A Traffic Signal Control Algorithm For Emergency Vehicles
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A Traffic Signal Control Algorithm For Emergency Vehicles
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Author : Md Asaduzzaman
language : en
Publisher:
Release Date : 2017
A Traffic Signal Control Algorithm For Emergency Vehicles written by Md Asaduzzaman and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017 with categories.
Signal preemption disrupts normal traffic signal to allow emergency vehicles to pass through the intersection more safely and quickly. In medical emergency situations, EVP (Emergency Vehicle Preemption) offers a faster response to the sufferer which improves the chance of survival. Despite this lifesaving advantage, conventional preemption has some problems which need more attention. Two important issues are increased delay of overall traffic due to preemption and absence of prioritization of conflicting preemption requests. This thesis presents a traffic signal control algorithm that addresses the above. We have used TSP (Transit Signal Priority) techniques to improve the EVP system. TSP is a proven strategy to provide a better quality public transit operation in urban areas. Our proposed algorithm adjusts signal phases using TSP techniques to serve an emergency vehicle. We consider both single and multiple simultaneous emergency vehicle requests. TSP techniques help us to alleviate the impact on general traffic. For multiple emergency vehicle requests, a branch and bound algorithm is developed that prioritizes among conflicting requests. Experiments have been conducted using the VISSIM microscopic traffic simulator. Results show that the proposed traffic control algorithm reduces overall traffic delay by up to 8% compared to conventional EVP system.
Robust Intelligent Traffic Signal Control Within A Vehicle To Infrastructure And Vehicle To Vehicle Communication Environment
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Author : Qing He
language : en
Publisher:
Release Date : 2010
Robust Intelligent Traffic Signal Control Within A Vehicle To Infrastructure And Vehicle To Vehicle Communication Environment written by Qing He and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.
Modern traffic signal control systems have not changed significantly in the past 40-50 years. The most widely applied traffic signal control systems are still time-of-day, coordinated-actuated system, since many existing advanced adaptive signal control systems are too complicated and fathomless for most of people. Recent advances in communications standards and technologies provide the basis for significant improvements in traffic signal control capabilities. In the United States, the IntelliDriveSM program (originally called Vehicle Infrastructure Integration - VII) has identified 5.9GHz Digital Short Range Communications (DSRC) as the primary communications mode for vehicle-to-vehicle (v2v) and vehicle-to-infrastructure (v2i) safety based applications, denoted as v2x. The ability for vehicles and the infrastructure to communication information is a significant advance over the current system capability of point presence and passage detection that is used in traffic control systems. Given enriched data from IntelliDriveSM, the problem of traffic control can be solved in an innovative data-driven and mathematical way to produce robust and optimal outputs. In this doctoral research, three different problems within a v2x environment- "enhanced pseudo-lane-level vehicle positioning", "robust coordinated-actuated multiple priority control", and "multimodal platoon-based arterial traffic signal control", are addressed with statistical techniques and mathematical programming. First, a pseudo-lane-level GPS positioning system is proposed based on an IntelliDriveSM v2x environment. GPS errors can be categorized into common-mode errors and noncommon-mode errors, where common-mode errors can be mitigated by differential GPS (DGPS) but noncommon-mode cannot. Common-mode GPS errors are cancelled using differential corrections broadcast from the road-side equipment (RSE). With v2i communication, a high fidelity roadway layout map (called MAP in the SAE J2735 standard) and satellite pseudo-range corrections are broadcast by the RSE. To enhance and correct lane level positioning of a vehicle, a statistical process control approach is used to detect significant vehicle driving events such as turning at an intersection or lane-changing. Whenever a turn event is detected, a mathematical program is solved to estimate and update the GPS noncommon-mode errors. Overall the GPS errors are reduced by corrections to both common-mode and noncommon-mode errors. Second, an analytical mathematical model, a mixed-integer linear program (MILP), is developed to provide robust real-time multiple priority control, assuming penetration of IntelliDriveSM is limited to emergency vehicles and transit vehicles. This is believed to be the first mathematical formulation which accommodates advanced