS 8 9 [10] [11] [12] 13 14 15 16 NETSTREAM 17 144 2014 Spring / No.399
III.1 1 NETSTREAM 17 1 2 3 1 3 2 2 250m 1km 3 3 1 6 3 2 9 3 3 12 3 4 3 1 7% 3 2 50% 3 3 10% 145
40% 3 4 1.2 1 2 3 (1)3 台 /km (2)6 台 /km (3)9 台 /km (4)12 台 /km 3 146 2014 Spring / No.399
18 [3] 2 4 real traffic flow macroscopic model proposed model 0.40 0.94 210m 210m 210m.3 V K Greenshields 18 4 147
V = V Ï MAX Ô1 D D MIN Ï Ô 1 V VMAX 0 D DMIN VMAX RS 0.8 RS 1.3 19 RS DMIN RS RS 2 DMIN 18 RS 1 RS 1 RS 1 RS 1 minï D V Ï MIN MAX 1- D V = DMIN minïv Ï MAX 1- D Ô Ô Ï, RS V Ï, RS V MAX MAX Ï 2 Ï RS D 1- D MIN Ï Ï ( RS 1) ( RS > 1) 2 RS 148 2014 Spring / No.399
IV.1 ID ID GPS GPS W = {id, p, t, l} id ID p t l ID R prec trec pcur tcur Vest d p1,p2 V est = ( prec, pcur) tcur 2R prec 3 ID 4R 5 149
l = 0 5 ID ID 警 戒 情 報 A P 警 戒 情 報 を 送 信 転 送 距 離 がD min 未 満 の 場 合 は 監 視 せずに 転 送 B C D P D min 図 6 提 案 プロトコルの 概 要 D が 監 視 を 行 う. 監 視 車 両 1 1 N 6.2 6 1 2 3 4 5 6 Dmin 7.3 150 2014 Spring / No.399
V.1 MANS 12 MANS NETSTREAM MANS MANS 7 7 100km 100 5km 2 3 130km IEEE802.11 IBSS IndependentBasic Service Set 20 IEEE802.11 UDP/IP D 200m ID 40m ID x 1- x/d 2 R D0 ID =60% 1 ID 100km 28m ID ID 40m ID 7 151
.2 8 4 4 30km/ 25km/ 9 probability [%] 中 継 器 なし( 既 存 のモビリティモデル) 中 継 器 なし( 現 実 的 なモビリティモデル) 中 継 器 あり( 既 存 のモビリティモデル) 中 継 器 あり( 現 実 的 なモビリティモデル) Average speed of dangerous vehicles [km/h] 8 [21] [22] VI NETSTREAM 17 [1] Akira Uchiyama, Kumiko Maeda, Takaaki Umedu, Hirozumi Yamaguchi, Teruo Higashino(2007) / Performance Evaluation of Mobile Wireless Communication and Services with Modelling of Real Environment, International Journal of Ad Hoc and Ubiquitous Computing, vol. 2, no. 4, pp. 239-249. [2] Kumiko Maeda, Akira Uchiyama, Takaaki Umedu, Hirozumi Yamaguchi, Keiichi Yasumoto, Teruo Higashino (2009) / Urban Pedestrian Mobility for Mobile Wireless Network Simulation, Ad Hoc Networks / Elsevier, vol. 7, no. 1, pp. 153-170. 152 2014 Spring / No.399
[3] Kazuhiro Nakanishi, Takaaki Umedu, Teruo Higashino, Hiroko Mori, Hironobu Kitaoka (2007) / Synthesizing Realistic Vehicular Mobility for Precise Simulation of Inter-vehicle Communication, Proceedings of the 2nd IEEE Workshop on Automotive Networking and Applications AutoNet 2007. [4] VICS http://www.vics.or.jp/index1.html. [5] G-BOOK http://g-book.com/pc/default.asp. [6] INTERNAVI http://www.honda.co.jp/internavi/. [7] CARWINGS http://drive.nissan-carwings.com/web/index.htm. [8] ITS : 700MHz, http://www.itsforum.gr.jp/public/ J7Database/p34/ ITSFORUMRC006V1_0.pdf. [9] S. Ni, Y. Tseng, Y. Chen, and J. Sheu (1999) / The Broadcast Storm Problem in a Mobile Ad Hoc Network, Proc. of the 5th Annual ACM/IEEE International Conference on Mobile Computing and Networking MobiCom'99, pp.151-162. [10] M. M. Artimy, W. Robertson and W. J. Phillips (2005) / Assignment of Dynamic Transmission Range Based on Estimation of Vehicle Density, Proc. of the 2nd ACM International Workshop on Vehicular Ad Hoc Networks VANET 2005, pp.40-48. [11] A. Khelil, C. Becker, J. Tian and K. Rothermel(2002) / An Epidemic Model for Information Diffusion in MANETs, Proc. of the 5th ACM International Workshop on Modeling Analysis and Simulation of Wireless and Mobile Systems MSWiM'02, pp.54-60. [12] M. Saito, J. Tsukamoto, T. Umedu and T. Higashino(2007) / Design and Evaluation of Inter-Vehicle Dissemination Protocol for Propagation of Preceding Traffic Information, IEEE Transactions on Intelligent Transportation