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Mükemmel/İdeal Şehir içi Ulaşım Sisteminin Diğerleriyle Karşılaştırılması: Toplam Seyahat Zamanları

Year 2019, Volume: 2 Issue: 1, 1 - 14, 24.04.2019

Abstract

Tüm nakliye ve ulaşım
sistemleri için en önemli hususlardan bir tanesi de zamandır. İnsan nakil
sistemleri için ise zaman daha fazla önem arz eder. O halde, zaman ve maliyeti
azaltmak ve emniyeti arttırmak üzerinde çalışmalar yapılmalıdır. Çalışmamızda şehir
içi insan aktarımı için tasarlanabilecek bir sistemin özelliklerinin neler
olması gerektiği ortaya konularak böyle bir sistemin nasıl olabileceğine dair
bir örnek sunulmuştur. Bu özellikleri taşıyan sistemlere de bu çalışmada
mükemmel/ideal sistem denilmiştir. Bu çalışma, mevcut/geleneksel sistemlerle,
teklif edilen mükemmel/ideal sistemin seyahat zamanları açısından bir
mukayesesini ortaya koymaktadır. şehir içi ulaşımı özellikle büyük şehirlerde
zaman, enerji ve kaynak kaybına sebep olmakta, insan vücudu ve ruhu üzerinde
olumsuz etkiler yapmaktadır. Mevcut şehir içi insan nakliyatı olması gerekenden
çok daha yavaş, tehlikeli ve zordur. Şehir içi insan ulaşımı günümüzde
gereklidir çünki şehirler artık eskisi gibi küçük kasabalar halinde
değillerdir. İnsanların pek az bir kısmı işlerine yaya olarak gidebilirler.
Arkadaş veya akrabalarını ziyaret etmek isteyenler çoğu zaman uzun mesafeler
almak zorundadırlar. Mevcut sistemler bu zorluklara çare olamamışlardır.
Tavsiye edilen sistemin hemen her meseleyi çözdüğü ve seyahat için harcanan
zaman açısından önceki tüm sistemlerden iyi olduğu gösterilmiştir.

References

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Chevrel, F. Claveau, J-F. Lafay, and F. Mars, Shared steering control between a driver and an automation: Stability in the presence of driver behavior uncertainty, IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [28] E. Belyaev, P. Molchanov, A. Vinel and Y. Koucheryavy, the use of automotive radars in video-based overtaking assistance applications. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, Sept. 2013. [29] H. Veeraraghavan, O. Masoud, and N. P. Papanikolopoulos, computer vision algorithms for intersection monitoring. IEEE Trans. Intell. Transp. Syst., vol. 4, no. 2, June 2003. [30] X. Yang, X. Li, and K. Xue, A new traffic-signal control for modern roundabouts: Method and application, IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, Dec. 2004. [31] H. Ling and J. Wu, A study on cyclist behavior at signalized intersections. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, Dec. 2004. [32] Y.-K. Ki, and D.-Y. 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Sys. Magazine, 18, Spring 2010. [38] L. Zhao, X. Peng, L. Li and Z. Li, A fast signal timing algorithm for individual oversaturated intersections. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 1, March 2011. [39] G. F. List and M. Cetin, modeling traffic signal control using petri nets. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 3, September 2004. [40] A. D. Febbraro, D. Giglio and N. Sacco, Urban traffic control structure based on hybrid petri nets. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, Dec. 2004. [41] S. Lin, B. D. Schutter, Y. Xi, and H. Hellendoorn, integrated urban traffic control for the reduction of travel delays and emissions, IEEE Trans. Intell. Transp. Syst., vol. 14, no. 4, December 2013. [42] H. Oliveira and P. L. Correia, automatic road crack detection and characterization, IEEE Trans. Intell. Transp. Syst., vol. 14, no. 1, March 2013 [43] M. A. Sotelo, F. J. Rodriguez and L. 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Comparison of perfect/ideal urban transportation system with the others: Total travel times

Year 2019, Volume: 2 Issue: 1, 1 - 14, 24.04.2019

Abstract

For
all types of transportations, one of the most important parameters is the total
travel time. So, the studies must be focused on reducing the total travel time
and cost, while increasing safety. This work is a comparison of total travel
times of present/traditional systems and the perfect/ideal system proposed by
the author. Urban transportation causes waste of time, energy and resources and
has negative effects on the health of human body and soul, especially in big
cities. Transportation in cities is much slower, risky and difficult than it
should be. Urban transportation is necessary today, because unlike the previous
times, the cities are not small towns. Most people cannot go to their works by
walking. People have to travel long distances to visit their relatives and
friends. Present systems cannot solve these difficulties in anyway. It is
proven in this paper that the suggested system solves almost all the problems
and calculations show that the travel time becomes much shorter.

