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Analytical and Computer Modelling of Transportation Systems for Traffic Bottleneck Resolution: A Hajj Case Study

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Abstract

The rate of advancements in the fields of integrated electronic sensor technology, wireless communications, and efficient software algorithms has enabled us to witness a wide outreach of such technologies in an expanding variety of consumer and industrial applications. Essentially, the integration of such advanced communication systems and efficient computational modelling techniques is used to construct effective transportation systems (TSs) for optimising people/vehicle movement in congested areas. An approach for incorporating efficient TSs in a major candidate application domain is described in this paper for the case of the Hajj pilgrimage traffic scenario, which has a profound impact on several million pilgrims each year. This paper reviews technologies previously considered for Hajj and presents a mathematical model to provide an evaluation of the proposed TS deployment at saturated road intersection points between Holy sites. Significantly, the developed model can be used to obtain fast and accurate performance estimates and provide a guide of how to optimise traffic management policies taken. Analytical results of the proposed transportation model had demonstrated that frequent bottleneck scenarios can be efficiently managed resulting with improved journey times, congestion levels, throughput, and an overall enhancement to the transport-infrastructure capacity utilisation under the constraints of Hajj. The accuracy of this model and its practical use was demonstrated with the simulation results of the computer model. Once validated, the model was used to evaluate the impact of the proposed approach as compared to the existing transportation approach.

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References

  1. Khanafer, M.; Guennoun, M.; Mouftah, H.T.: WSN architectures for intelligent transportation systems. In: 3rd International Conference on New Technologies, Mobility and Security (NTMS) (2009)

  2. Chen, Y.; Cheng, L.; Chen, C.; Ma, J.: Wireless sensor network for data sensing in intelligent transportation system. In: 69th IEEE Vehicular Technology Conference, April 2009

  3. Guo, L.; Fang, W.; Wang, G.; Zheng, L.: Intelligent traffic management system base on WSN and RFID. In: International Conference On Computer and Communication Technologies in Agriculture Engineering (CCTAE), June 2010

  4. Franceschinis, M.; Gioanola, L.; Messere, M.; Tomasi, R.; Spirito, M.A.; Civera, P.: Wireless sensor networks for intelligent transportation systems. In: IEEE 69th Vehicular Technology Conference, Apr 2009

  5. Liu, Y.; Wang, X.; Song, Y.: Application of wireless sensor mesh networks in ITS. In: PACCS ’09. Pacific-Asia Conference on Circuits, Communications and Systems, May 2009

  6. Li, B.; Wang, H.; Yan, B.; Zhang, C.: The research of applying wireless sensor networks to intelligent transportation system (ITS) based On IEEE 802.15.4. In: Proceedings of the 6 International Conference on ITS Telecommunications, June 2006

  7. Peng, L.; Xiao, F.; Ni, Z.: Design for wireless sensor network-based intelligent public transportation system. In: 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication, Aug 2009

  8. Chen, W.; Gao, L.; Chai, Z.; Chen, Z.; Tu, S.: An intelligent guiding and controlling system for transportation network based on wireless sensor network technology. In: The Fifth International Conference on Computer and Information Technology, Sept 2005

  9. Chen, W.; Chen, L.; Chen, Z.; Tu, S.; WITS: A wireless sensor network for intelligent transportation system. In: First International Multi-Symposiums on Computer and Computational Sciences, June 2006

  10. BBC Online—Hajj report. http://www.bbc.co.uk/religion/galleries/hajj

  11. Mohandes, M.; Haleem, M.A.; Abdul-Hussain, A.; Balakrishnan, K.: Pilgrim tracking using wireless sensor network. In: Proceedings of the International Conference on Advanced Information Networking and Applications (2011)

  12. Tayan, O.: A proposed model for optimizing the flow of pilgrims between Holy sites during Hajj using traffic congestion control. In: Proceedings of the International Journal of Engineering and Technology, 10 Apr 2010

  13. Bafaqeeh R., Tanir A., Mufti R.: Shuttle bus system to transport pilgrims from Arafat to Muzdalifah. Arabic technical report, Ministry of Transportation, Saudi Arabia (1992)

  14. Othman F.: Bus transportation system between Hajj ritual sites through a closed loop and its integration with pedestrians. Arabic technical report, Ministry of Transportation, Saudi Arabia (1993)

