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Journal articles on the topic 'Advanced traffic management systems'

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Published: 4 June 2021
Last updated: 8 February 2022

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1

Peters, Joseph I., and King M. Roberts. "Human Factors and Advanced Traffic Management Systems." Proceedings of the Human Factors Society Annual Meeting 36, no. 15 (1992): 1068–72. http://dx.doi.org/10.1518/107118192786749739.

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Advanced Traffic Management Systems (ATMS) are those components of Intelligent Vehicle Highway Systems (IVHS) that integrate traffic detection, communication, and control functions to be responsive to dynamic traffic conditions and increase the efficiency of existing traffic networks. ATMS provide the management foundation that will enable and integrate other IVHS components such as Commercial Vehicle Operations, Advanced Traveler Information Systems, Advanced Vehicle Control Systems, and Advanced Public Transportation Systems. This paper defines Advanced Traffic Management Systems. It also describes the functions that may take place within an ATMS-class Traffic Management Center (TMC), a scenario that a future TMC operator may encounter, and some of the human factors issues that must be addressed in the design of an ATMS-class TMC.
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2

Coconea, Laura, and Emanuele Bellini. "Advanced Traffic Management Systems supporting resilient smart cities." Transportation Research Procedia 41 (2019): 556–58. http://dx.doi.org/10.1016/j.trpro.2019.09.099.

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3

Hawas, Yaser E. "Calibrating Simulation Models for Advanced Traveler Information Systems/Advanced Traffic Management Systems Applications." Journal of Transportation Engineering 128, no. 1 (2002): 80–88. http://dx.doi.org/10.1061/(asce)0733-947x(2002)128:1(80).

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4

Yang, Qi, Haris N. Koutsopoulos, and Moshe E. Ben-Akiva. "Simulation Laboratory for Evaluating Dynamic Traffic Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1710, no. 1 (2000): 122–30. http://dx.doi.org/10.3141/1710-14.

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Advanced traffic management systems (ATMS) and advanced traveler information systems (ATIS) are promising technologies for achieving efficiency in the operation of transportation systems. A simulation-based laboratory environment, MITSIMLab, is presented that is designed for testing and evaluation of dynamic traffic management systems. The core of MITSIMLab is a microscopic traffic simulator (MITSIM) and a traffic management simulator (TMS). MITSIM represents traffic flows in the network, and the TMS represents the traffic management system under evaluation. An important feature of MITSIMLab is its ability to model ATMS or ATIS that generate traffic controls and route guidance based on predicted traffic conditions. A graphical user interface allows visualization of the simulation, including animation of vehicle movements. An ATIS case study with a realistic network is also presented to demonstrate the functionality of MITSIMLab.
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5

Zhang, Chuan, Liehuang Zhu, Jianbing Ni, Cheng Huang, and Xuemin Shen. "Verifiable and Privacy-Preserving Traffic Flow Statistics for Advanced Traffic Management Systems." IEEE Transactions on Vehicular Technology 69, no. 9 (2020): 10336–47. http://dx.doi.org/10.1109/tvt.2020.3005363.

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Vujić, Miroslav, Ivana Šemanjski, and Pero Vidan. "Improving Energy Efficiency by Advanced Traffic Control Systems." Transactions on Maritime Science 4, no. 2 (2015): 119–26. http://dx.doi.org/10.7225/toms.v04.n02.003.

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The problem of traffic congestion is particularly acute in urban areas in which the possibilities for the physical increase of capacities are limited or nonexistent. Traffic congestion has a direct impact on the emission, energy efficiency and fuel consumption of personal vehicles. Several projects in the European Union are focused on solving this problem (both at the physical level – automotive industry, as well as at the traffic management level). This paper explores the possibility of the implementation of advanced traffic control systems in urban areas in which driving behavior involves a multitude of stopand-go actions, lower speeds in lower vehicle gears. Since this type of driving behavior affects vehicle fuel consumption and emission, relevant evaluation parameters were defined (queue length, average vehicle speed, etc.). A demonstration corridor in the city of Zagreb was chosen and a simulation model based on the traffic data collected in real traffic situations developed. The basis for further research is laid down to allow the application of the proposed model and adaptive traffic control algorithms to the greater urban traffic network.
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Gartner, Nathan H., and Chronis Stamatiadis. "Integration of Dynamic Traffic Assignment with Real-Time Traffic Adaptive Control System." Transportation Research Record: Journal of the Transportation Research Board 1644, no. 1 (1998): 150–56. http://dx.doi.org/10.3141/1644-16.

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Intelligent transportation systems (ITS) are being designed to provide real-time control and route guidance to motorists to optimize traffic network performance. Current research and development efforts consist of a dynamic traffic assignment capability that can predict future traffic conditions and a real-time traffic adaptive control system (RT-TRACS) for generation of signal control strategies. Although these models are intimately connected, so far they have developed independently of one another. A framework is presented here for integrating the two models into a combined system with a practical approach for realizing it. First the static case involving the interaction between travelers (demand) and transportation facilities (supply) under recurrent conditions is discussed. This model is applicable in the design and planning of transportation systems management actions. The framework is then extended to the quasi-dynamic and the dynamic cases, which involve incorporation of advanced ITS technologies in the form of advanced traffic management systems and advanced traveler information systems. An innovative application of this framework to advanced traffic-adaptive signal control is presented using the hierarchic structure of RT-TRACS.
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8

Fu, Liping, Jeffrey Henderson, and Shuo Li. "Locating changeable message signs for advanced traffic information and management systems." Canadian Journal of Civil Engineering 34, no. 5 (2007): 651–63. http://dx.doi.org/10.1139/l06-151.

