Auswahl der wissenschaftlichen Literatur zum Thema „Road Traffic Data Security“

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Zeitschriftenartikel zum Thema "Road Traffic Data Security"

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Sankaranarayanan, Suresh, and Srijanee Mookherji. "SVM-Based Traffic Data Classification for Secured IoT-Based Road Signaling System." International Journal of Intelligent Information Technologies 15, no. 1 (2019): 22–50. http://dx.doi.org/10.4018/ijiit.2019010102.

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The traffic controlling systems at present are microcontroller-based, which is semi-automatic in nature where time is the only parameter that is considered. With the introduction of IoT in traffic signaling systems, research is being done considering density as a parameter for automating the traffic signaling system and regulate traffic dynamically. Security is a concern when sensitive data of great volume is being transmitted wirelessly. Security protocols that have been implemented for IoT networks can protect the system against attacks and are purely based on standard cryptosystem. They can
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Bąk, Iwona, and Beata Szczecińska. "Statistical analysis of road safety in Poland with application of taxonomic methods." Transportation Overview - Przeglad Komunikacyjny 2016, no. 1 (2016): 20–26. http://dx.doi.org/10.35117/a_eng_16_01_03.

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The road safety is an area of public security, which is a basic need of every human being. One of the sources of the threats are road traffic offenses related in violation of safety rules. The aim of the article is to analyze road safety throughout the country and in individual provinces. In the study were used spatial and time data included in e.g. in the Regional Bank Data in the years 2001-2014 and the Police research papers available on the Internet. The statistical analysis and application of the Hellwig's taxonomic measure of development allowed the characterization of road traffic offen
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Tong, Yifei. "Road Blockchain: A Blockchain-Based Intelligent Road Traffic Management System." Journal of Intelligence and Knowledge Engineering 2, no. 3 (2024): 162–68. https://doi.org/10.62517/jike.202404322.

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Blockchain technology is an innovative technology based on distributed ledgers, featuring core characteristics such as immutability and transparency, thanks to its unique encryption and consensus mechanisms. This technology has been applied in various industries including finance, supply chain, and healthcare, effectively enhancing operational efficiency and security in these fields[1]. For instance, in finance, blockchain technology has been used to create safer payment systems and transparent transaction records; in supply chain management, it facilitates transparent tracking of goods and st
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Yuan, Hong Wei, and Qi Wen Song. "The Design of Car Networking Based on WiMax and Zigbee Technology." Applied Mechanics and Materials 97-98 (September 2011): 971–75. http://dx.doi.org/10.4028/www.scientific.net/amm.97-98.971.

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The Car networking based on WiMax and Zigbee technology is mainly adopting WiMax network and Zigbee technology to build traffic information transmission system, using sensor carrying on the real-time data acquisition including the vehicle running and road condition data, with the chip storing date of vehicles or road, thus realizing the information communication between vehicles and vehicles, vehicle and roads, security control of vehicles. Test results show that the system can realize remote communication between vehicles and roads, traffic signs automatic identification, measuring the distan
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Espinoza-Mina, Marcos Antonio, and Alejandra Mercedes Colina-Vargas. "Characterization of traffic accidents for urban road safety." Revista Facultad de Ingeniería, Universidad de Antioquia, no. 112 (November 22, 2023): 60–77. https://doi.org/10.17533/udea.redin.20231134.

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Transit crashes are a serious social problem for any country, with a significant loss of human lives and economic consequences that are difficult to quantify. This article proposes a characterization of the transit crash rate for urban road safety using time series. A quantitative descriptive study was conducted, characterizing the variables of each crash extracted from the National Traffic Agency of Ecuador (NTA); the data were processed at a descriptive and predictive level for the city of Guayaquil. The first step was an exploration of the scientific interest of the topic with the processin
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Lin, Hua-Yi. "Secure cloud internet of vehicles based on blockchain and data transmission scheme of map/reduce." Computer Science and Information Systems, no. 00 (2022): 56. http://dx.doi.org/10.2298/csis220921056l.

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Over the past few years, because of the popularity of the Internet of vehicles and cloud computing, the exchange of group information between vehicles is no longer out of reach. Through WiFi/5G wireless communication protocol, vehicles can instantly deliver traffic conditions and accidents to the back end or group vehicles traveling together, which can reduce traffic congestion and accidents. In addition, vehicles transmit real-time road conditions to the cloud vehicle management center, which can also share real-time road conditions and improve the road efficiency for pedestrians and drivers.
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Hermani, Wahyuningsih Tri, Ary Setyawan, Syafi’i, and Evi Gravitiani. "DECREASED PERFORMANCE AT UNSIGNALED INTERSECTIONS AFFECTS THE CONSTRUCTION OF THE SOLO-YOGYA ROAD WITH THE LEAST SQUARE METHOD." Journal of Applied Engineering Science 21, no. 3 (2023): 963–71. http://dx.doi.org/10.5937/jaes0-45137.