  15. Hariri, M.; et al.: A feasibility study of using shuttle buses as a transportation system between the Holy sites. Arabic technical report, Hajj Research Center, Umm-al-Qura University, Makkah, Saudi Arabia (1996)

  16. Al-Sabban S.A., Ramadan H.M.: A Simulation study of the shuttle-bus pilgrim transportation system between the Holy sites for the 1422H Hajj Season. J. King Abdulaziz Univ. 16(2), 71–93 (2005)

    Article  Google Scholar 

  17. Seliaman, M.E.; Duffuaa, S.O.; Andijani, A.A.: Evaluating traffic stream models for Nafrah using simulation. In: The 6th Saudi Engineering Conference, KFUPM, Dhahran, Dec 2002

  18. AlGadhi, S.A.H.: Microscopic modeling and simulation of Hajj vehicular traffic during Ifadha. In: Proceedings of the Fifth Saudi Engineering Conference, Mar 1999

  19. Andijani, A.A.; Duffuaa, S.O.; Seliman, M.E.: The use of shuttle bus in Hajj to transport pilgrims: a simulation study. In: Proceedings of the Seventh International Society for Science and Technology (ISSAT) International Conference on Reliability, and Quality in Design, USA (2001)

  20. Seliaman M.E., Duffuaa S., Andijani A.: A Stochastic Simulation Model for the Design of a Shuttle Bus System to Transport Pilgrims in Hajj. Researchgate, Berlin (2013)

    Google Scholar 

  21. Ministry of Hajj: Tracking Hajj shuttle buses using RFID technology. http://www.hajinformation.com/main/m80335.htm. Last accessed April 2011

  22. Malaysia’s Hajj Tracking System: http://www.Islamonline.net. Last accessed 2009

  23. Mohandes, M.; Kousa, M.; Hussain, A.A.: An RFID-based pilgrim identification system. http://faculty.kfupm.edu.sa/EE/ahussain/publications/RFID_JournalPaper_2C.pdf (2008)

  24. Mohandes, M.: Pilgrim tracking system using active RFID wristband tags. Hajj Multaqa

  25. Yamin, M.; Mohammadian, M.; Huang, X.; Sharma, D.: RFID technology and crowded event management. In: International Conference on Computational Intelligence for Modeling Control and Automation (2008)

  26. Hellinga, B.: Innovations for monitoring and enhancing transportation during the Hajj. In: Transport and Crowd Management Workshop, Jeddah, Saudi Arabia, May 2010

  27. Zhu, Y.: Study on intelligent traffic control based BRT. In: 2nd International Workshop on Intelligent Systems and Applications (ISA), Wuhan (2010)

  28. Mihai, H.; Claudiu, D.: GPS based road monitoring system. In: IEEE International Conference on Automation Quality and Testing Robotics (AQTR), July 2010

  29. Chinrungrueng, J.; Sununtachaikul, U.; Triamlumlerd, S.: A vehicular monitoring system with power-efficient wireless sensor networks. In: Proceedings of the 6th International Conference on ITS Telecommunications (2006)

  30. AlGadhi S.A.H.: Macroscopic modeling and simulation of Hajj vehicular traffic during Ifadha from Arafat. J. King Abdulaziz Univ. 13(2), 306–318 (2001)

    Google Scholar 

  31. Kleinrock L.: Computer Applications, vol. 2, Queuing Systems. Wiley-Interscience, London (1976)

    Google Scholar 

  32. AlAwfi, K.: Intelligent system for the management of traffic lights in Medina. In: Proceedings of the Second Scientific Research Forum on Madinah Al-Munawwarrah, Madinah Al-Munawwarrah (2008)

  33. Akimaru H., Kawashima K.: Teletraffic Theory and Applications. Springer, Berlin (1999)

    Book  Google Scholar 

  34. Saraydar, C.; Tekinay, S.; Choi, W.-J.: Efficient vehicular traffic monitoring using mobility management in cellular networks. In: IEEE International Conference on Networking, Sensing and Control, May 2004

  35. Xiaojing, L.; Qingchun, M.; Jianshe, X.; Tianbin, W.; Xuzhu, W.; Peng, D.: The real-time detection technology of city traffic condition based-on GPS system. In: Proceedings of the 4th World Congress on Intelligent Control and Automation, Nov 2002