features of modern traffic controllers, such as green extension and vehicle actuations, to provide flexibility in implementation of optimal signal plans. Signal coordination between adjacent signals is addressed by virtual coordination requests which behave significantly different than the current coordination control in a coordinated-actuated controller. The proposed new coordination method can handle both priority and coordination together to reduce and balance delays for buses and automobiles with real-time optimized solutions. The robust multiple priority control problem was simplified as a polynomial cut problem with some reasonable assumptions and applied on a real-world intersection at Southern Ave. & 67 Ave. in Phoenix, AZ on February 22, 2010 and March 10, 2010. The roadside equipment (RSE) was installed in the traffic signal control cabinet and connected with a live traffic signal controller via Ethernet. With the support of Maricopa County's Regional Emergency Action Coordinating (REACT) team, three REACT vehicles were equipped with onboard equipments (OBE). Different priority scenarios were tested including concurrent requests, conflicting requests, and mixed requests. The experiments showed that the traffic controller was able to perform desirably under each scenario. Finally, a unified platoon-based mathematical formulation called PAMSCOD is presented to perform online arterial (network) traffic signal control while considering multiple travel modes in the IntelliDriveSM environment with high market penetration, including passenger vehicles. First, a hierarchical platoon recognition algorithm is proposed to identify platoons in real-time. This algorithm can output the number of platoons approaching each intersection. Second, a mixed-integer linear program (MILP) is solved to determine the future optimal signal plans based on the real-time platoon data (and the platoon request for service) and current traffic controller status. Deviating from the traditional common network cycle length, PAMSCOD aims to provide multi-modal dynamical progression (MDP) on the arterial based on the real-time platoon information. The integer feasible solution region is enhanced in order to reduce the solution times by assuming a first-come, first-serve discipline for the platoon requests on the same approach. Microscopic online simulation in VISSIM shows that PAMSCOD can easily handle two traffic modes including buses and automobiles jointly and significantly reduce delays for both modes, compared with SYNCHRO optimized plans.
Traffic Signal Preemption For Emergency Vehicles
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Author :
language : en
Publisher:
Release Date : 2006
Traffic Signal Preemption For Emergency Vehicles written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with Electronic traffic controls categories.
Adaptive Traffic Signal Control Using Deep Reinforcement Learning For Network Traffic Incidents
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Author : Tianxin Li (M.S. in Engineering)
language : en
Publisher:
Release Date : 2023
Adaptive Traffic Signal Control Using Deep Reinforcement Learning For Network Traffic Incidents written by Tianxin Li (M.S. in Engineering) and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
Traffic signal control is an essential aspect of urban mobility that significantly impacts the efficiency and safety of transportation networks. Traditional traffic signal control systems rely on fixed-time or actuated signal timings, which may not adapt to the dynamic traffic demands and congestion patterns. Therefore, researchers and practitioners have increasingly turned to reinforcement learning (RL) techniques as a promising approach to improve the performance of traffic signal control. This dissertation investigates the application of RL algorithms to traffic signal control, aiming to optimize traffic flow and reduce congestion. The study develops a simulation model of a signalized intersection and trains RL agents to learn how to adjust signal timings based on real-time traffic conditions. The RL agents are designed to learn from experience and adapt to changing traffic patterns, thereby improving the efficiency of traffic flow, even for scenarios in which traffic incidents occur in the network. In this dissertation, the potential benefits of using RL algorithms to optimize traffic signal control in scenarios with and without traffic incidents were explored. To achieve this, an incident generation module was developed using the open-source traffic signal performance simulation framework that relies on the SUMO software. This module includes emergency response vehicles to mimic the realistic impact of traffic incidents and generates incidents randomly in the network. By exposing the RL agent to this environment, it can learn from the experience and optimize traffic signal control to reduce system delay. The study began with a single intersection scenario, where the DQN algorithm was modeled to form the RL agent traffic signal