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This paper presents an optimization model for locating changeable message signs (CMSs) on an integrated freeway-arterial network. Compared with existing models, the proposed model represents a well-balanced compromise between computational efficiency required to solve problems of realistic size, and model realism to ensure the quality of solutions. The model has three unique features: (1) it recognizes that locating CMSs is a planning problem that must take into account both current and future needs and benefits, (2) it evaluates benefits of CMSs over multiple time periods with different traffic distributions, and (3) it explicitly considers inherent variations in incident characteristics across links and over time. A sensitivity analysis is performed to examine the potential impacts on optimal CMSs locations resulting from uncertainties in various input parameters, such as traffic demand, incident attributes, and driver behaviour. Lastly, the proposed model is applied to the Highway 401 express-collector freeway system in Toronto for relocating the existing CMSs.Key words: changeable message signs (CMSs), location optimization, traffic assignment, queuing theory.
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9

Daniels, Ginger, and Tim Starr. "Guidelines for Funding Operations and Maintenance of Intelligent Transportation Systems/Advanced Traffic Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1588, no. 1 (1997): 49–62. http://dx.doi.org/10.3141/1588-07.

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As the deployment of intelligent transportation systems (ITS) technologies moves forward, the issue of sustaining and supporting traffic management systems after they have been constructed becomes increasingly critical. In the midst of limited funding, undocumented costs, competing maintenance needs, aging systems, and institutional barriers, the systems already under operation are struggling to meet the expectations conveyed during implementation. Planning for day-to-day performance and upkeep, despite the necessity, has been an unglamourous and apparently secondary consideration in the ITS implementation process. A well-run and well-maintained system not only serves the transportation system users as intended, but boosts the credibility of the program with the public. Conversely, systems that are plagued with inadequate staffing, persistent software bugs, and inoperable field devices will fail to provide high-performance services and will certainly tarnish the ITS initiative and the credibility of all transportation service providers. Quantifying and securing the funding necessary to operate and maintain ITS and advanced traffic management systems adequately is the first step, yet very little documentation is available to assist system operators. First, a mechanism is provided for estimating the costs required to operate and maintain ITS elements adequately; second, the funding issues are examined and guidelines are provided to address the obstacles that prevent adequate funding of traffic management operations and maintenance. Although the Texas Department of Transportation costs and procedures are examined, the research and recommendations will be useful to other state agencies.
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10

Michalopoulos, P., and J. Hourdakis. "Review of non-intrusive advanced sensor devices for advanced traffic management systems and recent advances in video detection." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 215, no. 4 (2001): 345–55. http://dx.doi.org/10.1177/095965180121500407.

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11

Perez, William A., and Truman M. Mast. "Human Factors and Advanced Traveler Information Systems (ATIS)." Proceedings of the Human Factors Society Annual Meeting 36, no. 15 (1992): 1073–77. http://dx.doi.org/10.1518/107118192786749694.

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The nation's motoring public is increasingly burdened by recalcitrant transportation problems, many of them directly attributable to increasing traffic congestion. In response to this, the US. Department of transportation is actively moving on several fronts to address this problem. One of the more promising approaches to relieving congestion is through the design and implementation of new technology in the Intelligent Vehicle/Highway System (IVHS). IVHS is composed of five elements: Advanced Traffic Management Systems (ATMS), Advanced Traveler Information Systems (ATIS), Commercial Vehicle Operations (CVO), Advanced Vehicle Control Systems (AVCS), and Advanced Public Transportation Systems (APTS). This paper will discuss human factors issues associated with ATIS.
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12

Pande, Anurag, and Mohamed Abdel-Aty. "A Freeway Safety Strategy for Advanced Proactive Traffic Management." Journal of Intelligent Transportation Systems 9, no. 3 (2005): 145–58. http://dx.doi.org/10.1080/15472450500183789.

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13

Mika, P. "Regulator Algorithms of Traffic Control Systems." Acta Technica Jaurinensis 9, no. 3 (2016): 183. http://dx.doi.org/10.14513/actatechjaur.v9.n3.399.

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Currently known control algorithm of traffic control systems are based on a model predictive control (MPC). The MPC method implementation uses the Jacobi iteration method, which is effectively a nonlinear programming problem solving algorithm with limitation. The development objective is to reduce congestion, reduce travel time and to ensure consistent traffic flow. The MPC-based control used in any urban transport network, but the measuring system and advanced traffic management equipment is required for the proper operation. In this study, a regulative algorithm of the traffic control systems synchronization for the proper operation is presented.
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14

Zhou, Xu, Zhao Liu, Xiao Xiao Zhao, and Jian Hua Guo. "Framework for Dynamic OD Matrix Estimation Based on Multi-Source Traffic Data Fusion." Applied Mechanics and Materials 505-506 (January 2014): 1153–56. http://dx.doi.org/10.4028/www.scientific.net/amm.505-506.1153.

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The advanced transportation management and information systems (ATMIS) are strengthening the capability of collecting multi-source traffic data constantly from the road networks. Considering the fundamental role of dynamic Origin-Destination data for many advanced traffic management systems, it is promising to apply the multi-source traffic data to improve the dynamic OD estimation. Targeting dynamic OD data estimation, the classical OD data estimation approaches are discussed, and a framework of dynamic OD estimation based on multi-source traffic data is proposed and analyzed. Future researches are recommended in the end.
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15

Balakrishna, Ramachandran, Haris N. Koutsopoulos, Moshe Ben-Akiva, Bruno M. Fernandez Ruiz, and Manish Mehta. "Simulation-Based Evaluation of Advanced Traveler Information Systems." Transportation Research Record: Journal of the Transportation Research Board 1910, no. 1 (2005): 90–98. http://dx.doi.org/10.1177/0361198105191000111.