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The construction of the Solo-Yogyakarta toll road is part of the National Strategic Project. At the development stage, toll road infrastructure needs to assess the impact of traffic, considering many security and safety disturbances. Road performance evaluation is essential to overcome traffic problems during toll road operations in the future. The purpose of the study was to calculate traffic performance at the unsignaled intersection affecting the construction of the Solo-Yogya toll road. The locations studied were four Solo-Yogya toll road access intersections using primary data on the cond
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Yang, Zhenzhen. "Driving Risk Identification of Truck Drivers Based on China’s Highway Toll Data." Sustainability 16, no. 5 (2024): 2122. http://dx.doi.org/10.3390/su16052122.

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Dangerous or illegal driving may disrupt the traffic safety management of public security organs, damage road infrastructure, lead to traffic accidents, or result in economic losses. This paper proposes a framework based on China’s highway toll data to identify dangerous or illegal driving risks, such as unfamiliarity with road conditions, overload, driving over the speed limit, fatigued driving, fake license plates, and other risks. The unfamiliarity with road conditions is identified with the frequency of driving routes. When the total weight of a vehicle and its cargo is greater than the up
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Sudjana, Sudjana. "PENYULUHAN HUKUM DALAM UPAYA PENINGKATAN KESADARAN HUKUM BERLALULINTAS MELALUI PEMAHAMAN TERHADAP ISI UNDANG-UNDANG NOMOR 22 TAHUN 2009 TENTANG LALU LINTAS DAN ANGKUTAN JALAN." JURNAL PENDIDIKAN ILMU SOSIAL 25, no. 2 (2017): 124. http://dx.doi.org/10.17509/jpis.v25i2.6186.

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This study discusses the public understanding of the contents of Law No. 22 of 2009 regarding Traffic and Road Transportation. This is important, considering traffic and road transportation has an important role to realize the security, prosperity, order traffic and road transportation to support economic development. Methods Research method used is a normative juridical approach, Specifications descriptive analytical research, conducted research stage through the study of literature to examine the primary legal materials, secondary law, and tertiary legal materials. Data collected through the
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Aminigbo, Leonard Michael Onyinyechi. "Geospatial Approach to Solving Traffic Congestion Problems In Mushin Local Government Area of Lagos State." International Journal of Information Systems and Informatics 3, no. 1 (2022): 52–66. http://dx.doi.org/10.47747/ijisi.v3i1.705.

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The variation in road conditions in relation to traffic congestion overtime enhances the need for proper development of a geospatial platform by comprehensively building and relating the attributes information of the entire road network with respect to various road segments. This is better executed through the concept of dynamic road segmentation. The aim of this study is to carry out geospatial data structure of dynamic road segmentation in Mushin local government area of Lagos State showing the road segment (spatial data) and its topological information.The selected roads within Mushin Local
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Dissertationen zum Thema "Road Traffic Data Security"

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Diallo, El-hacen. "Study and Design of Blockchain-based Decentralized Road Traffic Data Management in VANET (Vehicular Ad hoc NETworks)." Electronic Thesis or Diss., université Paris-Saclay, 2022. http://www.theses.fr/2022UPASG017.

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La prolifération des véhicules autonomes a imposé la nécessité d'une gestion plus sécurisée des données du trafic routier (c'est-à-dire les événements liés aux accidents, l'état de la circulation, le rapport d'attaque, etc.) dans les réseaux Ad hoc pour véhicules (VANET). Les systèmes centralisés traditionnels répondent à ce besoin en exploitant des serveurs distants éloignés des véhicules. Cette solution n’est pas optimale, car les données relatives au trafic routier doivent être distribuées et mises en cache de manière sécurisée à proximité des véhicules. Cela améliore la latence et réduit l
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Naji, Jamil Abdul-Rabb. "Road accident analysis in Yemen : the identification of shortcomings in road accident data, data adjustment, cost and development of road fatality model." Thesis, University of South Wales, 1996. https://pure.southwales.ac.uk/en/studentthesis/road-accident-analysis-in-yemen(8586c669-4709-4b2c-9d83-45003bc5d0bf).html.

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The true extent of the road accident problem in Yemen is questionable. Some agencies and citizens believe that the safety situation in Yemen is very critical while others disagree with this belief. Both sides however, agree that the road accident problem in Yemen is such that it requires considerable attention. Since Yemen has no history in road safety research and since there is no reliable road accident data in the country, making final judgements on the situation is difficult unless supported by adequate research. The aim of the present research is to provide a better understanding of the r
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Mollet, C. J. "The analysis of road traffic accident data in the implementation of road safety remedial programmes." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52483.

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Thesis (M.Ing.)--Stellenbosch University, 2001.<br>ENGLISH ABSTRACT: A road safety remedial programme has as an objective the improvement of road transportation safety by applying road safety engineering remedial measures to hazardous road network elements in a manner that will be economically efficient. Since accident data is the primary manifestation of poor safety levels it must be analysed in manner that will support the overall objective of economic efficiency. Three steps in the process of implementing a road safety remedial programme, that rely on the systematic analysis of accid
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Amado, Vanessa. "Knowledge discovery and data mining from freeway section traffic data." Diss., Columbia, Mo. : University of Missouri-Columbia, 2008. http://hdl.handle.net/10355/5591.