  36. Lin, C.: The design and realization of the information service system for taxi business based on GPS/GIS. In: International Conference on Logistics Engineering and Intelligent Transportation Systems (LEITS), Nov 2010

  37. Abdulhai, B.; Kattan, L.: Traffic engineering analysis, Chap. 6. In: Kutz, M. (ed.) Handbook of Transportation Engineers. McGraw Hill, New York. ISBN:0071391223, Nov 2003

  38. Takagi H.: Queuing analysis of polling models. Proc. ACM Comput. Surv. 20(1), 5–28 (1988)

    Article  MATH  Google Scholar 

  39. Deng, C.; Xue, L.; Li, W.; Zhou, Z.: The real-time monitoring system for inspecting car based on RFID, GPS and GIS. In: International Conference on Environmental Science and Information Application Technology (ESIAT), Sept 2010

  40. Jain R.: The Art of Computer Systems Performance Analysis: Techniques for Experimental Design, Measurement, Simulation, and Modeling. Wiley, London (1991)

    MATH  Google Scholar 

  41. Xiaohui, S.; Jianping, X.; Jun, Z.; Lei, Z.; Weiye, L.: Application of dynamic traffic flow map by using real time GPS data equipped vehicles. In: 6th International Conference on ITS Telecommunications Proceedings, June 2006

  42. Byon, Y.; Shalaby, A.; Abdulhai, B.: Travel time collection and traffic monitoring via GPS technologies. In: IEEE Intelligent Transportation Systems Conference, Oct 2006

  43. Qingyan, Y.; Qiwen, Z.: Vehicle monitoring system based DGPS application. In: Radar, Oct 1996

  44. Xutao, L,. DongSen, C.; Zhijie, Z.; Yunqiang, S.: Design of transport vehicles remote monitoring system. In: 2nd International Conference on Education Technology and Computer (ICETC), June 2010

  45. Chen, P.; Liu, S.: Intelligent vehicle monitoring system based on GPS, GSM and GIS. In: WASE International Conference on Information Engineering (ICIE), Aug 2010

  46. Dornbush, S.; Joshi, A.: StreetSmart traffic: discovering and disseminating automobile congestion using VANET’s. In: IEEE 65th Vehicular Technology Conference, Apr 2007

  47. Wang, Y.; Zhuang, D.; Shi, R.; Li, S.: A WebGIS-based system model of vehicle monitoring central platform. In: Proceedings. 2005 IEEE International Geoscience and Remote Sensing Symposium, July 2005

  48. El-Medany, W.; Al-Omary, A.; Al-Hakim, R.; Al-Irhayim, S.; Nusaif, M.: A cost effective real-time tracking system prototype using integrated GPS/GPRS module. In: 6th International Conference on Wireless and Mobile Communications (ICWMC), Sept 2010

  49. Lina, Z.; Wei, P.; Xiaoping, W.: Design and implementation of vehicle monitor system based on GIS and GPRS. In: CCDC ’09. Chinese Control and Decision Conference, June 2009

  50. Lipan, F.; Groza, A.: Mining traffic patterns from public transportation GPS data. In: IEEE International Conference on Intelligent Computer Communication and Processing (ICCP), Oct 2010

  51. Calabrese F., Colonna M., Lovisolo P., Parata D., Ratti C.: Real-time urban monitoring using cell phones: a case study in Rome. IEEE Trans. Intell. Transp. Syst. 12(1), 141–151 (2011)

    Article  Google Scholar 

  52. Xue, G.; Li, Z.; Zhu, H.; Liu, Y.: Traffic-known urban vehicular route prediction based on partial mobility patterns. In: 15th International Conference on Parallel and Distributed Systems (ICPADS), Dec 2009

  53. Hu, H.; Fang, L.: Design and implementation of vehicle monitoring system based on GPS/GSM/GIS. In: IITA 2009. Third International Symposium on Intelligent Information Technology Application, Nov 2009

  54. Jing, G.; Guo, Y.; Lu, W.; Sun, B.; Sun, J.; Ren, G.; Sun, H.: Design of an intelligent transportation system based on GPS and GPRS. In: IET International Conference on Wireless, Mobile and Multimedia Networks, Nov 2006