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Traveler information has the potential to reduce travel times and improve their reliability. Studies have verified that driver overreaction from the dissemination of information can be eliminated through prediction-based route guidance that uses short-term forecasts of network state. Critical off-line tests of advanced dynamic traffic assignment–based prediction systems have been limited, since the system being evaluated has also been used as the test bed. This paper outlines a detailed simulation-based laboratory for the objective and independent evaluation of advanced traveler information systems, a laboratory with the flexibility to analyze the impacts of various design parameters and modeling errors on the quality of the generated guidance. MITSIMLab, a system for the evaluation of advanced traffic management systems, is integrated with Dynamic Network Assignment for the Management of Information to Travelers (DynaMIT), a simulation-based decision support system designed to generate prediction-based route guidance. Evaluation criteria and requirements for the closed-loop integration of MITSIMLab and DynaMIT are discussed. Detailed case studies demonstrating the evaluation methodology and sensitivity of DynaMIT's guidance are presented.
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16

Lecchini-Visintini, Andrea, and John Lygeros. "Air traffic management: Challenges and opportunities for advanced control." International Journal of Adaptive Control and Signal Processing 24, no. 10 (2010): 811–12. http://dx.doi.org/10.1002/acs.1206.

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17

Murray, John, and Yili Liu. "Operator Support in Traffic Management: A Heuristics Model and Experimental Study." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 18 (1996): 872–76. http://dx.doi.org/10.1177/154193129604001801.

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The identification of problems from numeric traffic measurements is an important part of control center activities in ATMS (Advanced Traffic Management Systems). However, an information modeling process that relies solely upon ‘traditional’ quantitative data analysis does not reflect faithfully the actual methods used by human operators. In addition to common-sense knowledge and specific contextual information, operators also use various heuristics and rules-of-thumb to supplement the numerical analysis. This paper describes an experiment to examine the effectiveness of an expert system that integrates quantitative and qualitative traffic information using a human-centered knowledge system design. The system's performance was investigated using a data suite of real traffic scenarios; the statistically significant results showed that the integrated process had superior performance compared to the ‘traditional’ quantitative analysis running alone.
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18

Killick, James. "Data Representation Using a Standard Data Transfer Specification." Journal of Navigation 46, no. 2 (1993): 223–37. http://dx.doi.org/10.1017/s0373463300011565.

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In the 1990s, digital maps are being used for a wide variety of applications. In the world of digital road maps, the most notable applications are in the area of theIntelligent Vehicle Highway Systems (IVHS). In the USA IVHS is involved with five basic interrelated applications:(i) Advanced Traffic Management Systems.(ii) Advanced Vehicle Control Systems.(iii) Commercial Vehicle Operations.(iv) Advanced Public Transportation Systems.(v) Advanced Traveller Information Systems.
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19

Marfia, Gustavo, Marco Roccetti, and Alessandro Amoroso. "A new traffic congestion prediction model for advanced traveler information and management systems." Wireless Communications and Mobile Computing 13, no. 3 (2013): 266–76. http://dx.doi.org/10.1002/wcm.2200.

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20

Jayakrishnan, R., Hani S. Mahmassani, and Ta-Yin Hu. "An evaluation tool for advanced traffic information and management systems in urban networks." Transportation Research Part C: Emerging Technologies 2, no. 3 (1994): 129–47. http://dx.doi.org/10.1016/0968-090x(94)90005-1.

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21

McLin, John L., and William T. Scherer. "Development and Evaluation of a Control System for Regional Traffic Management." Advances in Civil Engineering 2011 (2011): 1–11. http://dx.doi.org/10.1155/2011/724897.

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Traffic congestion is a worsening problem in metropolitan areas which will require integrated regional traffic control systems to improve traffic conditions. This paper presents a regional traffic control system which can detect incident conditions and provide integrated traffic management during nonrecurrent congestion events. The system combines advanced artificial intelligence techniques with a traffic performance model based on HCM equations. Preliminary evaluation of the control system using traffic microsimulation demonstrates that it has the potential to improve system conditions during traffic incidents. In addition, several enhancements were identified which will make the system more robust in a real traffic control setting. An assessment of the control system elements indicates that there are no substantial technical barriers in implementing this system in a large traffic network.
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22

Lou, James Z. "Network and Communication Design of a Work Zone Intelligent Transportation System." Transportation Research Record: Journal of the Transportation Research Board 1910, no. 1 (2005): 64–71. http://dx.doi.org/10.1177/0361198105191000108.

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Road construction on major freeways is a primary cause of traffic incidents and delays. One approach to improve traffic mobility and safety in construction work zones is to use intelligent transportation systems (ITSs), which can effectively enhance work zone traffic management through advanced surveillance and communication technologies. Although conceptually similar to a traditional advanced traffic management system, a work zone ITS has unique network and communication design requirements. The Palm Beach County, Florida, Interim Traffic Management System (ITMS) was a work zone ITS that was successfully deployed in the summer of 2003. Using Palm Beach County ITMS as an example, this paper provides technical guidelines for applying cutting-edge technologies, such as wireless communication, video compression, and Internet protocol encapsulation, in designing a work zone ITS.
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23

Brown, Steven. "ROMANSE Public Transport Information Systems." Journal of Navigation 50, no. 1 (1997): 14–26. http://dx.doi.org/10.1017/s0373463300023547.

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ROMANSE — Road Management System for Europe — is multi-million pound pilot project based in Southampton. It aims to use Advanced Transport Telematics (ATT) to develop the city as a model for transport management systems across Europe. ROMANSE achieves this by providing realtime traffic and travel information to influence travel behaviour, increase the use of public transport, maximize the efficiency of the transport system and provide high-quality information for use in strategic policy decisions.
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24

Klimovich, A. N., and V. N. Shuts. "Crossroad control algorithm based on V2I-interaction." «System analysis and applied information science», no. 4 (February 6, 2019): 21–27. http://dx.doi.org/10.21122/2309-4923-2018-4-21-27.

