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Letteratura scientifica selezionata sul tema "Traffic engineering – Data processing"

Autore: Grafiati

Pubblicato: 4 giugno 2021

Ultima modifica: 30 gennaio 2023

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Articoli di riviste sul tema "Traffic engineering – Data processing"

1

Knoop, Victor L., Serge P. Hoogendoorn, and Henk J. van Zuylen. "Processing Traffic Data Collected by Remote Sensing." Transportation Research Record: Journal of the Transportation Research Board 2129, no. 1 (January 2009): 55–61. http://dx.doi.org/10.3141/2129-07.

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2

Tarko, Andrzej P., and Nagui M. Rouphail. "Intelligent Traffic Data Processing for ITS Applications." Journal of Transportation Engineering 123, no. 4 (July 1997): 298–307. http://dx.doi.org/10.1061/(asce)0733-947x(1997)123:4(298).

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3

Mallikarjuna, C., A. Phanindra, and K. Ramachandra Rao. "Traffic Data Collection under Mixed Traffic Conditions Using Video Image Processing." Journal of Transportation Engineering 135, no. 4 (April 2009): 174–82. http://dx.doi.org/10.1061/(asce)0733-947x(2009)135:4(174).

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4

Sun, Yuan, Hao Xu, Jianqing Wu, Jianying Zheng, and Kurt M. Dietrich. "3-D Data Processing to Extract Vehicle Trajectories from Roadside LiDAR Data." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 45 (June 8, 2018): 14–22. http://dx.doi.org/10.1177/0361198118775839.

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High-resolution vehicle data including location, speed, and direction is significant for new transportation systems, such as connected-vehicle applications, micro-level traffic performance evaluation, and adaptive traffic control. This research developed a data processing procedure for detection and tracking of multi-lane multi-vehicle trajectories with a roadside light detection and ranging (LiDAR) sensor. Different from existing methods for vehicle onboard sensing systems, this procedure was developed specifically to extract high-resolution vehicle trajectories from roadside LiDAR sensors. This procedure includes preprocessing of the raw data, statistical outlier removal, a Least Median of Squares based ground estimation method to accurately remove the ground points, vehicle data clouds clustering, a principle component-based oriented bounding box method to estimate the location of the vehicle, and a geometrically-based tracking algorithm. The developed procedure has been applied to a two-way-stop-sign intersection and an arterial road in Reno, Nevada. The data extraction procedure has been validated by comparing tracking results and speeds logged from a testing vehicle through the on-board diagnostics interface. This data processing procedure could be applied to extract high-resolution trajectories of connected and unconnected vehicles for connected-vehicle applications, and the data will be valuable to practices in traffic safety, traffic mobility, and fuel efficiency estimation.

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5

Zhao, Liangbin, Guoyou Shi, and Jiaxuan Yang. "Ship Trajectories Pre-processing Based on AIS Data." Journal of Navigation 71, no. 5 (April 22, 2018): 1210–30. http://dx.doi.org/10.1017/s0373463318000188.

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Data derived from the Automatic Identification System (AIS) plays a key role in water traffic data mining. However, there are various errors regarding time and space. To improve availability, AIS data quality dimensions are presented for detecting errors of AIS tracks including physical integrity, spatial logical integrity and time accuracy. After systematic summary and analysis, algorithms for error pre-processing are proposed. Track comparison maps and traffic density maps for different types of ships are derived to verify applicability based on the AIS data from the Chinese Zhoushan Islands from January to February 2015. The results indicate that the algorithms can effectively improve the quality of AIS trajectories.

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6

Ivanov, Alexander, and Alexander Platov. "Environmental monitoring based on data processing of Internet of Things." E3S Web of Conferences 136 (2019): 01041. http://dx.doi.org/10.1051/e3sconf/201913601041.

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The concept of online monitoring of the urban environment is proposed. It is based on the online processing of hydrometeorological and traffic information received through the Internet of Things. The traditional approach of the Internet of things includes transfer and storage of huge arrays of measurements in digital form. This concept of online monitoring is primarily an analysis, evaluation of the results of processing information received from wireless networks. The concept was implemented at Nizhny Novgorod State University of Architecture and Civil Engineering in several services including Eco-routes, Quite-routes, in which the air pollution of the urban environment by vehicle emissions and the noise level from traffic flows are estimated in real time mode. The calculation is based on meteorological data and traffic flow velocity. The calculation and assessment of environment pollution is carried out at the request of the user via Internet. The concept includes micro weather and algal blooming monitoring of reservoirs and ponds. Developed services is the first to provide free short time health risk assessment for both decision makers and common internet users.

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7

Zhao, Ming, Norman W. Garrick, and Luke E. K. Achenie. "Data Reconciliation–Based Traffic Count Analysis System." Transportation Research Record: Journal of the Transportation Research Board 1625, no. 1 (January 1998): 12–17. http://dx.doi.org/10.3141/1625-02.