  55. Agarwal, A.; Goel, N.: GPS-RDS enabled location based smart transit. In: 13th International Conference on Intelligence in Next Generation Networks, (ICIN 2009), Oct 2009

  56. Chattaraj, A.; Bansal, S.; Chandra, A.: An intelligent traffic control system using RFID. In: Potentials, IEEE, May–June 2009

  57. Hongjian, W.; Yuelin, T.; Zhi, L.: RFID technology applied in highway traffic management. In: International Conference on Optoelectronics and Image Processing (ICOIP), Nov 2010

  58. Blessingson, W.J.; Jinila, Y.B.: Multi-utility/tracing kit for vehicles using RFID technology. In: Recent Advances in Space Technology Services and Climate Change (RSTSCC), Nov 2010

  59. Liu, X.; Cao, L.; Huang, X.: Highway early warning information system. In: 2nd International Conference on Information Engineering and Computer Science (ICIECS), Dec 2010

  60. Gan, J.; Yuan, L.; Sheng, Z.; Xu, T.: Construction and implementation of an integrated WSID traffic monitoring network system. In: Chinese Control and Decision Conference, June 2009

  61. OMNeT++ Integrated User Development (IDE) User Guide. http://www.omnetpp.org/documentation. Last accessed: Feb 2013

  62. Mustapha, A.M.; Hannan, M.A.; Hussain, A.; Basri, H.: UKM campus bus monitoring system using RFID and GIS. In: 6th International Colloquium on Signal Processing and Its Applications (CSPA), May 2010

  63. Intersection capacity analysis. Massachusetts Department of Transportation, Highway Division, Technical report

  64. Highway capacity manual. Special report-209, Transportation Research Board, Washington DC, (2000)

  65. Cascetta E.: Transportation Systems Engineering: Theory and Methods. Springer, Berlin (2001)

    Book  Google Scholar 

  66. Kerner, B.S.: Theory of breakdown phenomenon at highway bottlenecks. Transp. Res. Rec. J. Transp. Res. Board 1710/2000, 136–144 (2007)

  67. Singh, R.; Dowling, R.: Improved speed–flow relationships: application to transportation planning models. In: Seventh Transportation Research Board (TRB) Conference on the Application of Transportation Planning Methods, Massachusetts (2007)

  68. Ratrout N.T., Rahman S.M.: A comparative analysis of currently used microscopic and macroscopic traffic simulation software. Arab. J. Sci. Eng. (AJSE) 34(1B), 121–133 (2009)

    Google Scholar 

  69. Bertini, R.L.: Toward the systematic diagnosis of freeway bottleneck activation. In: Proceedings of the International IEEE Conference on Intelligent Transportation Systems, pp. 442–447 (2003)

  70. Robertson D., Bretherton R.: Optimizing networks of traffic signals in real time—the SCOOT method. IEEE Trans. Veh. Technol. 40(1), 11–15 (1991)

    Article  Google Scholar 

  71. Sims A., Dobinson K.: The Sydney coordinated adaptive traffic (SCAT) system philosophy and benefits. IEEE Trans. Veh. Technol. 29(2), 130–137 (1980)

    Article  Google Scholar 

  72. Xiaoguang, Y.; Changliang, Y.; Zhizhou, W.: Methodology and strategy of coordinated control for adjacent short-link intersections. In: Proceedings of the International IEEE Conference on Intelligent Transportation Systems, pp. 847–851 (2003)

  73. Ning, Z.; Mirchandani, P.: Analyses of vehicular delays and queues at intersections with adaptive and fixed timing control strategies. In: Proceedings of the 8th International IEEE Intelligent Transportation Systems Conference, pp. 97–102 (2005)

  74. Ciccia, M.; Giglio, D.; Minciardi, R.; Viarengo, M.: A queue-based macroscopic model for performance evaluation of congested urban traffic networks. In: Proceedings of the 2007 IEEE Intelligent Transportation Systems Conference, pp. 922–928, 30 Sept–3 Oct 2007

  75. Wunderlich R., Liu C., Elhanany I., Urbanik T.: A novel signal-scheduling algorithm with quality-of-service provisioning for an isolated intersection. IEEE Trans. Intell. Transp. Syst. 9(3), 536–542 (2008)

