52 research outputs found

    Calibration of microsimulation model for tight urban diamond interchange under heterogeneous traffic

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    Traffic simulation models have been widely used to evaluate design alternatives and to help decision-makers to select best design option for prevailing traffic conditions. This study focuses on application of microsimulation model to the performance assessment of Tight Urban Diamond Interchange (TUDI) located in a congested urban setting with population more than 9 million and current transport demand up to 13.5 million daily motorized trips. Geometric and operational data was collected by conducting multiple site visits. Traffic volume data showed the heterogeneous nature of traffic. Microsimulation model; VISSIM was applied and appropriateness of this model and the proposed methodology was assessed based on maximum queue length as Measure of Effectiveness (MOE)

    Development of an Integrated Incident and Transit Priority Management Control System

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    The aim of this thesis is to develop a distributed adaptive control system which can work standalone for a single intersection to handle various boundary conditions of recurrent, non-recurrent congestion, transit signal priority and downstream blockage to improve the overall network in terms of productivity and efficiency. The control system uses link detectors’ data to determine the boundary conditions of all incoming and exit links. Four processes or modules are deployed. The traffic regime state module estimates the congestion status of the link. The incident status module determines the likelihood of an incident on the link. The transit priority module estimates if the link is flagged for transit priority based on the transit vehicle location and type. Finally, the downstream blockage module scans all downstream links and determines their recurrent blockage conditions. Three different urban incident detection models (General Regression Model, Neuro-Fuzzy Model and Binary Logit Model) were developed in order to be adopted for the incident status module. Among these, the Binary Logit Model was selected and integrated with the signal control logic. The developed Binary Logit Model is relatively stable and performs effectively under various traffic conditions, as compared to other algorithms reported in the literature. The developed signal control logic has been interfaced with CORSIM micro-simulation for rigorous evaluations with different types of signal phase settings. The proposed system operates in a manner similar to a typical pre-timed signal (with split or protected phase settings) or a fully actuated signal (with splitphase arrangement, protected phase, or dual ring phase settings). The control decisions of this developed control logic produced significant enhancement to productivity (in terms of Person Trips and Vehicle Trips) compared with the existing signal control systems in medium to heavily congested traffic demand conditions for different types of networks. Also, more efficient outcomes (in terms of Average Trip Time/Person and delay in seconds/vehicle) is achieved for relatively low to heavy traffic demand conditions with this control logic (using Split Pre-timed). The newly developed signal control logic yields greater productivity than the existing signal control systems in a typical congested urban network or closely spaced intersections, where traffic demand could be similarly high on both sides at peak periods. It is promising to see how well this signal control logic performs in a network with a high number of junctions. Such performance was rarely reported in the existing literature. The best performing phase settings of the newly developed signal control were thoroughly investigated. The signal control logic has also been extended with the logic of pre-timed styled signal phase settings for the possibility of enhancing productivity in heavily congested scenarios under a closely spaced urban network. The performance of the developed pre-timed signal control signal is quite impressive. The activation of the incident status module under the signal control logic yields an acceptable performance in most of the experimental cases, yet the control logic itself works better without the incident status module with the Split Pre-timed and Dual Actuated phase settings. The Protected Pre-timed phase setting exhibits benefits by activating the incident status module in some medium congested demand

    Multi-objective traffic signal optimization using 3D mesoscopic simulation and evolutionary algorithms

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    © 2018 Elsevier B.V. Modern cities are currently facing rapid urban growth and struggle to maintain a sustainable development. In this context, “eco-neighbourhoods” became the perfect place for testing new innovative ideas that would reduce congestion and optimize traffic flow. The main motivation of this work is a true and stated need of the Department of Transport in Nancy, France, to improve the traffic flow in a central eco-neighbourhood currently under reconfiguration, reduce travel times and test various traffic control scenarios for a better interconnectivity between urban intersections. Therefore, this paper addresses a multi-objective simulation-based signal control problem through the case study of “Nancy Grand Cœur” (NGC) eco-neighbourhood with the purpose of finding the optimal traffic control plan to reduce congestion during peak hours. Firstly, we build the 3D mesoscopic simulation model of the most circulated intersection (C129) based on specifications from the traffic management centre. The simulation outputs from various scenario testing will be then used as inputs for the optimisation and comparative analysis modules. Secondly, we propose a multi-objective optimization method by using evolutionary algorithms and find the optimal traffic control plan to be used in C129 during morning and evening rush hours. Lastly, we take a more global view and extend the 3D simulation model to three other interconnected intersections, in order to analyse the impact of local optimisation on the surrounding traffic conditions in the eco-neighbourhood. The current proposed simulation-optimisation framework aims at supporting the traffic engineering decision-making process and the smart city dynamic by favouring a sustainable mobility