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Traffic volume data, especially average annual daily traffic (AADT), are important in transportation engineering. They are required in managing and maintaining existing facilities and in planning and designing new facilities. Many state highway agencies use the ramp counting procedure described in FHWA’s Traffic Monitoring Guide to estimate AADTs for freeways. The procedure involves counting all entrance and exit ramps between two established mainline counters (anchor points) and then reconciling the count data to estimate mainline AADT. The reconciling of count data includes three steps. First, AADTs for the ramps and the anchor points are estimated from the count data. Then AADT for each uncounted mainline link is calculated by addition or subtraction of ramp AADT to or from mainline AADT, starting from one anchor point. Finally, adjustments of the AADT are performed to achieve a match at the second anchor point if necessary. The process can be time-consuming and labor-intensive if it is done manually. A computer program to automate the process is required. The traffic count analysis system (TCAS) developed to automate the reconciling of count data in the ramp counting process is described. The TCAS was developed on the basis of data coaptation and data reconciliation techniques frequently used in the processing of network flow rate data. Data coaptation is used to calculate flow rates for uncounted links, and data reconciliation is used to adjust and balance the flow rates. The TCAS has been tested for the two longest freeways in Connecticut. The results are close to those from the ramp counting procedure. However, the TCAS significantly reduces the time and labor required for processing traffic volume data for freeways.

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8

Zhihuang Jiang. "Traffic Operation Data Analysis and Information Processing Based on Data Mining." Automatic Control and Computer Sciences 53, no. 3 (May 2019): 244–52. http://dx.doi.org/10.3103/s0146411619030040.

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9

Zhou, Xin. "Research on Front-End Fusion Processing Technology of Traffic Scenes." Journal of Architectural Research and Development 6, no. 2 (March 4, 2022): 1–7. http://dx.doi.org/10.26689/jard.v6i2.3707.

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With the intelligent development of road traffic control and management, higher requirements for the accuracy and effectiveness of traffic data have been put forward. The issue of how to collect and integrate data for traffic scenes has sought importance in this field as various treatment technologies have emerged. A lot of research work have been carried out from the theoretical aspect to engineering application.

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10

Chronopoulos, Anthony Theodore, and Gang Wang. "Traffic Flow Simulation through Parallel Processing." Transportation Research Record: Journal of the Transportation Research Board 1566, no. 1 (January 1996): 31–38. http://dx.doi.org/10.1177/0361198196156600104.

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Numerical methods for solving traffic flow continuum models have been studied and efficiently implemented in traffic simulation codes in the past. Explicit and implicit methods have been used in traffic simulation codes in the past. Implicit methods allow a much larger time step size than explicit methods to achieve the same accuracy. However, at each time step a nonlinear system must be solved. The Newton method, coupled with a linear iterative method (Orthomin), is used. The efficient implementation of explicit and implicit numerical methods for solving the high-order flow conservation traffic model on parallel computers was studied. Simulation tests were run with traffic data from an 18-mile freeway section in Minnesota on the nCUBE2 parallel computer. These tests gave the same accuracy as past tests, which were performed on one-processor computers, and the overall execution time was significantly reduced.

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Tesi sul tema "Traffic engineering – Data processing"

1

賴翰笙 and Hon-seng Lai. "An effective methodology for visual traffic surveillance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2000. http://hub.hku.hk/bib/B30456708.

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2

Lam, Fung, and 林峰. "Internet inter-domain traffic engineering and optimizatioon." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2001. http://hub.hku.hk/bib/B31224581.

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3

Wolf, Jean Louise. "Using GPS data loggers to replace travel diaries in the collection of travel data." Diss., Georgia Institute of Technology, 2000. http://hdl.handle.net/1853/20203.

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4

Mawji, Afzal. "Achieving Scalable, Exhaustive Network Data Processing by Exploiting Parallelism." Thesis, University of Waterloo, 2004. http://hdl.handle.net/10012/779.

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Telecommunications companies (telcos) and Internet Service Providers (ISPs) monitor the traffic passing through their networks for the purposes of network evaluation and planning for future growth. Most monitoring techniques currently use a form of packet sampling. However, exhaustive monitoring is a preferable solution because it ensures accurate traffic characterization and also allows encoding operations, such as compression and encryption, to be performed. To overcome the very high computational cost of exhaustive monitoring and encoding of data, this thesis suggests exploiting parallelism. By utilizing a parallel cluster in conjunction with load balancing techniques, a simulation is created to distribute the load across the parallel processors. It is shown that a very scalable system, capable of supporting a fairly high data rate can potentially be designed and implemented. A complete system is then implemented in the form of a transparent Ethernet bridge, ensuring that the system can be deployed into a network without any change to the network. The system focuses its encoding efforts on obtaining the maximum compression rate and, to that end, utilizes the concept of streams, which attempts to separate data packets into individual flows that are correlated and whose redundancy can be removed through compression. Experiments show that compression rates are favourable and confirms good throughput rates and high scalability.