    Article  Google Scholar 

  76. Zavalishchin, D.S.; Timofeeva, G.A.: Mathematical modelling of vehicle flow on a crossroads. In: Proceedings of the 18th IEEE International Conference on Control Applications (CCA) and Intelligent Control (ISIC), pp. 849–852, 8–10 July 2008

  77. Manrong, Y.; Zhaosheng, Y.; Feng, L.: Store-and-forward based methods for queue prediction used in the urban bottle-neck intersection. In: 2nd International Conference on Advanced Computer Control (ICACC), pp. 282–286 (2010)

  78. Papamichail, I.; Papageorgiou, M.: Balancing of queues or waiting times on metered dual-branch on-ramps. In: Proceedings of the 13th International IEEE Conference on Intelligent Transportation Systems, pp. 1448–1455, Madeira Island, Portugal, 19–22 Sept 2010

  79. Geroliminis N., Skabardonis A.: Identification and analysis of queue spillovers in city street networks. IEEE Trans. Intell. Transp. Syst. 12(4), 1107–1115 (2011)

    Article  Google Scholar 

  80. Nafi, N.S.; Hasan, M.K.; Abdallah, A.H.: Traffic flow model for vehicular network. In: Proceedings of the International Conference on Computer and Communication Engineering (ICCCE 2012), Kuala Lumpur, 3–5 July 2012

  81. Wei, C.; Xiaolan, L.; Wengfeng, Z.: An optimal adaptive traffic signal control algorithm for intersections group. In: Proceedings of the 8th World Congress on Intelligent Control and Automation, Dalian, China, 21–23 June 2006

  82. Patel, A.; Julius, D.; Radhika, N.: Desynchronisation: the theory of self-organizing algorithms for round-robin scheduling. In: Proceedings of the First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), pp. 87–96 (2007)

  83. Salkham, A.; Cunningham, R.; Garg, A.; Cahill, V.: A collaborative reinforcement learning approach to urban traffic control optimization. In: IEEE/ACM International Conference on Web Intelligence and Intelligent Agent Technology, pp. 560–566 (2008)

  84. Faye, S.; Chaudet, C.; Demeure, I.: A distributed algorithm for adaptive traffic lights control. In: 15th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 1572–1577 (2012)

  85. Ghavami, A.; Kar, K.; Ukkusuri, S.: Delay analysis of signal control policies for an isolated intersection. In: 15th International IEEE Conference on Intelligent Transportation Systems (ITSC), pp. 397–402 (2012)

  86. Anderson, J.; Bell, M.: Travel time estimation in urban road networks. In: IEEE Conference on Intelligent Transportation System, (ITSC ’97), pp. 924–929 (1997)

  87. Cassidy, M.J.: Recent findings on simple attributes of freeway queue formation and propagation. In: Proceedings of the 2001 IEEE Intelligent Transportation Systems Conference, pp. 531–535, Oakland, USA, 25–29 Aug 2001

  88. Yousef K.M., Al-Karaki J.N., Shatnawi A.M.: Intelligent traffic light flow control system using wireless sensor networks. J. Inf. Sci. Eng. 26(3), 753–768 (2010)

    Google Scholar 

  89. Zhou, B.; Cao, J.; Zeng, X.; Wu, H.: Adaptive traffic light control in wireless sensor network-based intelligent transportation system. In: Proceedings of the IEEE Vehicular Technology Conference, Ottawa, Canada, Sept 2010

  90. Zou, F.; Yang, B.; Cao, Y.: Traffic light control for a single intersection based on a wireless sensor network. EURASIP J. Adv. Signal Process. (2010). doi:10.1155/2010/724035

  91. Chen, X.F.; Shi, Z.K.: Real-coded genetic algorithm for signal timing optimization of a single intersection. In: Proceedings of International Conference on Machine Learning and Cybernetics, pp. 1245–1248 (2002)

  92. Houli, D.; Zhiheng, L.; Yi, Z.: Multiobjective reinforcement learning for traffic signal control using vehicular ad hoc network. J. Adv. Signal Process. (2010)

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Tayan, O., Al BinAli, A.M. & Kabir, M.N. Analytical and Computer Modelling of Transportation Systems for Traffic Bottleneck Resolution: A Hajj Case Study. Arab J Sci Eng 39, 7013–7037 (2014). https://doi.org/10.1007/s13369-014-1231-3

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