    Transport Systems: Safety Modeling, Visions and Strategies

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    This reprint includes papers describing the synthesis of current theory and practice of planning, design, operation, and safety of modern transport, with special focus on future visions and strategies of transport sustainability, which will be of interest to scientists dealing with transport problems and generally involved in traffic engineering as well as design, traffic networks, and maintenance engineers

    Decision-Making For Roadway Lane Designation Among Variable Modes

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    Increasing traffic congestion and a shortage of funds available to build new roads are forcing the transportation infrastructure to function at its maximum capacity. The limited road space available on congested urban street networks in major cities in the United States as well as other parts of the world, notably in Eastern Asian countries, represents a challenge to transportation planners and traffic engineers. The available road space is typically partitioned according to a variety of modes: exclusive lanes for bicycles, buses, parking lanes, etc. The current road space allocation for most urban road networks has been modified throughout the years through a process of incremental changes, each tailored to meet a specific demand or to respond to a specific change at the time. The questions in this research are: Is there a way to provide a solution to reduce congestion with minimum resources such as pavement markings and traffic signs? Should different modes of transportation be included in roadway lane designation? What are the best possible scenarios that would provide the best measures of effectiveness? And how can transportation professionals provide a comprehensive analysis to stakeholders to allow them to make an informed decision for lane-use allocation in urban transportation networks? The approach in this study consists of investigating what relationships exist between the lane-use allocation on one hand and the traffic flow, traffic speed, environmental impact, safety impact, mobility, and accessibility on the other. Since not all of the objectives can be transformed into a single monetary dimension, a multi-objective decision-making framework is used to compare different road-allocation scenarios. This method is employed to incorporate multiple and conflicting objectives into a process where all of them are given credence regardless of how well they can be estimated in monetary terms. Further, the suggested decision-making method includes charts as visual tools to help decision-makers understand the results of each objective when corresponding to a specific scenario. The research provides a unique application for a multimodal analysis and a decision-making method not influenced by decision-makers' input, and contributes to the transportation community efforts to improve corridor and network efficiency

    Delay-based Performance Analyses Of Four-legged Signalized Intersections: A Case Study