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Wang, Hong Feng. "IGP traffic engineering : a comparison of computational optimization algorithms." Thesis, Stellenbosch : Stellenbosch University, 2008. http://hdl.handle.net/10019.1/20877.

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Thesis (MSc)--Stellenbosch University, 2008.<br>ENGLISH ABSTRACT: Traffic Engineering (TE) is intended to be used in next generation IP networks to optimize the usage of network resources by effecting QoS agreements between the traffic offered to the network and the available network resources. TE is currently performed by the IP community using three methods including (1) IGP TE using connectionless routing optimization (2) MPLS TE using connection-oriented routing optimization and (3) Hybrid TE combining IGP TE with MPLS TE. MPLS has won the battle of the core of the Internet and is making its way into metro, access and even some private networks. However, emerging provider practices are revealing the relevance of using IGP TE in hybrid TE models where IGP TE is combined with MPLS TE to optimize IP routing. This is done by either optimizing IGP routing while setting a few number of MPLS tunnels in the network or optimizing the management of MPLS tunnels to allow growth for the IGP traffic or optimizing both IGP and MPLS routing in a hybrid IGP+MPLS setting. The focus of this thesis is on IGP TE using heuristic algorithms borrowed from the computational intelligence research field. We present four classes of algorithms for Maximum Link Utilization (MLU) minimization. These include Genetic Algorithm (GA), Gene Expression Programming (GEP), Ant Colony Optimization (ACO), and Simulated Annealing (SA). We use these algorithms to compute a set of optimal link weights to achieve IGP TE in different settings where a set of test networks representing Europe, USA, Africa and China are used. Using NS simulation, we compare the performance of these algorithms on the test networks with various traffic profiles.<br>AFRIKAANSE OPSOMMING: Verkeersingenieurswese (VI) is aangedui vir gebruik in volgende generasie IP netwerke vir die gebruiksoptimering van netwerkbronne deur die daarstelling van kwaliteit van diens ooreenkomste tussen die verkeersaanbod vir die netwerk en die beskikbare netwerkbronne. VI word huidiglik algemeen bewerkstellig deur drie metodes, insluitend (1) IGP VI gebruikmakend van verbindingslose roete-optimering, (2) MPLS VI gebruikmakend van verbindingsvaste roete-optimering en (3) hibriede VI wat IGP VI en MPLS VI kombineer. MPLS is die mees algemene, en word ook aangewend in metro, toegang en selfs sommige privaatnetwerke. Nuwe verskaffer-praktyke toon egter die relevansie van die gebruik van IGP VI in hibriede VI modelle, waar IGP VI gekombineer word met MPLS VI om IP roetering te optimeer. Dit word gedoen deur `of optimering van IGP roetering terwyl ’n paar MPLS tonnels in die netwerk gestel word, `of optimering van die bestuur van MPLS tonnels om toe te laat vir groei in die IGP verkeer `of die optimering van beide IGP en MPLS roetering in ’n hibriede IGP en MPLS situasie. Die fokus van hierdie tesis is op IGP VI gebruikmakend van heuristieke algoritmes wat ontleen word vanuit die berekeningsintelligensie navorsingsveld. Ons beskou vier klasse van algoritmes vir Maksimum Verbindingsgebruik (MVG) minimering. Dit sluit in genetiese algoritmes, geen-uitdrukkingsprogrammering, mierkoloniemaksimering and gesimuleerde temperoptimering. Ons gebruik hierdie algoritmes om ’n versameling optimale verbindingsgewigte te bereken om IGP VI te bereik in verskillende situasies, waar ’n versameling toetsnetwerke gebruik is wat Europa, VSA, Afrika en China verteenwoordig. Gebruikmakende van NS simulasie, vergelyk ons die werkverrigting van hierdie algoritmes op die toetsnetwerke, met verskillende verkeersprofiele.

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Hwang, Kuo-Ping. "Applying heuristic traffic assignment in natural disaster evacuation: a decision support system." Diss., Virginia Polytechnic Institute and State University, 1986. http://hdl.handle.net/10919/54455.

