Simulation Based Integrated Control Algorithm For Controlling Shockwave Propagation On Freeways And Queue Spillback At On Ramps
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Simulation Based Integrated Control Algorithm For Controlling Shockwave Propagation On Freeways And Queue Spillback At On Ramps
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Author : Karteek Kumar Allam
language : en
Publisher:
Release Date : 2015
Simulation Based Integrated Control Algorithm For Controlling Shockwave Propagation On Freeways And Queue Spillback At On Ramps written by Karteek Kumar Allam and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with categories.
Heavy traffic flow entering the freeway mainline can cause or worsen congestion on the freeway mainline due to interrupted on-ramp traffic. In order to address this problem, Freeway ramp metering systems are usually deployed to improve the traffic flow on urban freeways. These systems are attended to improve the flow on the freeway by regulating the on-ramp rate entering the freeway. However, amongst all the possible factors contributing to traffic congestion on freeways and arterials connected via ramps, lack of coordination in the operation of various system components is a major source of inefficiency at freeway and ramp conjunctions. Various ramp metering algorithms have been developed in an attempt to solve the unsystematic problem in coordinating the control of freeway, and arterials. Nevertheless, most of the algorithms control actions were selected based on either pre-defined plans or detected traffic condition. Implementation of the algorithms on the field is also a concern because of its excessive data requirements of these algorithms. Furthermore, existence of a range of flow rates in synchronized flow traffic can cause breakdown due to internal perturbations. Many algorithms failed to address the issue of worsening freeway congestion due to upstream traffic at the on-ramp. This research will formulate an integrated ramp metering control algorithm, using real time traffic measurements. Multiple priority objectives are explicitly set up to delay the congestion due to internal perturbations, maintain the throughput of freeway, and to prevent on-ramp vehicles from overflowing into arterials. This algorithm is also formulated to minimize the delays and control the shockwave propagation from the merge location of the on-ramp and the freeway. In order to measure the effectiveness, the proposed algorithm is compared with a traffic responsive algorithm, such as ALINEA (Asservissement LINeaire d'Entree Autoroutiere), and proposed recommendations accordingly. Considering the importance of gap acceptance and internal perturbations in the current research, calibration of the simulation model was conducted. For this purpose, video data was collected capturing the traffic at the merge location of the freeway and on-ramp, from which the accepted gaps and headways of the vehicles merging into the freeway have been extracted. This was given as an input to the VISSIM simulation model for calibration. The simulation test results indicate that the proposed integrated ramp metering algorithm is more effective than the ALINEA and Fixed Time ramp metering algorithms in terms of reducing the system delays and travel time on the freeway, and minimizing the freeway breakdown. Additionally, the proposed algorithm works efficiently at the ramp traffic flow of no more than 580 veh/hr. In other words, the ALINEA likely outperforms the proposed algorithm as the ramp traffic exceeds 580 veh/hr. The contribution of the research will be reflective of the following aspects: 1) developing a method with a supportive algorithm for minimizing the shockwave propagation by dampening shockwave formation of mainline freeway traffic; 2) developing a method with a supportive algorithm to reduce mainline freeway shockwaves by dispatching vehicles from the on-ramp at a flow rate that can best fit in the observed gaps to be available from the freeway traffic; 3) identifying the minimum accepted gaps at the merge location from video observation to develop appropriate gap acceptance parameters; and 4) developing an integrated computing system to provide a fundamental platform for further functionality expansion in the future for study of a multiple-ramp situation at a freeway system.
An Integrated Traffic Responsive Ramp Control Strategy Via Nonlinear State Feedback
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Author : H. Michael Zhang
language : en
Publisher:
Release Date : 1995
An Integrated Traffic Responsive Ramp Control Strategy Via Nonlinear State Feedback written by H. Michael Zhang and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1995 with Express highways categories.
Evaluation Of Ramp Control Algorithms Using A Microscopic Traffic Simulation Laboratory Mitsim
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Author : Masroor Hasan
language : en
Publisher:
Release Date : 1999
Evaluation Of Ramp Control Algorithms Using A Microscopic Traffic Simulation Laboratory Mitsim written by Masroor Hasan and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999 with categories.
Numerical Simulation Of Micro Ramp Control For Oblique Shock Wave Boundary Layer Interactions
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Author : Aaron F. Shinn
language : en
Publisher:
Release Date : 2007
Numerical Simulation Of Micro Ramp Control For Oblique Shock Wave Boundary Layer Interactions written by Aaron F. Shinn and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007 with categories.
Integrated Real Time Freeway On Ramp Control Strategies
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Author : Menahem Eldor
language : en
Publisher:
Release Date : 1976
Integrated Real Time Freeway On Ramp Control Strategies written by Menahem Eldor and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1976 with Electronic traffic controls categories.
Model Predictive Control For Integrating Traffic Control Measures
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Author : András Hegyi
language : en
Publisher:
Release Date : 2003
Model Predictive Control For Integrating Traffic Control Measures written by András Hegyi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Express highways categories.
Development And Evaluation Of Model Based Adaptive Signal Control For Congested Arterial Traffic
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Author : Gang Liu
language : en
Publisher:
Release Date : 2015
Development And Evaluation Of Model Based Adaptive Signal Control For Congested Arterial Traffic written by Gang Liu and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015 with Traffic flow categories.