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The importance of efficient traffic management problem grows every year. Constantly increasing number of vehicles and traffic volume requires improvement of methods and algorithms of traffic control. Such improvement becomes possible due to the spreading of global navigation and positioning systems, the development of wireless communication technologies and mobile internet, the advance in specialized technologies for interaction between vehicles and road infrastructure (V2I), the enhancement of machine learning models, computer vision algorithms, the emergence of driverless cars. This paper considers the novel approach to traffic management at intersection based on the use of V2I communication, describes general scheme of such approach and differences with conventional traffic light regulation. Developed algorithm of intersection management utilizes advantages of V2I communication to increase throughput of the intersection comparing to simple traffic light regulation and more advanced adaptive methods. The increase of throughput is achieved due to the dynamic construction of regulation phases which can be done because of more complete information about traffic flow. The comparence of various methods of regulation was performed in developed traffic simulation environment based on multi-agent approach.
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Hunter, George, Bill Holtzman, Alicia Fernandes, and Corissa Robinson. "Advanced Trajectory Modeling: Stakeholder Needs and Expectations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 61, no. 1 (2017): 115–19. http://dx.doi.org/10.1177/1541931213601494.

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Advanced air traffic control techniques require accurate predictions of aircraft trajectories. Such predictions rely on complex aircraft parameters which typically are unknown and must be estimated. These estimates can be improved with aircraft-to-ground data exchange methods. The Advanced Trajectory Modeling project is exploring such methods, and how they can improve the aircraft data available to the air traffic control trajectory models used by controller and traffic management decision support tools. The project has identified aircraft data, including current state and intent, which could be downlinked to ground automation systems. The project is exploring emerging technologies onboard the aircraft—such as Internet Protocol Data Link, Aircraft Interface Devices, and Electronic Flight Bags—that could be used to extract and downlink these data to ground automation systems. The project is evaluating advanced trajectory models to enable future synchronization of various ground automation trajectory models with aircraft-generated models to support Trajectory Based Operations, an effort that affects a wide range of stakeholders. Here we use a two-phase stakeholder engagement approach to insure the feasibility of the proposed concept.
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26

Sun, Huijun, Jianjun Wu, Wei Wang, and Ziyou Gao. "Reliability-based traffic network design with advanced traveler information systems." Information Sciences 287 (December 2014): 121–30. http://dx.doi.org/10.1016/j.ins.2014.07.036.

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27

Rowell, J. Martin. "Applying Map Databases to Advanced Navigation and Driver Assistance Systems." Journal of Navigation 54, no. 3 (2001): 355–63. http://dx.doi.org/10.1017/s0373463301001503.

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Navigation map databases have evolved during the last 10 years in coverage, content and accuracy to such a degree that they are being used (and considered) for applications beyond vehicle navigation. For a number of advanced driver assistance systems (ADAS) in Europe and North America, the navigation maps are being enhanced to offer new functions. This will complement dynamic route guidance, with location referencing, descriptions of delays, floating car data and re-routeing, all requiring developments in traffic management, road capacity balancing and routing algorithms.
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Li, Ruimin, Hongliang Ma, Huapu Lu, and Min Guo. "Research and Application of the Beijing Road Traffic Prediction System." Discrete Dynamics in Nature and Society 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/316032.

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As an important part of the urban Advanced Traffic Management Systems (ATMS) and Advanced Traveler Information Systems (ATIS), short-term road traffic prediction system has received special attention in recent decades. The success of ATMS and ATIS technology deployment is heavily dependent on the availability of timely and accurate estimation or prediction of prevailing and emerging traffic conditions. We studied a real-time road traffic prediction system developed for Beijing based on various traffic detection systems. The logical architecture of the system was presented, including raw data level, data processing and calculation level, and application level. Four key function servers were introduced, namely, the database server, calculation server, Geographic Information System (GIS) server, and web application server. The functions, function modules, and the data flow of the proposed traffic prediction system were analyzed, and subsequently prediction models used in this system are described. Finally, the prediction performance of the system in practice was analyzed. The application of the system in Beijing indicated that the proposed and developed system was feasible, robust, and reliable in practice.
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Özbay, Kaan, and Shirsendu Mukherjee. "Web-Based Expert Geographical Information System for Advanced Transportation Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1719, no. 1 (2000): 200–208. http://dx.doi.org/10.3141/1719-26.

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The Internet is fast becoming the standard environment for client-server applications that involve multiple users. The proliferation of Internet-based application development tools opens new doors to transportation researchers who work in real-time decision support system development. In the 1990s, one of the most important problems in advanced transportation management systems research was the development of better incident management systems. Although the incident management process has been well studied, the development of real-time decision support systems that can be used by all the involved agencies remains a challenging area of transportation engineering research. Existing incident management systems are developed on various traditional computing platforms, including UNIX and Windows. However, with the advent of the World Wide Web and Internet-based programming tools such as Java, it is possible to develop platform independent decision support tools for the incident management agencies. Web-based support tools offer an invaluable opportunity to develop next-generation online decision support tools for real-time traffic management. The applicability of Web-based tools to the development of online decision support systems for incident management is explored and demonstrated, and a prototype incident management decision support system (DSS) that has most of the capabilities of similar UNIX-based DSS support systems is developed and tested. Briefly described are the implementation and development of a prototype wide-area incident management system using Web-based tools.
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30

Runyoro, Angela-Aida K., Irina Zlotnikova, and Jesuk Ko. "Towards automated road information framework a case study of Tanzania." Transport and Telecommunication Journal 15, no. 1 (2014): 12–19. http://dx.doi.org/10.2478/ttj-2014-0002.