References

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Yin, a real-time transit signal priority control model considering stochastic bus arrival time. IEEE Trans, Transp. Syst., vol. 15, no.4 August 2014. [7] N. D. Bird, O. Masoud, N. P. Papanikolopoulos and A. Isaacs, Detection of loitering individuals in public transportation areas. IEEE Trans. Intell. Transp. Syst., vol. 6, no. 2, June 2005. [8] K. T. Seow, and M. Pasquier, Supervising passenger land-transport systems. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 3, Sept. 2004. [9] J. K. K. Yuen, E. W. M. Lee, S. M. Lo, and R. K. K. Yuen, An intelligence - based optimization model of passenger flow in a transportation station. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, Sept. 2013. [10] L. Zhao and C. E. Thorpe, Stereo - and neural network - based pedestrian detection. IEEE Trans. Intell. Transp. Syst., vol. 1, no. 3, Sept. 2000. [11] C. Curio, J. Edelbrunner, T. Kalinke, C. Tzomakas, and W. v. Seelen, walking pedestrian recognition. IEEE Trans. Intell. Transp. Syst., vol. 1, no. 3, Sept. 2000. [12] U. Franke and S. Heinrich, Fast obstacle detection for urban traffic situations. IEEE Trans. Intell. Transp. Syst., vol. 3, no. 3, Sept. 2002. [13] M. S. Darms, P. E. Rybski, C. Baker, and C. Urmson, Obstacle detection and tracking for the urban challenge. IEEE Trans. Intell. Transp. Syst., vol. 10, no. 3, Sept. 2009. [14] A. Broggi, P. Cerri, S. Ghidoni, P. Grisleri, and H. G. Jung, A new approach to urban pedestrian detection for automatic braking. IEEE Trans. Intell. Transp. Syst., vol. 10, no. 4, Dec. 2009. [15] S. Gidel, P. Checchin, C. Blanc, T. Chateau, and L. Trassoudaine, pedestrian detection and tracking in an urban environment using a multilayer laser scanner. IEEE Trans. Intell. Transp. Syst., vol. 11, no. 3, Sept. 2010. [16] C. Xu, W. Wang, and P. Liu, A genetic programming model for real-time crash prediction on freeways. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [17] M. R. Hafner, D. Cunningham, L. Caminiti, and D. D. Vecchio, Cooperative collision avoidance at intersections: Algorithms and experiments. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, Sept. 2013. [18] J. Wang, X. Li, S. S. Liao, and Z. Hua, A hybrid approach for automatic incident detection. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, Sept. 2013. [19] L. Malta, C. Miyajima and Kazuya Takeda, A study of driver behavior under potential threats in vehicle traffic. IEEE Trans. Intell. Transp. Syst., vol. 10, no. 2, June 2009. [20] T. Wada, S. Doi, N. Tsuru, K. Isaji, and H. Kaneko, Characterization of expert drivers’ last-second braking and its application to a collision avoidance system, IEEE Trans. Intell. Transp. Syst., vol. 11, no. 2, June 2010. [21] L. Malta, C. Miyajima, N. Kitaoka, and K. Takeda, analysis of real-world driver’s frustration. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 1, March 2011. [22] D. Greene, J. Liu, J. Reich, Y. Hirokawa, A. Shinagawa, H. Ito, and T. Mikami, An efficient computational architecture for a collision early-warning system for vehicles, pedestrians, and bicyclists. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, Dec. 2011. [23] N. Wu, F. Chu, S. Mammar, and M. C. Zhou, petri net modeling of the cooperation behavior of a driver and a copilot in an advanced driving assistance system. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, Dec. 2011. [24] D. Das, S. Zhou, and J. D. Lee, Differentiating alcohol-induced driving behaviour using steering wheel signals. IEEE Trans. Intell. Transp. Syst., vol. 13, no. 3, Sept. 2012. [25] J. Wang, L. Zhang, D. Zhang, and K. Li, An adaptive longitudinal driving assistance system based on driver characteristics. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 1, March 2013. [26] C. Ahlstrom, K. Kircher, and A. Kircher, A gaze-based driver distraction warning system and its effect on visual behaviour. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [27] L. Saleh, P. Chevrel, F. Claveau, J-F. Lafay, and F. Mars, Shared steering control between a driver and an automation: Stability in the presence of driver behavior uncertainty, IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [28] E. Belyaev, P. Molchanov, A. Vinel and Y. Koucheryavy, the use of automotive radars in video-based overtaking assistance applications. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 3, Sept. 2013. [29] H. Veeraraghavan, O. Masoud, and N. P. Papanikolopoulos, computer vision algorithms for intersection monitoring. IEEE Trans. Intell. Transp. Syst., vol. 4, no. 2, June 2003. [30] X. Yang, X. Li, and K. Xue, A new traffic-signal control for modern roundabouts: Method and application, IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, Dec. 2004. [31] H. Ling and J. Wu, A study on cyclist behavior at signalized intersections. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, Dec. 2004. [32] Y.-K. Ki, and D.