Under congested conditions, the road traffic states of different arterial links will interact with each other; therefore, it is necessary to understand the behavior of traffic corridors and to investigate corridor-wide traffic coordinated control strategies. In order to achieve this, traffic flow models are applied in signal control to predict future traffic states. Optimization tools are used to search for the best sequence of future control decisions, based on predictions by traffic flow models. A number of model-based adaptive control strategies have been presented in the literature and have been proved effective in practice. However, most studies have modeled the traffic dynamic either at a link-based level or at an individual movement-based level. Moreover, the efficiency of corridor-wide coordination algorithms for congested large-scale networks still needs to be further improved. A hierarchical control structure is developed to divide the complex control problem into different control layers: the highest level optimizes the cycle length, the mid layer optimizes the offsets, and the Model Predictive Control (MPC) procedure is implemented in the lowest layer to optimize the split. In addition, there is an extra multi-modal priority control layer to provide priority for different travel modes. Firstly, MPC is applied to optimize the signal timing plans for arterial traffic. The objectives are to increase the throughput. A hybrid urban traffic flow model is proposed to provide relatively accurate predictions of the traffic state dynamic, which is capable of simulating queue evolutions among different lane groups in a specific link. Secondly, this study expands the dynamic queue concept to the corridor-wide coordination problem. The ideal offset and boundary offsets to avoid spillback and starvation are found based on the shockwave profiles at each signalized intersection. A new multi-objective optimization model based on the preemptive goal programming is proposed to find the optimal offset. Thirdly, the priority control problem is formulated into a multi-objective optimization model, which is solved with a Non-dominated Sorting Genetic Algorithm. Pareto-optimal front results are presented to evaluate the trade-off among different objectives and the most appropriate solution is chosen with high-level information. Performance of the new adaptive controller is verified with software-in-the-loop simulation. The applied simulation environment contains VISSIM with the ASC/3 module as the simulation environment and the control system as the solver. The simulation test bed includes two arterial corridors in Edmonton, Alberta. The simulation network was well calibrated and validated. The simulation results show that the proposed adaptive control methods outperform actuated control in increasing throughput, decreasing delay, and preventing queue spillback.
Feedback Ramp Metering In Intelligent Transportation Systems
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Author : Pushkin Kachroo
language : en
Publisher: Springer Science & Business Media
Release Date : 2003
Feedback Ramp Metering In Intelligent Transportation Systems written by Pushkin Kachroo and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2003 with Technology & Engineering categories.
Feedback Ramp Metering in Intelligent Transportation Systems is the first book on the topic of using feedback control (also called real-time traffic control or adaptive control by some traffic engineers) in ramp metering. It provides traffic theory fundamentals and then the design of feedback controllers for isolated and coordinated ramp metering problems. Software simulation code in Matlab and Paramics is provided in the book so that the reader can get a hands-on feel for the various algorithms. With a large number of examples, illustrations, and original problems, this book is excellent as a textbook or reference book for a senior or graduate level course on the subject, as well as a reference for researchers in related fields.
An Algorithm For Controlling Spillback From Ramp Meters
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Author : Robert L. Gordon
language : en
Publisher:
Release Date : 1996
An Algorithm For Controlling Spillback From Ramp Meters written by Robert L. Gordon and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996 with Computer algorithms categories.
Modeling Vehicular Traffic Shock Wave With Machine Learning Approaches
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Author : Jihyoung Kim
language : en
Publisher:
Release Date : 2016
Modeling Vehicular Traffic Shock Wave With Machine Learning Approaches written by Jihyoung Kim and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with categories.
The current trend of transforming old cities into smart cities has revealed many issues of the modern cities. One of the issues is the prevailing traffic jam on highways of the modern cities. The vehicular shock wave has been a problem on highways since it is one of the main causes of the traffic jam. The combination of heavy traffic and small traffic perturbations or unexpected driver actions are the main causes of shock waves. In order to alleviate road traffic caused by shock waves, it is crucial to have a system that predicts shock waves and informs them to the drivers. In this dissertation, we analyzed 6 months of freeway traffic data of Los Angeles, CA, provided by CalTrans PeMS (Performance Measurement System) and obtained the vehicular shock wave propagation speed of each freeway. Based on this information, we propose a machine learning approaches to predict shock waves. We utilize Hidden Markov Model (HMM) to predict if the shock wave will occur and propagate based on neighboring lanes' traffic information. Addtionally, HMM is used to estimate the probability of lane change from one lane to other lanes based on the occupancy of a lane. Baum-Welch algorithm is used to predict the parameters (occupancy and state). We also utilized Deep Learning (DL) in order to predict the shock wave occurrence and propagation. We compared Stacked AutoEncoder (SAE), Deep Belief Networks (DBN), and HMM for the accuracy of the prediction of shock wave occurrences and propagation. These approaches have been tested on the same PeMS data sets and achieved good accuracy. In the future, our models will be used to include modern collision prevention techniques (e.g., anti-shock wave strategies) to test their efficacy and help to reduce the number of potential accidents and save energy in the process. Also, our models can be used to improve traffic simulators to provide driving patterns that are close to real human's.