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Abstract Traffic congestion problem has been noticed to have a serious impact on the economy of the country in terms of time wastage, energy consumption costs, human loss and environmental effects. Different strategies have been used so far all over the world as shown in the literature review. Intelligent Transportation System (ITS) is a multi-technology approach that can help to handle the issues and create a complete congestion reduction framework. This paper presents a case study for implementing automated road management system using networks in Tanzania, where three cities highly affected by traffic congestion have been studied. Study results show that these cities have not yet implemented new technologies in road traffic management; instead the traffic is controlled using traffic police officers and traffic lights only. The traffic lights use an old technology that cannot manage traffic in relation to the real-time situations. This study proposes components for a framework, which will assist automation in road traffic management. From the review of various existing ITS of which Advanced Traffic Management System (ATMS) and Advanced Travel Information System (ATIS) are subsystems, we have identified the possibility to integrate the two sub-systems within the framework. Three-phase traffic theory has been referred, FOTO and ASDA models are applied to the automatic recognition and tracking of congested spatiotemporal traffic patterns on roads.
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Ishak, Sherif, and Haitham Al-Deek. "Statistical Evaluation of Interstate 4 Traffic Prediction System." Transportation Research Record: Journal of the Transportation Research Board 1856, no. 1 (2003): 16–24. http://dx.doi.org/10.3141/1856-03.

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Short-term traffic prediction systems have received considerable attention in the past few years as a means to support advanced traveler information and traffic management systems. Predictive information allows transportation system users to make better trip decisions at the pretrip planning stage and en route. A comprehensive statistical analysis of the traffic prediction system performance implemented on the 40-mi corridor of Interstate 4 in Orlando, Florida, is presented. The system was evaluated under a wide range of traffic conditions and various model parameters. The prediction performance in terms of prediction errors was examined with both link-based and path-based approaches.
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32

Reid, K. "The Application of Advanced Systems – An Airline Perspective." Journal of Navigation 47, no. 2 (1994): 177–80. http://dx.doi.org/10.1017/s0373463300012091.

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The achievement of the goals of the International Civil Aviation Organization (ICAO) Future Air Navigation System (FANS) is essential for the continued development of the airline industry. A recently completed movement study for the North Atlantic Track area forecast that the previously anticipated aircraft movements for 2010 would now be achieved by 1999. Peak time capacity growth for the region is now reliant on the introduction of Reduced Vertical Separation Minima (RVSM) scheduled for January 1997. Similarly, Europe had an all-too-evident capacity problem though some alleviation should follow from the introduction of precision area navigation (PRNAV) routeings in early 1998. However, despite the introduction of these developments, the restrictions on flow rates imposed by capacity variations in adjacent areas will remain. Quite obviously, an enhanced and fully capable Air Traffic Management (ATM) environment is required to solve many of the problems that commonly exist today. Nevertheless, more could be achieved through the application and exploitation of advanced navigation equipment such as the aircraft Flight Management Computer System (FMS) that is in widespread use today – a theme that will be returned to later in the paper.
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33

Lecchini-Visintini, Andrea, and John Lygeros. "Special Issue on ‘Air Traffic Management: Challenges and Opportunities for Advanced Control’." International Journal of Adaptive Control and Signal Processing 22, no. 8 (2008): 814. http://dx.doi.org/10.1002/acs.1046.

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34

Jayakrishnan, R., Jun-Seok Oh, and Abd-El-Kader Sahraoui. "Calibration and Path Dynamics Issues in Microscopic Simulation for Advanced Traffic Management and Information Systems." Transportation Research Record: Journal of the Transportation Research Board 1771, no. 1 (2001): 9–17. http://dx.doi.org/10.3141/1771-02.

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35

Huang, Tingting, Subhadipto Poddar, Cristopher Aguilar, et al. "Building Intelligence in Automated Traffic Signal Performance Measures with Advanced Data Analytics." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 18 (2018): 154–66. http://dx.doi.org/10.1177/0361198118791380.

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Automated traffic signal performance measures (ATSPMs) are designed to equip traffic signal controllers with high-resolution data-logging capabilities which may be used to generate performance measures. These measures allow practitioners to improve operations as well as to maintain and operate their systems in a safe and efficient manner. While they have changed the way that operators manage their systems, several shortcomings of ATSPMs, as identified by signal operators, include a lack of data quality control and the extent of resources required to use the tool properly for system-wide management. To address these shortcomings, intelligent traffic signal performance measurements (ITSPMs) are presented in this paper, using the concepts of machine learning, traffic flow theory, and data visualization to reduce the operator resources needed for overseeing data-driven ATSPMs. In applying these concepts, ITSPMs provide graphical tools to identify and remove logging errors and data from bad sensors, to determine trends in demand intelligently, and to address the question of whether or not coordination may be needed at an intersection. The focus of ATSPMs and ITSPMs on performance measures for multimodal users is identified as a pressing need for future research.
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36

Takagi, Tsubasa, and Miwa Nakanishi. "Efficiency-Thoroughness Trade-Off Characteristics of Air Traffic Controllers During Tower Operations." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 64, no. 1 (2020): 1745–49. http://dx.doi.org/10.1177/1071181320641423.

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Air traffic demand has been growing for years and many countries are trying to solve this situation by modernizing their national airspace through advanced automation. Those projects aim to provide a greater level of efficiency while ensuring a safe flow of air traffic. However, human air traffic controllers have been coping with difficult situations and unexpected events by flexibly balancing efficiency and thoroughness throughout their operations. In this study, we conducted an experiment using a simulator depicting air traffic control tower operations and analyzed the trade-off decisions made by humans under varying situations. By doing so, we proposed a model with the aim of applying the results to future air traffic management systems. This could allow those autonomous systems to make decisions that are similar to those of human preferences, which could lead to a proactive management of safety and a higher level of automation acceptance.
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Kumar, Kranti, Manoranjan Parida, and Vinod Kumar Katiyar. "SHORT TERM TRAFFIC FLOW PREDICTION IN HETEROGENEOUS CONDITION USING ARTIFICIAL NEURAL NETWORK." TRANSPORT 30, no. 4 (2013): 397–405. http://dx.doi.org/10.3846/16484142.2013.818057.