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The goal of this research is to develop a heuristic traffic assignment method to simulate the traffic flow of a transportation network at a real-time speed. The existing assignment methods are reviewed and a heuristic path-recording assignment method is proposed. Using the new heuristic assignment method, trips are loaded onto the network in a probabilistic approach for the first iteration; paths are recorded, and path impedance is computed as the basis for further assignment iteration. The real-time traffic assignment model developed with the new assignment method is called HEUPRAE. The difference in link traffic between this new assignment and Dial's multipath assignment ranges from 10 to 25 percent. Saving in computer time is about 55 percent. The proposed heuristic path-recording assignment is believed to be an efficient and reliable method. Successful development of this heuristic assignment method helps solve those transportation problems which need assignment results at a real-time speed, and for which the assignment process lasts a couple of hours. Evacuation planning and operation are well suited to the application of this real-time heuristic assignment method. Evacuation planning and operations are major activities in emergency management. Evacuation planning instructs people where to go, which route to take, and the time needed to accomplish an evacuation. Evacuation operations help the execution of an evacuation plan in response to the changing nature of a disaster. The Integrated Evacuation Decision Support System (IEDSS) is a computer system which employs the evacuation planning model, MASSVAC2, and the evacuation operation model, HEUPRAE, to deal with evacuations. The IEDSS uses computer graphics to prepare input and interpret output. It helps a decision maker analyze the evacuation system, review evacuation plans, and issue an evacuation order at a proper time. Users of the IEDSS can work on evacuation problems in a friendly interactive visual environment. The application of the IEDSS to the hurricane and flood problems for the city of Virginia Beach shows how IEDSS is practically implemented. It proves the usefulness of the IEDSS in coping with disasters.<br>Ph. D.

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Trinh, Viet. "Using voicexml to provide real-time traffic information." Honors in the Major Thesis, University of Central Florida, 2002. http://digital.library.ucf.edu/cdm/ref/collection/ETH/id/307.

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This item is only available in print in the UCF Libraries. If this is your Honors Thesis, you can help us make it available online for use by researchers around the world by following the instructions on the distribution consent form at http://library.ucf.edu/Systems/DigitalInitiatives/DigitalCollections/InternetDistributionConsentAgreementForm.pdf You may also contact the project coordinator, Kerri Bottorff, at kerri.bottorff@ucf.edu for more information.<br>Bachelors<br>Engineering<br>Computer Engineering

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8

Smith, Katie S. "A profile of HOV lane vehicle characteristics on I-85 prior to HOV-to-HOT conversion." Thesis, Georgia Institute of Technology, 2011. http://hdl.handle.net/1853/42923.

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The conversion of high-occupancy vehicle (HOV) lanes to high-occupancy toll (HOT) lanes is currently being implemented in metro Atlanta on a demonstration basis and is under consideration for more widespread adoption throughout the metro region. Further conversion of HOV lanes to HOT lanes is a major policy decision that depends on knowledge of the likely impacts, including the equity of the new HOT lane. Rather than estimating these impacts using modeling or surveys, this study collects revealed preference data in the form of observed vehicle license plate data and vehicle occupancy data from users of the HOV corridor. Building on a methodology created in Spring 2011, researchers created a new methodology for matching license plate data to vehicle occupancy data that required extensive post-processing of the data. The new methodology also presented an opportunity to take an in-depth look at errors in both occupancy and license plate data (in terms of data collection efforts, processing, and the vehicle registration database). Characteristics of individual vehicles were determined from vehicle registration records associated with the license plate data collected during AM and PM peak periods immediately prior to the HOV lanes conversion to HOT lanes. More than 70,000 individual vehicle license plates were collected for analysis, and over 3,500 records are matched to occupancy values. Analysis of these data have shown that government and commercial vehicle were more prevalent in the HOV lane, while hybrid and alternative fuel vehicles were much less common in either lane than expected. Vehicle occupancy data from the first four quarters of data collection were used to create the distribution of occupancy on the HOV and general purpose lane, and then the matched occupancy and license plate data were examined. A sensitivity analysis of the occupancy data established that the current use of uncertain occupancy values is acceptable and that bus and vanpool occupancy should be considered when determining the average occupancy of all vehicles on the HOV lane. Using a bootstrap analysis, vehicle values were compared to vehicle occupancy values and the results found that there is no correlation between vehicle value and vehicle occupancy. A conclusions section suggests possible impacts of the findings on policy decisions as Georgia considers expanding the HOT network. Further research using these data, and additional data that will be collected after the HOT lane opens, will include emissions modeling and a study of changes in vehicle characteristics associated with the HOT lane conversion.

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Kumar, Saurabh. "Real-Time Road Traffic Events Detection and Geo-Parsing." Thesis, Purdue University, 2018. http://pqdtopen.proquest.com/#viewpdf?dispub=10842958.

