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All praise goes to almighty Allah, the most merciful and the most benevolent. At the outset I would like to express my deepest gratitude to my supervisor Dr. Md. Hadiuzzaman, Associate Professor, Department of Civil Engineering, BUET, Dhaka for his invaluable guidance, inspiration, passionate directions and continuous support throughout the entire journey of my research work.
I also express my sincere appreciation to the members of the Doctoral committee: Brigadear General K M Salzar Hossain, ndc, psc, Dean, Faculty of CE, MIST; Prof Dr G. M. Jahid Hasan, CE Dept., MIST; Prof Dr Hossain Md Shahin, CEE Dept., IUT; Prof Dr Md Tauhid-Ur-Rahman, CE Dept., MIST; Major Khandaker Sakil Ahmed, PhD, Engrs, CE Dept., MIST; and Major Mohammed Russedul Islam, PhD, Engrs, CE Dept., MIST for their constant supervision, constructive criticism fruitful propositions, invaluable observations, and appropriate corrections in taking the research work at the expected level.
I am grateful to Major General Md Siddiqur Rahman Sardar, SGP, hdmc, psc, the ex-commandant, MIST for his visionary decision of introducing PhD program in MIST and inspiring me to enroll in the program. I am also indebted to present Commandant Major General Md. Abul Khair, ndc for his invaluable guidance and moral support. Sincere obligation to Ex and present Dean of Civil Engineering faculty Brigadier General (Rtd.) Habibur Rahman Kamal, ndc, psc and Brigadier General K M Salzar Hossain, ndc, psc for their unceasing support and encouragement. I am also grateful to Director R&D, Brigadier General Md Gazi Ferooz Rahman for his constant backing. Sincere thanks to Lieutenant Colonel G.M. Azizur Rahman (Rtd.) for his continuous insistence for pursuing PhD program.
Sincere appreciations to all the members of the board of examiners for their invaluable suggestions during defense which has definitely added additional impact to the research work.
I am also grateful to MIST; Maj Md Jahidul Islam, PhD, Assistant Professor Kamrul Islam, Major Tarique, Lecturer Tahmida Hossain Shimu, Captain H. M. Imran Kays, Engrs, Captain Sampa Akter, Engrs, Captain A T M Masum, Engrs and Captain
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Muntahith Mehadi Orvin, Engrs, CE Dept., MIST; Lecturer Sanjana Hossain, CE Dept., BUET, Research Assistant Sarder Rafee Musabbir, Nazmul Haque, Mohammad Rayeedul Kalam Siam, Department of Civil Engineering, BUET for their extensive support and assistance.
I am indebted to my mother and parents-in-laws for their support and inspiration. Special thanks to my beloved wife Fara Jabin Parvez, son Adnaf Shah and daughter Apsara Munir for their sacrifice and continuous encouragement which helped me to stay focused.
Finally I am grateful to all faculties and staffs of Civil Engineering department for their help, assistance, and inspiration in conducting the research work. |
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In Dhaka city traffic operating condition is predominantly non-lane-based and heterogeneous in nature. Accurate measurement of traffic state is the first and principal task for describing and improving such traffic condition. For this, video-based image processing algorithms are preferred over other alternatives. This research initiates with the development of a novel traffic detection algorithm for detecting non-lane-based heterogeneous traffic. The algorithm uses mainly two different parameters: (1) static background; and (2) threshold parameter. The algorithm achieves high accuracy of detection through small computational effort. The qualitative analysis shows that compared to others the proposed algorithm can detect vehicles accurately. The quantitative analysis of the algorithm shows stable Precision-Recall Relationship. The RMSE values computed from ground truth and estimated traffic parameters show that the proposed algorithm outperforms other state of the art algorithms.
Given the difficulty of obtaining variable traffic demands in the real world and the cost and time associated with the field data collection, a controlled environment is needed where the demand can be changed artificially and the overall network performance can be observed. Microscopic simulators (e.g. VISSIM) are capable of providing such controlled environment. In this research a generic calibration tool, VISCAL has been developed, for microscopic simulation parameters in VISSIM environment. The optimization system of the tool is based on three heuristic algorithms: (a) GA; (b) SPSA; (c) SA. VISCAL can be used to calibrate any type (rural, urban etc.) and extent (large, medium etc.) of network.
Again macroscopic traffic flow models play an irreplaceable role in real-time traffic state estimation & prediction and represent the traffic states with the help of aggregated variables. The two most frequently used macroscopic models are the first-order cell transmission model (CTM) and the second-order METANET model.
In this research a 1st order CTM model was developed for non-lane-based heterogeneous urban traffic condition. At first the nature of the fundamental traffic relationships was systematically investigated based on the traffic data. From regression analysis it was concluded that 3rd degree polynomial structure shows the best fit with
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the measured traffic data. As classical CTM tends to simulate inappropriate flow and speed behavior due to simple and linear consideration of FD, a new model was proposed in this research. Detail investigation shows that, the non-linear FD plays the most important role in developing CTM model, for estimating traffic state accurately in heterogeneous traffic operating condition.
Again this research proposes a new second-order macroscopic traffic flow model having the following special features: (1) both the flow and speed dynamics have a normally distributed stochastic term; (2) the FD in the speed dynamics follows Zhang‘s one-parameter polynomial structure and (3) the parameters of the FD are variable over the links. In the model calibration stage, simultaneous optimization of FD parameters and driver-related parameters were conducted. The optimized parameters capture the existing traffic conditions of the respective links quite well. The link-specific FD parameters and the stochastic traffic state influencing terms improve the model performance the most, followed by the Car Following parameter. Proposed model performs most poorly in the absence of FD in the speed dynamics. Thus it can be concluded that FD affects the traffic states very seriously for heterogeneous composition and cannot be dropped off from the speed dynamics for simplicity in control design.
The predicted speed, flow and density from the developed macroscopic model were compared with those from a microscopic simulation model, VISSIM. Four levels of traffic demands viz. light, moderate, heavy and excessive demand levels were applied to evaluate the compatibility of the two models. Based on the performance of the models and comparative analysis, the following main conclusions are found:
i) The prediction of traffic states from the proposed stochastic METANET-based model is generally consistent with that from VISSIM simulation over the whole range of traffic demand levels used in this research.
ii) The MAEs in traffic state estimation of various links do not show any distinct trend with the change of traffic demand levels, thus indicating that the developed macroscopic model performs quite satisfactorily for different traffic demand levels. |
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