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea to avoid traffic instabilities and to homogenize traffic flow in such a way that risk of accidents is minimized and traffic flow is maximized. There is a need to predict traffic flow data for advanced traffic management and traffic information systems, which aim to influence traveller behaviour, reducing traffic congestion and improving mobility. This study applies Artificial Neural Network for short term prediction of traffic volume using past traffic data. Besides traffic volume, speed and density, the model incorporates both time and the day of the week as input variables. Model has been validated using actual rural highway traffic flow data collected through field studies. Artificial Neural Network has produced good results in this study even though speeds of each category of vehicles were considered separately as input variables.
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Iocchi, Luca, Luca Novelli, Luigi Tombolini, and Michele Vianello. "Automatic Real-Time River Traffic Monitoring Based on Artificial Vision Techniques." International Journal of Social Ecology and Sustainable Development 1, no. 2 (2010): 40–51. http://dx.doi.org/10.4018/jsesd.2010040104.

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Artificial vision techniques derived from computer vision and autonomous robotic systems have been successfully employed for river traffic monitoring and management. For this purpose, ARGOS and HYDRA systems have been developed by Achimedes Logica in collaboration with Sapienza University of Rome under the EU initiatives URBAN and MOBILIS for the monitoring of the boat traffic in Venice on the Gran Canal and the harbour area. These advanced systems provide an efficient automatic traffic monitoring to guarantee navigation safety and regular flow while producing and distributing information about the traffic. The systems are based on the processing of digital images that are gathered by survey cell stations distributed throughout the supervised area providing a visual platform on which the system displays recent and live traffic conditions in a synthetic way similar to radar view. ARGOS and HYDRA systems are programmed to automatically recognize and notice situations of great interest in whatever sea or land-targeted security applications including environmental, perimeter, and security control. This article describes the wide spectrum of applications of these two systems, that is, monitoring traffic and automatically tracking position, speed and direction of all vehicles.
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CHEN, ZHONGQIANG, ALEX DELIS, and PETER WEI. "IDENTIFICATION AND MANAGEMENT OF SESSIONS GENERATED BY INSTANT MESSAGING AND PEER-TO-PEER SYSTEMS." International Journal of Cooperative Information Systems 17, no. 01 (2008): 1–51. http://dx.doi.org/10.1142/s0218843008001750.

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Sessions generated by Instant Messaging and Peer-to-Peer systems (IM/P2Ps) not only consume considerable bandwidth and computing resources but also dramatically change the characteristics of data flows affecting both the operation and performance of networks. Most IM/P2Ps have known security loopholes and vulnerabilities making them an ideal platform for the dissemination of viruses, worms, and other malware. The lack of access control and weak authentication on shared resources further exacerbates the situation. Should IM/P2Ps be deployed in production environments, performance of conventional applications may significantly deteriorate and enterprise data may be contaminated. It is therefore imperative to identify, monitor and finally manage IM/P2P traffic. Unfortunately, this task cannot be easily attained as IM/P2Ps resort to advanced techniques to hide their traces including multiple channels to deliver services, port hopping, message encapsulation and encryption. In this paper, we propose an extensible framework that not only helps to identify and classify IM/P2P-generated sessions in real time but also assists in the manipulation of such traffic. Consisting of four modules namely, session manager, traffic assembler, IM/P2P dissector, and traffic arbitrator, our proposed framework uses multiple techniques to improve its traffic classification accuracy and performance. Through fine-tuned splay and interval trees that help organize IM/P2P sessions and packets in data streams, we accomplish stateful inspection, traffic re-assembly, data stream correlation, and application layer analysis that combined will boost the framework's identification precision. More importantly, we introduce IM/P2Ps "plug-and-play" protocol analyzers that inspect data streams according to their syntax and semantics; these analyzers render our framework easily extensible. Identified IM/P2P sessions can be shaped, blocked, or disconnected, and corresponding traffic can be stored for forensic analysis and threat evaluation. Experiments with our prototype show high IM/P2Ps detection accuracy rates under diverse settings and excellent overall performance in both controlled and real-world environments.
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Sun, Xiaofei, Xumei Chen, Yi Qi, Bimin Mao, Lei Yu, and Peijia Tang. "Effects of advanced traffic signal status warning systems on vehicle emission reductions at signalized intersections." Journal of the Air & Waste Management Association 69, no. 4 (2019): 391–401. http://dx.doi.org/10.1080/10962247.2018.1506834.

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Marchal, Fabrice, and André de Palma. "Measurement of Uncertainty Costs with Dynamic Traffic Simulations." Transportation Research Record: Journal of the Transportation Research Board 2085, no. 1 (2008): 67–75. http://dx.doi.org/10.3141/2085-08.

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Nonrecurrent congestion in transportation networks occurs as a consequence of stochastic factors affecting demand and supply. Intelligent transportation systems such as advanced traveler information systems and advanced traffic management systems are designed to reduce the impacts of nonrecurrent congestion by providing information to a fraction of users or by controlling the variability of traffic flows. For these reasons, the design of these systems requires a reliable forecast of nonrecurrent congestion. A new method is proposed to measure the impacts of nonrecurrent congestion on travel costs by taking risk aversion into account. The traffic model is based on the dynamic traffic simulation model METROPOLIS. Incidents are generated randomly by reducing the capacity of the network. Users can instantaneously adapt to the unexpected travel conditions or can also change their behavior through a day-to-day adjustment process. Comparisons with incident-free simulations provide a benchmark for potential travel time savings that can be brought about by a state-of-the-art information system. The impact of variable travel conditions is measured by describing the willingness to pay to avoid risky or unreliable journeys. Indeed, for risk-averse drivers, any uncertainty corresponds to a utility loss. This utility loss is computed for several levels of network disruption. The main result of the study is that the utility loss due to uncertainty is of the same order of magnitude as the total travel costs.
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Mulyanto, Agus, Wisnu Jatmiko, Petrus Mursanto, Purwono Prasetyawan, and Rohmat Indra Borman. "A New Indonesian Traffic Obstacle Dataset and Performance Evaluation of YOLOv4 for ADAS." Journal of ICT Research and Applications 14, no. 3 (2021): 286–98. http://dx.doi.org/10.5614/itbj.ict.res.appl.2021.14.3.6.