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<p> In the 21<sup>st</sup> century, there is an increasing number of vehicles on the road as well as a limited road infrastructure. These aspects culminate in daily challenges for the average commuter due to congestion and slow moving traffic. In the United States alone, it costs an average US driver $1200 every year in the form of fuel and time. Some positive steps, including (a) introduction of the push notification system and (b) deploying more law enforcement troops, have been taken for better traffic management. However, these methods have limitations and require extensive planning. Another method to deal with traffic problems is to track the congested area in a city using social media. Next, law enforcement resources can be re-routed to these areas on a real-time basis. </p><p> Given the ever-increasing number of smartphone devices, social media can be used as a source of information to track the traffic-related incidents. </p><p> Social media sites allow users to share their opinions and information. Platforms like Twitter, Facebook, and Instagram are very popular among users. These platforms enable users to share whatever they want in the form of text and images. Facebook users generate millions of posts in a minute. On these platforms, abundant data, including news, trends, events, opinions, product reviews, etc. are generated on a daily basis. </p><p> Worldwide, organizations are using social media for marketing purposes. This data can also be used to analyze the traffic-related events like congestion, construction work, slow-moving traffic etc. Thus the motivation behind this research is to use social media posts to extract information relevant to traffic, with effective and proactive traffic administration as the primary focus. I propose an intuitive two-step process to utilize Twitter users' posts to obtain for retrieving traffic-related information on a real-time basis. It uses a text classifier to filter out the data that contains only traffic information. This is followed by a Part-Of-Speech (POS) tagger to find the geolocation information. A prototype of the proposed system is implemented using distributed microservices architecture.</p><p>

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Glick, Travis Bradley. "Utilizing High-Resolution Archived Transit Data to Study Before-and-After Travel-Speed and Travel-Time Conditions." PDXScholar, 2017. https://pdxscholar.library.pdx.edu/open_access_etds/4065.

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Travel times, operating speeds, and service reliability influence costs and service attractiveness. This paper outlines an approach to quantify how these metrics change after a modification of roadway design or transit routes using archived transit data. The Tri-County Metropolitan Transportation District of Oregon (TriMet), Portland's public transportation provider, archives automatic vehicle location (AVL) data for all buses as part of their bus dispatch system (BDS). This research combines three types of AVL data (stop event, stop disturbance, and high-resolution) to create a detailed account of transit behavior; this probe data gives insights into the behavior of transit as well as general traffic. The methodology also includes an updated approach for confidence intervals estimates that more accurately represent of range of speed and travel time percentile estimates. This methodology is applied to three test cases using a month of AVL data collected before and after the implementation of each roadway change. The results of the test cases highlight the broad applicability for this approach to before-and-after studies.

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Più fonti

Libri sul tema "Traffic engineering – Data processing"

1

Computer image processing in traffic engineering. Taunton, Somerset, England: Research Studies Press, 1991.

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Young, W. Microcomputers in traffic engineering. Taunton, Somerset, England: Research Studies Press, 1989.

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Abawajy, Jemal H. Network and traffic engineering in emerging distributed computing applications. Hershey, PA: Information Science Reference, 2013.

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1951-, Bonsall P. W., and Young W. 1949-, eds. Understanding traffic systems: Data, analysis, and presentation. Aldershot: Ashgate, 2000.

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1951-, Bonsall P. W., and Young W. 1949-, eds. Understanding traffic systems: Data, analysis, and presentation. Aldershot: Avebury Technical, 1996.

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Taylor, M. A. P. Traffic analysis: New technology & new solutions. North Melbourne, Victoria, Australia: Hargreen Pub. Co., 1988.

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Blay, D. R. Evaluation of the FREQ7PE freeway traffic simulation program. Downsview, Ont: Research and Development Branch, Ontario Ministry of Transportation, 1988.

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C, Bazzan Ana L., and Klügl Franziska, eds. Handbook of research on multi-agent systems for traffic and transportation engineering. Hershey, PA: Information Science Reference, 2009.

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Heureka '90 (1990 Karlsruhe, Germany). Optimierung in Verkehr und Transport: Vortragsveranstaltung mit Vorstellung von Hard- und Software, Karlsruhe 5./6. April 1990 : Tagungsbericht. [Köln]: Die Forschungsgesellschaft, 1990.

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Gao su gong lu jiao tong yun xing zhuang tai fen xi fang fa ji ying yong. Nanjing Shi: Dong nan da xue chu ban she, 2012.

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Capitoli di libri sul tema "Traffic engineering – Data processing"

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Sanghavi, Jeet D., Alay M. Shah, Saurabh S. Rane, and V. Venkataramanan. "Smart Traffic Density Management System Using Image Processing." In Lecture Notes on Data Engineering and Communications Technologies, 301–12. Singapore: Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-10-8339-6_33.

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Willmott, S. C. "Design of A Flight and Radar Data Processing System for the Support of Air Traffic Control." In Software Engineering for Large Software Systems, 122–40. Dordrecht: Springer Netherlands, 1990. http://dx.doi.org/10.1007/978-94-009-0771-3_5.

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Tarefder, Rafiqul, and James Brogan. "A Review of Statewide Traffic Data Collection, Processing, Projection and Quality Control." In Traffic Management, 1–18. Hoboken, NJ, USA: John Wiley & Sons, Inc., 2016. http://dx.doi.org/10.1002/9781119307822.ch1.

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Molnár, P., and T. R. Collins. "Traffic Data Collection Using Image Processing Technology." In Traffic and Granular Flow ’99, 357–62. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59751-0_35.