-Y. Lee, A traffic accident recording and reporting model at intersections. IEEE Trans. Intell. Transp. Syst., vol. 8, no. 2, June 2007. [33] L. Huang, J. Wu, Cyclists’ path planning behavioral model at unsignalized mixed traffic intersections in china. IEEE Intell. Transp. Sys. Magazine, 13, Summer 2009. [34] H. Zhao, J. Cui, and H. Zha, K. Katabira, X. Shao, and R. Shibasaki, Sensing an intersection using a network of laser scanners and video cameras. IEEE Intell. Transp. Sys. Magazine, 31, Summer 2009. [35] V. Milanés, J. Pérez, E. Onieva and C. González, Controller for urban intersections based on wireless communications and fuzzy logic. IEEE Trans. Intell. Transp. Syst., vol. 11, no. 1, March 2010. [36] G. Vigos and M. Papageorgiou, A simplified estimation scheme for the number of vehicles in signalized links. IEEE Trans. Intell. Transp. Syst., vol. 11, no. 2, June 2010. [37] H. Wang, B. Long, S. Tian, Spiral-shaped driveways: A novel method for traffic circles. IEEE Intell. Transp. Sys. Magazine, 18, Spring 2010. [38] L. Zhao, X. Peng, L. Li and Z. Li, A fast signal timing algorithm for individual oversaturated intersections. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 1, March 2011. [39] G. F. List and M. Cetin, modeling traffic signal control using petri nets. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 3, September 2004. [40] A. D. Febbraro, D. Giglio and N. Sacco, Urban traffic control structure based on hybrid petri nets. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, Dec. 2004. [41] S. Lin, B. D. Schutter, Y. Xi, and H. Hellendoorn, integrated urban traffic control for the reduction of travel delays and emissions, IEEE Trans. Intell. Transp. Syst., vol. 14, no. 4, December 2013. [42] H. Oliveira and P. L. Correia, automatic road crack detection and characterization, IEEE Trans. Intell. Transp. Syst., vol. 14, no. 1, March 2013 [43] M. A. Sotelo, F. J. Rodriguez and L. Magdalena, VIRTUOUS: Vision-based road transportation for unmanned operation on urban - like scenarios. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 2, June 2004. [44] Y. He, H. Wang, and B. Zhang, Color-based road detection in urban traffic scenes. IEEE Trans. Intell. Transp. Syst., vol. 5, no. 4, Dec. 2004. [45] T. X., M. Yang, R. Yang, and C. Wang, CyberC3: A prototype cybernetic transportation system for urban applications. IEEE Trans. Intell. Transp. Syst., vol. 11, no. 1, March 2010. [46] X. Chen, G. Zhou, Y. Yang, and H. Huang, A newly developed safety-critical computer system for china metro. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [47] K. Sohn, Optimizing train-stop positions along a platform to distribute the passenger load more evenly across individual cars. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [48] S. Su, X. Li, T. Tang and Z. Gao, A subway train timetable optimization approach, based on energy-efficient operation strategy, IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [49] G. M. Shafiullah, A. B. M. S. Ali, A. Thompson and P. J. Wolfs, Predicting vertical acceleration of railway wagons using regression algorithms. IEEE Trans. Intell. Transp. Syst., vol. 11, no. 2, June 2010. [50] J. J. García, J. Ureña, A. Hernández, M. Mazo, J. A. Jiménez, F. J. Álvarez, C. De Marziani, A. Jiménez, M. J. Díaz, C. Losada and E. García, Efficient multisensory barrier for obstacle detection on railways. IEEE Trans. Intell. Transp. Syst., vol. 11, no. 3, Sept. 2010. [51] H. Dong, B. Ning, Y. Chen, X. Sun, D. Wen, Y. Hu and R. Ouyang, Emergency management of urban rail transportation based on parallel systems. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [52] S. Lu, S. Hillmansen, T. K. Ho and C. Roberts, Single-train trajectory optimization. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [53] H. Wang, F. Schmid, L. Chen, C. Roberts and T. Xu, A topology-based model for railway train control systems. IEEE Trans. Intell. Transp. Syst., vol. 14, no. 2, June 2013. [54] Q. Miao, F. Zhu, Y. Lv, C. Cheng, C. Chen, and X. Qiu, A game-engine-based platform for modeling and computing artificial transportation systems, IEEE Trans. Intell. Transp. Syst., vol. 12, no. 2, June 2011. [55] J. Li, S. Tang, X. Wang, W. Duan and F.-Y. Wang, Growing artificial transportation systems: A rule-based iterative design process. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 2, June 2011. [56] L. Li, H. Zhang, X. Wang, W. Lu and Z. Mu, Urban transit coordination using an artificial transportation system. IEEE Trans. Intell. Transp. Syst., vol. 12, no. 2, June 2011.
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Details

Primary Language English
Subjects Engineering
Journal Section Articles
Authors

Ahmet Hakan Selçuk

Publication Date April 24, 2019
Submission Date October 16, 2018
Acceptance Date March 21, 2019
Published in Issue Year 2019 Volume: 2 Issue: 1

Cite

APA Selçuk, A. H. (2019). Comparison of perfect/ideal urban transportation system with the others: Total travel times. Akıllı Ulaşım Sistemleri Ve Uygulamaları Dergisi, 2(1), 1-14.