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    Tez (Yüksek Lisans) -- İstanbul Teknik Üniversitesi, Fen Bilimleri Enstitüsü, 2014Thesis (M.Sc.) -- İstanbul Technical University, Instıtute of Science and Technology, 2014Önümüzdeki çalışmada ortalama taşıt başına gecikme seç timiz örnek kavşakların çalışma durumunu yansıtmak için kullanılmaktadır.  Gecikme sürücünün arzu ettiği ve gerçekte yaşadığı yolculuk zamanların arasındaki fark olarak tanımlanır. Bu çalışmanın yapılmasında İstanbul’daki Pendik mahallesinde olan iki dört kollu ışıklı kavşak örnek olarak alınmıştır. Biran önce 7:00-10:00, 12:00-14:00 ve 16:30-19:30 Saatlar arasında kamera ile çekim yapılmıştır. Sonra kamera görüntüleri bilgisayar ortamına aktarılıp ve bunlar üzerinden türel ayrımı yaparak 15’r dakikalık zaman dilimleri halinde her yöne giden trafik hacimleri belirlenmiştir. Bu bilgiler ışığında her kol da ve her akım için en fazla taşıt bulunan saat zirve saat olarak tanımlanmıştır. Sonra, zirve saat faktörü (ZSF) zirve saat hacmin akım değerine bölerek her kol için elde edilmişte.  Zirve saat faktörün kullanarak her kol için düzeltilmiş hacim hesaplanmıştır. Sonunda bu akım değerleri VISSIM’e aktarılıp ve oluşturdumuz benzetim model bu verilere göre kalibre edilmiştir. Kalibrasiyon süreci modelin gerçeke yakın çalışmasın sağlar ve sonuçta elde edilmiş sonuçlara daha fazla güvenile bilir. Bu çalışmada kalibrasiyon araç sayısına göre tüm kollarda yapılıp ve benzetim modelin gerçeğe ne kadar yaklaştığı GEH değeri ile ölçülmektedir. Benzetim kalibrasiyonu yapıldıktan sonra elde edilen akım değerleri kayıt edilip ve bu çalışmanın tüm yöntemlerinde akım değeri olarak kullanılmaktadır.  VISSIM’de elde edilen veriler ışığında Amerikan (HCM) ve Avusturalya (Akçelik) yöntemlerin kullanarak seçtimiz kavşakların performansı belirlrnmektedir. Aslında genel Avustralya ve HCM yöntemleri VISSIM’in dinamik yöntem ile karşılaştırılmıştır. Sonunda bu yöntemlerden elde edilen sonuçlar birbiri ile karşılaştırılmış ve olası nedenler tartışılmıştır.For conducting this study, two for-legged signalized intersections in Pendik area of Istanbul city were designated as case studies. Traffic flows obtained using camera recording method at sites between 7:00-10:00, 12:00-14:00 and 16:30-19:30 time periods. Then, all the recordings were transformed to the computer and the frequency of different types of vehicles in 15-min periods were counted and tabulated with respect to their travel directions. Subsequently, on each approach and for each travel direction, the hour during which maximum traffic volume occurs was designated as its peak hour. In continue, peak hour factors (PHF) were calculated for each approach by dividing the peak hour volume to the flow rate of that approach. Using this PHF factor the adjusted flow rate was computed for each lane group.  Finally, these flow rates were transformed to the VISSIM, and the established models were calibrated to replicate the field situation subsequently, and the final volumes yielded by the VISSIM after calibration process were used as this study flow rate inputs in all methods. Employing these data the performance of case studies were estimated applying Australian (Akcelik) and USA (HCM 2000) methods as well as PTV VISSIM software. That is, the conventional methods of Australian and USA were compared with dynamic method of VISSIM. Finally, the results derived from these four methods were analyzed and differences between these methods and possible reasons were discussed.Yüksek LisansM.Sc

    Doctor of Philosophy

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    dissertationTraffic congestion is an increasing problem in most urban areas in the United States. One of the sources of this problem is the automobile-oriented development that encourages automobile use and suppresses other transportation modes. A good transit system can satisfy most of the requirements of a transportation system user. A transit system must be efficient, safe, comfortable, and competitive to private cars in order to attract more riders. Transit Signal Priority (TSP) is an operational strategy that facilitates transit vehicles at signalized intersections. It improves transit efficiency and helps transit offer travel times competitive to private cars. A lot of studies conducted in the past 40 years show the major possibilities and benefits of TSP. The goal of this research is to develop a simulation-based methodology for the evaluation and improvement of TSP strategies. The objectives consist of evaluating existing and future TSP systems, and developing field-ready algorithms that provide adaptive ways for achieving different levels of TSP and improving its operation. The focus of the research is on using traffic microsimulation to evaluate and improve TSP, but it also looks into some field-based implementations and evaluations for additional support. The analysis of different TSP strategies is performed on existing and future rapid transit mode implementations, namely Bus Rapid Transit (BRT) and Light Rail Transit (LRT). The results from the presented studies show the major benefits of TSP implementations for transit operations and small disruptions for vehicular traffic. Depending on the selected strategies and level of TSP, the travel time savings for transit can be between 10% and 30%, the reduction in intersection delay can exceed 60%, while running time reliability and headway adherence are greatly improved. These improvements in transit operations can make transit more efficient and competitive to private cars, justifying the TSP implementation. This research offers significant contributions to the state of TSP practice and research. It provides detailed insights into TSP operations, develops methods for its evaluation, and describes algorithms for achieving different levels of TSP. A significant part of the research is dedicated to the use of Software-in-the-Loop (SIL) traffic controllers in microsimulation. Through this research, SIL is proven to be a powerful tool for simulating complex traffic signal operations and TSP

    Urban arterial lane flow distribution: a before and after traffic microsimulation analysis on the effect of implementing new route markings and signage.