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García-Dorado, José Luis, Felipe Mata, Javier Ramos, Pedro M. Santiago del Río, Victor Moreno, and Javier Aracil. "High-Performance Network Traffic Processing Systems Using Commodity Hardware." In Data Traffic Monitoring and Analysis, 3–27. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-36784-7_1.

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Furutani, Nobuaki, Jun Kitazono, Seiichi Ozawa, Tao Ban, Junji Nakazato, and Jumpei Shimamura. "Adaptive DDoS-Event Detection from Big Darknet Traffic Data." In Neural Information Processing, 376–83. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26561-2_45.

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Trinh, Thong Duc, Dinh Khanh Nguyen Diep, and Vinh Dinh Nguyen. "Robust Median-Ternary Pattern for Traffic Light Detection." In Artificial Intelligence in Data and Big Data Processing, 485–94. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-97610-1_38.

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Berns, Karsten, Alexander Köpper, and Bernd Schürmann. "Sensor Data Processing." In Lecture Notes in Electrical Engineering, 227–53. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65157-2_8.

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Godse, Jay. "Reverse-Engineering Complex Solutions." In Ruby Data Processing, 89–96. Berkeley, CA: Apress, 2018. http://dx.doi.org/10.1007/978-1-4842-3474-7_4.

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Awange, Joseph L. "Data Processing and Adjustment." In Environmental Science and Engineering, 91–107. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-540-88256-5_6.

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Atti di convegni sul tema "Traffic engineering – Data processing"

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Lu, B., L. Yang, and A. Qin. "Mobile Traffic Data Collection/Processing and Its Applications." In Second International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41039(345)627.

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Kriegel, Hans-Peter, Peer Kroger, Peter Kunath, Matthias Renz, and Tim Schmidt. "Efficient Query Processing in Large Traffic Networks." In 2008 IEEE 24th International Conference on Data Engineering (ICDE 2008). IEEE, 2008. http://dx.doi.org/10.1109/icde.2008.4497586.

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Jiang, Jia, Hong Li, and Rui Xiao. "Error Processing on the Real-Time Traffic Data." In 2010 International Conference on Intelligent System Design and Engineering Application (ISDEA). IEEE, 2010. http://dx.doi.org/10.1109/isdea.2010.127.

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Nejad, Emad Soltani, and Mohammad Reza Majma. "RMTE: Robust modular traffic engineering in software-defined data center networks." In 2017 International Artificial Intelligence and Data Processing Symposium (IDAP). IEEE, 2017. http://dx.doi.org/10.1109/idap.2017.8090216.

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Liu, Nan, Peng Peng, Zuzhi Shen, Haihang Han, and Mingrong Deng. "Optimization of Traffic Information Processing Based on Data Mining from GPS Historical Data." In Second International Conference on Transportation Engineering. Reston, VA: American Society of Civil Engineers, 2009. http://dx.doi.org/10.1061/41039(345)584.

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Blackman, Samuel S., M. T. Busch, S. W. Cantrell, and C. J. Musial. "Applications of signal and data processing technology to vehicular traffic monitoring." In Optical Engineering and Photonics in Aerospace Sensing, edited by Oliver E. Drummond. SPIE, 1993. http://dx.doi.org/10.1117/12.157791.

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Li, Jianping, and Han Chen. "Research on Abnormal Data Analysis and Data Processing Method Based on Network Traffic." In 2022 IEEE International Conference on Computation, Big-Data and Engineering (ICCBE). IEEE, 2022. http://dx.doi.org/10.1109/iccbe56101.2022.9888172.

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Yadav, Mukesh, Kasturi Ghadge, Nitya Shetty, Deepa Chanchlani, Priyanka Narwani, and Richard Joseph. "Smart Road Traffic Handler: Cause Identification and Resolution Using Image Processing." In 2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence). IEEE, 2019. http://dx.doi.org/10.1109/confluence.2019.8776938.

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Zhang, Ming, Shisheng Wang, Yu jing Cai, and Xiubin Xuan. "Intelligent processing system for equipment monitoring data of urban rail transit based on IOT perception." In 5th International Conference on Traffic Engineering and Transportation System (ICTETS 2021), edited by Yongkang Xing. SPIE, 2021. http://dx.doi.org/10.1117/12.2619774.

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Figueiras, Paulo, Ricardo Silva, André Ramos, Guilherme Guerreiro, Ruben Costa, and Ricardo Jardim-Goncalves. "Big Data Processing and Storage Framework for ITS: A Case Study on Dynamic Tolling." In ASME 2016 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/imece2016-68069.