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Intelligent transport systems (ITS) are a promising area of studies. One implementation of ITS are advanced driver assistance systems (ADAS), involving the problem of obstacle detection in traffic. This study evaluated the YOLOv4 model as a state-of-the-art CNN-based one-stage detector to recognize traffic obstacles. A new dataset is proposed containing traffic obstacles on Indonesian roads for ADAS to detect traffic obstacles that are unique to Indonesia, such as pedicabs, street vendors, and bus shelters, and are not included in existing datasets. This study established a traffic obstacle dataset containing eleven object classes: cars, buses, trucks, bicycles, motorcycles, pedestrians, pedicabs, trees, bus shelters, traffic signs, and street vendors, with 26,016 labeled instances in 7,789 images. A performance analysis of traffic obstacle detection on Indonesian roads using the dataset created in this study was conducted using the YOLOv4 method.
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Bowman, Brian L., and Larry Crowley. "Impediments to and Methods for Evaluating Safety Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1560, no. 1 (1996): 18–26. http://dx.doi.org/10.1177/0361198196156000104.

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The Intermodal Surface Transportation Efficiency Act (ISTEA) mandates that individual states develop six transportation infrastructure management systems. One of these systems, the safety management system (SMS), focuses on reducing the number of roadway traffic accidents, injuries, and fatalities by considering the safety needs of the driver, vehicle, and roadway. This necessitates cooperation among state, city, and county roadway agencies as well as diverse public and quasi-public agencies. States have made significant advances toward implementing SMSs. The safety community recognizes that it is time to coordinate safety activities and responsibilities. Even if it is not mandated by Congress, as recent actions indicate, a large number of states are expected to implement elements of their SMS work plan. With this implementation comes the need for the evaluation of SMS's effectiveness in increasing traffic safety and ultimately reducing the number and severity of accidents. The challenge in evaluating SMS effectiveness is that many of the activities undertaken will not be directly quantifiable by accident statistics. Discussed here are some of the impediments, concerns, and design issues in an evaluation of SMS effectiveness in increasing traffic safety. Knowledge of these impediments and determination of an appropriate experimental design will enable the prior planning required to perform valid effectiveness evaluations.
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Fan, Qi, Wei Wang, Xiaojian Hu, Xuedong Hua, and Zhuyun Liu. "Space-Time Hybrid Model for Short-Time Travel Speed Prediction." Discrete Dynamics in Nature and Society 2018 (2018): 1–9. http://dx.doi.org/10.1155/2018/7696592.

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Short-time traffic speed forecasting is a significant issue for developing Intelligent Transportation Systems applications, and accurate speed forecasting results are necessary inputs for Intelligent Traffic Security Information System (ITSIS) and advanced traffic management systems (ATMS). This paper presents a hybrid model for travel speed based on temporal and spatial characteristics analysis and data fusion. This proposed methodology predicts speed by dividing the data into three parts: a periodic trend estimated by Fourier series, a residual part modeled by the ARIMA model, and the possible events affected by upstream or downstream traffic conditions. The aim of this study is to improve the accuracy of the prediction by modeling time and space variation of speed, and the forecast results could simultaneously reflect the periodic variation of traffic speed and emergencies. This information could provide decision-makers with a basis for developing traffic management measures. To achieve the research objective, one year of speed data was collected in Twin Cities Metro, Minnesota. The experimental results demonstrate that the proposed method can be used to explore the periodic characteristics of speed data and show abilities in increasing the accuracy of travel speed prediction.
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Kos, Goran, Predrag Brlek, Kristijan Meic, and Kresimir Vidovic. "Increase the Safety of Road Traffic Accidents by Applying Clustering." Romanian Journal of Transport Infrastructure 2, no. 2 (2013): 45–51. http://dx.doi.org/10.1515/rjti-2015-0018.

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Abstract In terms of continual increase of number of traffic accidents and alarming trend of increasing number of traffic accidents with catastrophic consequences for human life and health, it is necessary to actively research and develop methods to combat these trends. One of the measures is the implementation of advanced information systems in existing traffic environment. Accidents clusters, as databases of traffic accidents, introduce a new dimension in traffic systems in the form of experience, providing information on current accidents and the ones that have previously occurred in a given period. This paper proposes a new approach to predictive management of traffic processes, based on the collection of data in real time and is based on accidents clusters. The modern traffic information services collects road traffic status data from a wide variety of traffic sensing systems using modern ICT technologies, creating the most accurate road traffic situation awareness achieved so far. Road traffic situation awareness enhanced by accident clusters' data can be visualized and distributed in various ways (including the forms of dynamic heat maps) and on various information platforms, suiting the requirements of the end-users. Accent is placed on their significant features that are based on additional knowledge about existing traffic processes and distribution of important traffic information in order to prevent and reduce traffic accidents.
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Singh, Karan, and Nikita Malik. "CNN Based Approach for Traffic Sign Recognition System." Advanced Journal of Graduate Research 11, no. 1 (2021): 23–33. http://dx.doi.org/10.21467/ajgr.11.1.23-33.

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Machine Learning (ML) involves making a machine able to learn and take decisions on real-life problems by working with an efficient set of algorithms. The generated ML models find application in different areas of research and management. One such field, automotive technology, employs ML enabled commercialized advanced driver assistance systems (ADAS) which include traffic sign recognition as a part. With the increasing demand for the intelligence of vehicles, and the advent of self-driving cars, it is extremely necessary to detect and recognize traffic signs automatically through computer technology. For this, neural networks can be applied for analyzing images of traffic signs for cognitive decision making by autonomous vehicles. Neural networks are the computing systems which act as a means of performing ML. In this work, a convolutional neural network (CNN) based ML model is built for recognition of traffic signs accurately for decision making, when installed in driverless vehicles.
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Smith, Brian L., David C. Lewis, and Ryan Hammond. "Design of Archival Traffic Databases: Quantitative Investigation into Application of Advanced Data Modeling Concepts." Transportation Research Record: Journal of the Transportation Research Board 1836, no. 1 (2003): 126–31. http://dx.doi.org/10.3141/1836-16.