controller. To improve the training process and model performance, experience replay and target network were implemented to solve the limitations of DQN. Hyperparameter tuning was conducted to find the best parameter combination for the training process, and the results showed that DQN outperformed other controllers in terms of the system-wise and intersection-wise queue distribution and vehicle delay. The study was then extended to a small corridor with 2 intersections and a grid network (2x2 intersection), and the incident generation module was used to expose the RL agent to different traffic scenarios. Again, hyperparameter tuning was conducted, and the DQN model outperformed other controllers in terms of reducing congestion and improving the system performance. The robustness of the DQN performance was also tested with different demands, and the microsimulation results showed that the DQN performance was consistent. Overall, this study highlights the potential of RL algorithms to optimize traffic signal control in scenarios with and without traffic incidents. The incident generation module developed in this study provides a realistic environment for the RL agent to learn and adapt, leading to improved system performance and reduced congestion. In addition, hyperparameter tuning is essential to lay down a solid foundation for the RL training process
Intelligent Pervasive Computing Systems For Smarter Healthcare
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Author : Arun Kumar Sangaiah
language : en
Publisher: John Wiley & Sons
Release Date : 2019-06-21
Intelligent Pervasive Computing Systems For Smarter Healthcare written by Arun Kumar Sangaiah and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-21 with Computers categories.
A guide to intelligent decision and pervasive computing paradigms for healthcare analytics systems with a focus on the use of bio-sensors Intelligent Pervasive Computing Systems for Smarter Healthcare describes the innovations in healthcare made possible by computing through bio-sensors. The pervasive computing paradigm offers tremendous advantages in diversified areas of healthcare research and technology. The authors—noted experts in the field—provide the state-of-the-art intelligence paradigm that enables optimization of medical assessment for a healthy, authentic, safer, and more productive environment. Today’s computers are integrated through bio-sensors and generate a huge amount of information that can enhance our ability to process enormous bio-informatics data that can be transformed into meaningful medical knowledge and help with diagnosis, monitoring and tracking health issues, clinical decision making, early detection of infectious disease prevention, and rapid analysis of health hazards. The text examines a wealth of topics such as the design and development of pervasive healthcare technologies, data modeling and information management, wearable biosensors and their systems, and more. This important resource: Explores the recent trends and developments in computing through bio-sensors and its technological applications Contains a review of biosensors and sensor systems and networks for mobile health monitoring Offers an opportunity for readers to examine the concepts and future outlook of intelligence on healthcare systems incorporating biosensor applications Includes information on privacy and security issues on wireless body area network for remote healthcare monitoring Written for scientists and application developers and professionals in related fields, Intelligent Pervasive Computing Systems for Smarter Healthcare is a guide to the most recent developments in intelligent computer systems that are applicable to the healthcare industry.
User Friendly Intelligent Traffic Signal
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Author : Moumita Deb
language : de
Publisher: LAP Lambert Academic Publishing
Release Date : 2012-04
User Friendly Intelligent Traffic Signal written by Moumita Deb and has been published by LAP Lambert Academic Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-04 with categories.
Today, most of the traffic lights in India are controlled by Programmable Logic Control (PLC). This controller is chosen due to its higher cost and it is not user friendly Programming language. The program could be modified to suit the requirement of any particular traffic lights. This project used the intelligent traffic signal as a controller and it was designed to control the 4-junctions of traffic light. There was 3 mode of operation; Normal mode, Emergency mode and Night mode. In Normal mode, the operation of traffic light have been setting based on the study conducted on the numbers of vehicles move on the road. The traffic light automatically changes to emergency mode operation when there have the emergency vehicle such as police, firebrigade and ambulance use that junction. Third mode is night mode which operate during less traffic are using that junction. The IR transceivers have been used to implement this operation mode.