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Abstract (sommario):

Urban and national road networks in many countries are severely congested, resulting in increased travel times, unexpected delays, greater travel costs, worsening air pollution and noise levels, and a greater number of traffic accidents. Expanding traffic network capacities by building more roads is both extremely costly and harmful to the environment. By far the best way to accommodate growing travel demand is to make more efficient use of existing networks. Portugal has a good but underused toll highway network that runs near to an urban/national road network that is free to use but congested. In choosing not to pay a toll, many Portuguese drivers are apparently accepting greater risk to their safety and longer travel times. As a result, the urban/national road network is used far more intensively than projections anticipated, which raises maintenance costs while increasing levels of risk and inconvenience. The main idea behind the work presented here, is to motivate a shift of traffic from the overused network to the underused network. To this end, a model for calculating variable toll fees needs to be developed. In order to support the model, there is the need to accurately predict the status of road networks for real-time, short and medium term horizons, by using machine learning algorithms. Such algorithms will be used to feed the dynamic toll pricing model, reflecting the present and future traffic situations on the network. Since traffic data quantity and quality are crucial to the prediction accuracy of road networks’ statuses, the real-time and predictive analytics methods will use a panoply of data sources. The approach presented here, is being developed under the scope of the H2020 OPTIMUM, a European R&D project on ITS.

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Rapporti di organizzazioni sul tema "Traffic engineering – Data processing"

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Saad, T., R. Gandhi, X. Liu, V. Beeram, and I. Bryskin. Common YANG Data Types for Traffic Engineering. RFC Editor, June 2020. http://dx.doi.org/10.17487/rfc8776.

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Liu, X., I. Bryskin, V. Beeram, T. Saad, H. Shah, and O. Gonzalez de Dios. YANG Data Model for Traffic Engineering (TE) Topologies. RFC Editor, August 2020. http://dx.doi.org/10.17487/rfc8795.

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Gao, J., G. Xie, and R. Papneja. Label Switched Path (LSP) Data Path Delay Metrics in Generalized MPLS and MPLS Traffic Engineering (MPLS-TE) Networks. Edited by W. Sun and G. Zhang. RFC Editor, November 2012. http://dx.doi.org/10.17487/rfc6777.

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Chien, Stanley, Lauren Christopher, Yaobin Chen, Mei Qiu, and Wei Lin. Integration of Lane-Specific Traffic Data Generated from Real-Time CCTV Videos into INDOT's Traffic Management System. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317400.

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The Indiana Department of Transportation (INDOT) uses about 600 digital cameras along populated Indiana highways in order to monitor highway traffic conditions. The videos from these cameras are currently observed by human operators looking for traffic conditions and incidents. However, it is time-consuming for the operators to scan through all video data from all the cameras in real-time. The main objective of this research was to develop an automatic and real-time system and implement the system at INDOT to monitor traffic conditions and detect incidents automatically. The Transportation and Autonomous Systems Institute (TASI) of the Purdue School of Engineering and Technology at Indiana University-Purdue University Indianapolis (IUPUI) and the INDOT Traffic Management Center have worked together to research and develop a system that monitors the traffic conditions based on the INDOT CCTV video feeds. The proposed system performs traffic flow estimation, incident detection, and the classification of vehicles involved in an incident. The goal was to develop a system and prepare for future implementation. The research team designed the new system, including the hardware and software components, the currently existing INDOT CCTV system, the database structure for traffic data extracted from the videos, and a user-friendly web-based server for identifying individual lanes on the highway and showing vehicle flowrates of each lane automatically. The preliminary prototype of some system components was implemented in the 2018–2019 JTRP projects, which provided the feasibility and structure of the automatic traffic status extraction from the video feeds. The 2019–2021 JTRP project focused on developing and improving many features’ functionality and computation speed to make the program run in real-time. The specific work in this 2021–2022 JTRP project is to improve the system further and implement it on INDOT’s premises. The system has the following features: vehicle-detection, road boundary detection, lane detection, vehicle count and flowrate detection, traffic condition detection, database development, web-based graphical user interface (GUI), and a hardware specification study. The research team has installed the system on one computer in INDOT for daily road traffic monitoring operations.

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Ringhand, Madlen, Maximilian Bäumler, Christian Siebke, Marcus Mai, and Felix Elrod. Report on validation of the stochastic traffic simulation (Part A). Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.242.

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This document is intended to give an overview of the human subject study in a driving simulator that was conducted by the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD) to provide the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD with the necessary input for the validation of a stochastic traffic simulation, especially for the parameterization, consolidation, and validation of driver behaviour models. VPSY planned, conducted, and analysed a driving simulator study. The main purpose of the study was to analyse driving behaviour and gaze data at intersections in urban areas. Based on relevant literature, a simulated driving environment was created, in which a sample of drivers passed a variety of intersections. Considering different driver states, driving tasks, and traffic situations, the collected data provide detailed information about human gaze and driving behaviour when approaching and crossing intersections. The collected data was transferred to LKT for the development of the stochastic traffic simulation.

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Bäumler, Maximilian, Madlen Ringhand, Christian Siebke, Marcus Mai, Felix Elrod, and Günther Prokop. Report on validation of the stochastic traffic simulation (Part B). Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.243.