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Given the enormous quantities of data collected by intelligent transportation systems (ITS), transportation professionals recently have focused on developing archived data user services (ADUS) to facilitate efficient use of these data in myriad transportation analyses. Most ITS systems were designed by using a transactional database design, which is not well suited to support the ad hoc queries required by ADUS. Research investigated the application of data-warehousing concepts to better support the requirements of ADUS. A case study is presented in which an ADUS for the Hampton Roads Smart Traffic Center, the regional freeway management system, was redesigned from a transactional approach to one based on data warehousing. Test queries run by using both approaches demonstrated that dramatic increases in efficiency are achievable through the use of data-warehousing concepts in ADUS.
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48

Mast, Truman M., and Joseph I. Peters. "Intelligent Vehicle Highway Systems (IVHS): Human Factors Issues in Subsystem Development." Proceedings of the Human Factors Society Annual Meeting 36, no. 15 (1992): 1063. http://dx.doi.org/10.1518/107118192786749649.

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Intelligent Vehicle-Highway Systems (IVHS) is a major U.S. Department of Transportation initiative to improve the safety and efficiency of our nation's highways. IVHS includes five related components: Advanced Traffic Management Systems (ATMS); Advanced Traveler Information Systems (ATIS); Commercial Vehicle Operations (CVO); Advanced Vehicle Control Systems (AVCS); and, Advanced Public Transportation Systems (APTS). Although the Federal Highway Administration has initially chosen to address each of these components separately, a number of issues are shared by all components. One critical common element deals with the capabilities of the humans in the system. Appropriate guidelines that consider the needs and capabilities of operators, maintainers, and users will be critical for efficient functioning of each system. Efforts are underway to define and resolve critical human factors issues related to IVHS components. This symposium addresses four of the five more highway related IVHS components. For each of these components, presenters will define the key engineering characteristics, hypothetical scenarios that focus on human-system interfaces, and examples of human factors issues that must be considered in the design of IVHS systems.
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49

Zamyshliaev, A. М. "Premises of the creation of a digital traffic safety management system." Dependability 19, no. 4 (2019): 45–52. http://dx.doi.org/10.21683/1729-2646-2019-19-4-45-52.

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Aim.The digital transformation of the traffic safety management system in JSC RZD involves top-level integration with the operating processes of all business units in terms of integral assessment of the risk of possible events and achievement of specified indicators. The result will be the merger of the traffic safety management system with the processes of all levels of the company’s management enabled by an integrated intelligent system for managing processes and services whose functionality includes real-time traffic safety management.Methods. The paper uses system analysis of existing approaches and methods of processing of large quantities of structured and unstructered data.Results. The paper examines the development stages of train traffic safety management, as well as automated information and control systems that enable traffic safety management. General trends in the creation of systems for collection and processing of information are analyzed. The applicability of such technologies as Big Data, Data Mining, Data Science as part of advanced control systems is shown. The paper examines the performance of the above technologies by analyzing the effect of various factors on the average daily performance of a locomotive, where, at the first level, such factors as average daily run of a locomotive, average trainload are taken into consideration; at the second level, the focus is on the service speed, locomotive turnover at station, etc.; at the sixth level, the focus is on the type of locomotive, its technical state, etc. It is shown that statistical methods of factor analysis and link analysis combined with such other methods of Data Mining as methods of simulation and prediction, the average daily performance of a locomotive can be planned proactively. The author proposes a procedure of migration towards a digital traffic safety management system that would be based on models of interaction of safety and dependability factors of all railway facilities at all railway levels of hierarchy, as well as in association with other factors that have no direct relation to dependability, yet affect the safety of the transportation process.Conclusions. The primary benefit of migration towards Big Data consists in the development of a dynamic model of traffic safety, the elimination of human factor in control systems. Most importantly, it enables the creation within the Russian Railways company (JSC RZD) of an integrated intelligent process and service management system that enables real-time traffic safety management. An extensive process of development and deployment within the company of the URRAN Single Corporate Platform (SCP) enabled executive decision support as regards risk-based functional dependability and safety of transportation facilities. Thus, the URRAN SCP sets the stage for the digital transformation of the traffic safety management system in JSC RZD.
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Gagliardi, Gianfranco, Marco Lupia, Gianni Cario, et al. "Advanced Adaptive Street Lighting Systems for Smart Cities." Smart Cities 3, no. 4 (2020): 1495–512. http://dx.doi.org/10.3390/smartcities3040071.

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This paper reports the results of a recently concluded R&D project, SCALS (Smart Cities Adaptive Lighting System), which aimed at the development of all hardware/software components of an adaptive urban smart lighting architecture allowing municipalities to manage and control public street lighting lamps. The system is capable to autonomously adjust street lamps’ brightness on the basis of the presence of vehicles (busses/trucks, cars, motorcycles and bikes) and/or pedestrians in specific areas or segments of the streets/roads of interest to reduce the energy consumption. The main contribution of this work is to design a low cost smart lighting system and, at same time, to define an IoT infrastructure where each lighting pole is an element of a network that can increase their amplitude. More generally, the proposed smart infrastructure can be viewed as the basis of a wider technological architecture aimed at offering value-added services for sustainable cities. The smart architecture combines various sub-systems (local controllers, motion sensors, video-cameras, weather sensors) and electronic devices, each of them in charge of performing specific operations: remote street segments lamp management, single street lamp brightness control, video processing for vehicles motion detection and classification, wireless and wired data exchanges, power consumptions analysis and traffic evaluation. Two pilot sites have been built up in the project where the smart architecture has been tested and validated in real scenarios. Experimental results show that energy savings of up to 80% are possible compared to a traditional street lamp system.
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