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    Urban arterials may not effectively utilize available lanes to move vehicles efficiently as drivers try to establish position along the corridor. This study evaluates lane flow distribution before and after implementing new route markings and overhead signs to utilize existing lanes better. A cellphone-based traffic data service called StreetLight gathered the traffic data used to establish the VISSIM model parameters for simulating current and projected conditions. This study shows that the lane assignment signage and route markers affected the lane flow distribution in the simulation. The simulation indicated the existing condition had average queue lengths of 320.6 meters, average travel times of 389.5 seconds, an average stop delay of 259.6 seconds, and an average lane flow distribution in the right lane of 76.1%. Upon implementing new route markers and sign installations, the projected simulation showed average queue lengths of 39.0 meters, average travel times of 171.4 seconds, an average delay of 92.5 seconds, and an average lane flow distribution in the right lane of 47.4%

    Parameter Calibration Method of Microscopic Traffic Flow Simulation Models based on Orthogonal Genetic Algorithm

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    Abstract-Traffic microscopic traffic simulation models have become extensively used in both transportation operations and management analyses, which are very useful in reflecting the dynamic nature of transportation system in a stochastic manner. As far as the microscopic traffic flow simulation users are concerned, the one of the major concerns would be the appropriate calibration of the simulation models. In this paper a parameter calibration method of microscopic traffic flow simulation models based on orthogonal genetic algorithm is presented. In order to improve the capacity of locating a possible solution in solution space, the proposed method incorporates the orthogonal experimental design method into the genetic algorithm. The proposed method is applied to an arterial section of Ronghua Road in Beijing. Through comparing with the parameter calibration method based on genetic algorithm, the advantage of the proposed method is shown

    An artificial neural network model for predicting freeway work zone delays with big data

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    Lane closures due to road reconstruction and maintenance have resulted in a major source of non-recurring congestion on freeways. It is extremely important to accurately quantify the associated mobility impact so that a cost-effective work zone schedule and an efficient traffic management plan can be developed. Therefore, the development of a sound model for predicting delays or road users is desirable. A comprehensive literature review on existing work zone delay prediction models (i.e., deterministic queuing model and shock wave model) is conducted in this study, which explores the advantages, disadvantages, and limitations of different modeling approaches. The performance of those models seems restricted to predict congestion impact under space-varying (i.e., road geometry, number of lanes, lane width, etc.) and time-varying (i.e., traffic volume) conditions. To advance the delay prediction accuracy, a multivariate non-linear regression (MNR) model is developed first by incorporating big data to capture the relationship of speed versus the ratio of approaching traffic volume to work zone capacity for work zone delay prediction. The MNR model demonstrates itself able to predict spatio-temporal delays with reasonable accuracy. A more advanced model called ANN-SVM is developed later to further improve the prediction accuracy, which integrates a support vector machine (SVM) model and an artificial neural network (ANN) model. The SVM model is responsible to predict work zone capacity, and the ANN model is responsible to predict delays. The ultimate goal of ANN-SVM aims to predict spatio-temporal delays caused by a work zone on freeways in the statewide of New Jersey subject to road geometry, number of lane closure, and work zone duration in different times of a day and days of a week. There are 274 work zones with complete information for the proposed model development, which are identified by mapping data from different sources, including OpenReach, Plan4Safety, New Jersey Straight Line Diagram (NJSLD), New Jersey Congestion Management System (NJCMS), and INRIX. Big data analytics is used to examining this massive data for developing the proposed model in a reliable and efficient way. A comparative analysis is conducted by comparing the ANN-SVM results with those produced by MNR, RUCM (NJDOT Road User Cost Manual approach), and ANN-HCM (the ANN model with work zone capacity suggested by Highway Capacity Manual). It is found that ANN-SVM in general outperforms other models in terms of prediction accuracy and reliability. To demonstrate the applicability of the proposed model, an analysis tool, which adapts to ANN-SVM, is developed to produce graphical information. It is worth noting that the analysis tool is very user friendly and can be easily applied to assess the impact of any work zones on New Jersey freeways. This tool can assist transportation agencies visualize bottlenecks and congestion hot spots caused by a work zone, effectively quantify and assess the associated impact, and make suitable decisions (i.e., determining the best starting time of a work zone to minimize delays to the road users). Furthermore, ANN-SVM can be applied to develop, evaluate, and improve traffic management and congestion mitigation plans and to calculate contractor penalty based on cost overruns as well as incentive reward schedule in case of early work competition
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