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This document is intended to give an overview of the validation of the human subject study, conducted in the driving simulator of the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD), as well of the validation of the stochastic traffic simulation developed in the AutoDrive project by the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD. Furthermore, the evaluation process of a C-AEB (Cooperative-Automatic Emergency Brake) system is demonstrated. The main purpose was to compare the driving behaviour of the study participants and the driving behaviour of the agents in the traffic simulation with real world data. Based on relevant literature, a validation concept was designed and real world data was collected using drones and stationary cameras. By means of qualitative and quantitative analysis it could be shown, that the driving simulator study shows realistic driving behaviour in terms of mean speed. Moreover, the stochastic traffic simulation already reflects reality in terms of mean and maximum speed of the agents. Finally, the performed evaluation proofed the suitability of the developed stochastic simulation for the assessment process. Furthermore, it could be shown, that a C-AEB system improves the traffic safety for the chosen test-scenarios.

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Hall, Candice, and Robert Jensen. Utilizing data from the NOAA National Data Buoy Center. Engineer Research and Development Center (U.S.), March 2021. http://dx.doi.org/10.21079/11681/40059.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) guides users through the quality control (QC) and processing steps that are necessary when using archived U.S. National Oceanic and Atmospheric Administration (NOAA) National Data Buoy Center (NDBC) wave and meteorological data. This CHETN summarizes methodologies to geographically clean and QC NDBC measurement data for use by the U.S. Army Corps of Engineers (USACE) user community.

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Tarko, Andrew P., Mario A. Romero, Vamsi Krishna Bandaru, and Cristhian Lizarazo. TScan–Stationary LiDAR for Traffic and Safety Applications: Vehicle Interpretation and Tracking. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317402.

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To improve traffic performance and safety, the ability to measure traffic accurately and effectively, including motorists and other vulnerable road users, at road intersections is needed. A past study conducted by the Center for Road Safety has demonstrated that it is feasible to detect and track various types of road users using a LiDAR-based system called TScan. This project aimed to progress towards a real-world implementation of TScan by building two trailer-based prototypes with full end-user documentation. The previously developed detection and tracking algorithms have been modified and converted from the research code to its implementational version written in the C++ programming language. Two trailer-based TScan units have been built. The design of the prototype was iterated multiple times to account for component placement, ease of maintenance, etc. The expansion of the TScan system from a one single-sensor unit to multiple units with multiple LiDAR sensors necessitated transforming all the measurements into a common spatial and temporal reference frame. Engineering applications for performing traffic counts, analyzing speeds at intersections, and visualizing pedestrian presence data were developed. The limitations of the existing SSAM for traffic conflicts analysis with computer simulation prompted the research team to develop and implement their own traffic conflicts detection and analysis technique that is applicable to real-world data. Efficient use of the development system requires proper training of its end users. An INDOT-CRS collaborative process was developed and its execution planned to gradually transfer the two TScan prototypes to INDOT’s full control. This period will be also an opportunity for collecting feedback from the end user and making limited modifications to the system and documentation as needed.

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Li, Howell, Jijo K. Mathew, Woosung Kim, and Darcy M. Bullock. Using Crowdsourced Vehicle Braking Data to Identify Roadway Hazards. Purdue University, 2020. http://dx.doi.org/10.5703/1288284317272.

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Modern vehicles know more about the road conditions than transportation agencies. Enhanced vehicle data that provides information on “close calls” such as hard braking events or road conditions during winter such as wheel slips and traction control will be critical for improving safety and traffic operations. This research applied conflict analyses techniques to process approximately 1.5 million hard braking events that occurred in the state of Indiana over a period of one week in August 2019. The study looked at work zones, signalized intersections, interchanges and entry/exit ramps. Qualitative spatial frequency analysis of hard-braking events on the interstate demonstrated the ability to quickly identify temporary and long-term construction zones that warrant further investigation to improve geometry and advance warning signs. The study concludes by recommending the frequency of hard-braking events across different interstate routes to identify roadway locations that have abnormally high numbers of “close calls” for further engineering assessment.

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Kress, Marin, David Young, Katherine Chambers, and Brandan Scully. AIS data case study : quantifying connectivity for six Great Lakes port areas from 2015 through 2018. Engineer Research and Development Center (U.S.), May 2021. http://dx.doi.org/10.21079/11681/40720.

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This Coastal and Hydraulics Engineering Technical Note (CHETN) presents results from a preliminary examination of commercial vessel traffic connectivity between six major port areas on the Great Lakes using Automatic Identification System (AIS) data collected from 2015 to 2018. The six port areas included in this study are Calumet Harbor, IL and IN; Cleveland, OH; Detroit, MI; Duluth-Superior, MN and WI; Indiana Harbor, IN; and Two Harbors, MN. These six locations represent an important subset of the more than 100 federally authorized navigation projects in the Great Lakes maintained by the US Army Corps of Engineers (USACE). The results are presented in the context of USACE resilience-related policy initiatives as well as the larger topic of maritime system resilience.

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