Advanced Traffic Signal Control Algorithms
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Author : Alexander Skabardonis
language : en
Publisher:
Release Date : 2013
Advanced Traffic Signal Control Algorithms written by Alexander Skabardonis and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with Adaptive control systems categories.
Traffic Signal Preemption For Emergency Vehicles
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Author : United States. Department of Transportation. Intelligent Transportation Systems
language : en
Publisher:
Release Date : 2006
Traffic Signal Preemption For Emergency Vehicles written by United States. Department of Transportation. Intelligent Transportation Systems and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
A Two Stage Interval Valued Neutrosophic Soft Set Traffic Signal Control Model For Four Way Isolated Signalized Intersections
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Author : Endalkachew Teshome Ayele
language : en
Publisher: Infinite Study
Release Date : 2020-12-01
A Two Stage Interval Valued Neutrosophic Soft Set Traffic Signal Control Model For Four Way Isolated Signalized Intersections written by Endalkachew Teshome Ayele and has been published by Infinite Study this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-01 with Mathematics categories.
One of the major problems of both developed and developing countries is traffic congestion in urban road transportation systems. Some of the adverse consequences of traffic congestion are loss of productive time, delay in transportation,increase in transportation cost,excess fuel consumption, safety of people,increase in air pollution level and disruption of day-to-day activities. Researches have shown that among others, traditional traffic control system is one of the main reasons for traffic congestion at traffic junctions. Most countries through out the world use pre-timed / fixed cycle time traffic control systems. But these traffic control systems do not give an optimal signal time setting as they do not take into account the time dependent heavy traffic conditions at the junctions. They merely use a predetermined sequence or order for both signal phase change and time setting. Some times this also leads to more congestion at the junctions. As an improvement of fixed time traffic control method, fuzzy logic traffic control model was developed which takes into account the current traffic conditions at the junctions and works based on fuzzy logic principle under imprecise and uncertain conditions. But as a real life situation,in addition to uncertainty and impreciseness there is also indeterminacy in traffic signal control constraints which fuzzy logic can not handle. The aim of this research is to develop a new traffic signal control model that can solve the limitations of fixed time signal control and fuzzy logic signal control using a flexible approach based on interval-valued neutrosophic soft set and its decision making technique, specially developed for this purpose.We have developed an algorithm for controlling both phase change and green time extension / termination as warranted by the traffic conditions prevailing at any time.
A Longest Queue First Signal Scheduling Algorithm With Quality Of Service Provisioning For An Isolated Intersection
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Author :
language : en
Publisher:
Release Date : 2007
A Longest Queue First Signal Scheduling Algorithm With Quality Of Service Provisioning For An Isolated Intersection written by 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.
In today's face paced society, the need to travel using automobiles is increasingly important. Aside from the road itself, the intersection is the most basic unit of a traffic system. As such, controlling the flow of traffic through intersections in an efficient manner has become a task of the utmost importance. The signal-scheduling algoritm described in this thesis is designed for just such a task. Concepts are drawn from the field of packet switching in computer networks and are applied to the traffic control problem. The method proposed utilizes a maximal weight matching algorithm to minimize the queue sizes at each approach to the intersection. The goal is to provide lower average vehicle delay as compared to a current state-of-the-art traffic signal control method. In particular, a focus is given to providing increased levels of service to high-priority vehicle classes (such as emergency vehicles or large trucks). Because the minimization of vehicle queues forms the basis of the algorithm, it is important to establish the conditions under which the system is guaranteed to be stable (i.e. the queue sizes are finite); to this end, Lyapunov function-based analysis is provided. Using a traffic simulation environment, the proposed control method is compared to control methods currently implemented in the field. The results of the simulations show that the performance gain obtained when using the proposed method can be substantial, particularly in the case where prioritization among multiple classes of vehicles is desired.