Systems, Vol. 8, Issue 3, pp. 379-390. [13] T. Camp, J. Boleng and V. Davies (2002) / A Survey of Mobility Models for Ad Hoc Network Researh, Wireless Communication and Mobile Computing, vol. 2, No. 5, pp. 483-502. [14] R. Choffnes and F. E. Bustamante (2005) / An Integrated Mobility and Traffic Model for Vehicular Wireless Networks, in Proc. of the 2nd ACM International Workshop on Vehicular Ad Hoc Networks VANET 2005, pp.69-78. [15] S. Panwai and H. Dia (2005) / Comparative Evaluation of Microscopic Car-Following Behavior, IEEE Transactions on Intelligent Transportation Systems, Vol. 6, No. 3, pp.314-325. [16] J. Yoon, M. Liu and B. Noble (2003) / Sound Mobility Models, in Proc. of the 9th Annual ACM/ IEEE International Conference on Mobile Computing and Networking MobiCom'03, pp.205-216,. [17] 2005 NETSTREAM,, Vol.46, No.1, pp.226-235. [18] 1992 pp.126-127. [19] 2005 2005' 4.3.1-4.3.3. [20] IEEE802.11 Standard(1999) / Wireless LAN Medium Access Control MAC and Physical Layer PHY Specifications, ISO/IEC 8802-11:1999. 153
[21],,,, 2008,, vol. 49, no. 1, pp. 212-220. [22] Takaaki Umedu, Kumiko Isu, Teruo Higashino, C. K. Toh (2010) / An Inter-Vehicular Communication Protocol for Distributed Detection of Dangerous Vehicles, IEEE Transactions on Vehicular Technology, vol. 59, no. 2, pp. 627-637. 154 2014 Spring / No.399
Detection Method of Dangerous Vehicles Using Inter-Vehicular Communication and Its Evaluation Considering Realistic Vehicular Mobility Takaaki Umedu Recently, the deployment of wireless communication technologies for roads and highways has been increasing done. There are a lot of research about applying inter-vehicular communication to collection and propagation of traffic information. It has been suggested that ad-hoc communications can be used to propagate information related to traffic jams and accidents efficiently. In this paper, we propose an inter-vehicular information system that detects over speeded vehicles without any roadside infrastructures. In our system, vehicles observe each other and share the location information via inter-vehicular communication to detect over speeded vehicles. We evaluated the performance of proposing method using a simulator taking into account realistic lane and speed models, mobility, position, and location errors. Here, in most of existing traffic simulators, distance between two following vehicles is modeled as equals based on statistical flow rates. Such mobility models do not reflect real performance of inter-vehicle communication. We extract particular characteristics of real vehicular mobility from several traces of vehicular movement, formulate them formally, implement the formulated realistic vehicular mobility on existing traffic simulators and obtain more real performance of inter-vehicle communication. In the extracted vehicular mobility, each vehicle runs at a different speed, with different distance from the vehicle ahead and with different vehicular density and distribution while the bottleneck capacity and saturation flow rate of the target roads are preserved as the same as those on the original one. The simulation results show that our system can detect over speeded vehicles under various conditions where the density and speed of the vehicles vary. Detection Method of Dangerous Vehicles Using Inter-Vehicular Communication and Its Evaluation Considering Realistic Vehicular Mobility Takaaki Umedu 155