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Thesis (Ph. D.)--University of Missouri-Columbia, 2008.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on June 8, 2009) Vita. Includes bibliographical references.
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Perez, Katherine, Wendy Weijermars, Niels Bos, et al. "Implications of estimating road traffic serious injuries from hospital data." Elsevier, 2018. https://publish.fid-move.qucosa.de/id/qucosa%3A72269.

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To determine accurately the number of serious injuries at EU level and to compare serious injury rates between different countries it is essential to use a common definition. In January 2013, the High Level Group on Road Safety established the definition of serious injuries as patients with an injury level of MAIS3+(Maximum Abbreviated Injury Scale). Whatever the method used for estimating the number or serious injuries, at some point it is always necessary to use hospital records. The aim of this paper is to understand the implications for (1) in/exclusion criteria applied to case selection a
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Mao, Ruixue. "Road Traffic Density Estimation in Vehicular Network." Thesis, The University of Sydney, 2013. http://hdl.handle.net/2123/9467.

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In recent decades, vehicular networks or intelligent transportation systems are being increasingly investigated and used to provide solutions to next generation traffic systems. Road traffic density estimation provides important information for road planning, intelligent road routing, road traffic control, vehicular network traffic scheduling, routing and dissemination. The ever increasing number of vehicles equipped with wireless communication capabilities provide new means to estimate the road traffic density more accurately and in real time than traditionally used techniques. In this thesis
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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. Anoth
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Yaiaroon, Niphan. "Probabilistic modelling of extreme traffic load-effects based on WIM data." Thesis, The University of Sydney, 2009. https://hdl.handle.net/2123/28224.

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The primary aims of this thesis are to develop a realistic probabilistic model of extreme traffic load-effects (referred to as a Probabilistic Model), which could be used for a reliability—based assessment of the safety of existing bridges, and to develop a model that provides an efficient approximation (without significant computational difficulties) for the Probabilistic Model (referred to as an Approximate Model). The research focuses on the analysis of traffic load-effects estimated from Weigh-in-Motion data by calculating hypothetical load-effects that would be induced by each vehic
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Khatri, Chandra P. "Real-time road traffic information detection through social media." Thesis, Georgia Institute of Technology, 2015. http://hdl.handle.net/1853/53889.

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In current study, a mechanism to extract traffic related information such as congestion and incidents from textual data from the internet is proposed. The current source of data is Twitter, however, the same mechanism can be extended to any kind of text available on the internet. As the data being considered is extremely large in size automated models are developed to stream, download, and mine the data in real-time. Furthermore, if any tweet has traffic related information then the models should be able to infer and extract this data. To pursue this task, Artificial Intelligence, Machine Lear
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Boonsiripant, Saroch. "Speed profile variation as a surrogate measure of road safety based on GPS-equipped vehicle data." Diss., Atlanta, Ga. : Georgia Institute of Technology, 2009. http://hdl.handle.net/1853/28275.

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Thesis (M. S.)--Civil and Environmental Engineering, Georgia Institute of Technology, 2009.<br>Committee Chair: Hunter, Michael; Committee Member: Dixon, Karen; Committee Member: Guensler, Randall; Committee Member: Rodgers, Michael; Committee Member: Tsui, Kwok-Leung.
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Bücher zum Thema "Road Traffic Data Security"

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Petrie, D. D. Derivation of appropriate traffic & loading data, and parameters for road asset management. Transfund New Zealand, 2005.

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Golembiewski, Gary A. Road safety information analysis: A manual for local rural road owners. U.S. Dept. of Transportation, Federal Highway Administration, Office of Safety, 2011.

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Amoros, Emmanuelle. Reporting on serious road traffic casualties: Combining and using different data sources to improve understanding of non-fatal road traffic crashes. Edited by International Traffic Safety Data and Analysis Group and International Transport Forum. International Transport Forum, 2011.

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California. Division of Traffic Engineering., ed. Accident data on California state highways: (road miles, travel, accidents, accident rates). The Division, 1985.

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Fong, Peter K. W. An evaluative analysis of the Hong Kong Electronic Road Pricing System. University of Hong Kong, Centre of Urban Studies & Urban Planning, 1985.

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Zmud, Johanna. Compilation of public opinion data on tolls and road pricing. Transportation Research Board, 2008.

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Communications and Society Program (Aspen Institute) and Aspen Institute Conference on Telecommunications Policy (26th : 2011 : Aspen, Colo.), eds. Updating rules of the digital road: Privacy, security, intellectual property. The Aspen Institute, Communications and Society Program, Charles M. Firestone, executive director, 2012.

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H, Schneider William. Application of bluetooth technology to rural freeway speed data collection. Ohio Dept. of Transportation, Research & Development, 2012.

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International Conference on Road Transport Information and Control (11th 2002 Commonwealth Institute). Eleventh International Conference on Road Transport Information and Control: 19-21 March, 2002 ; venue, The Commonwealth Institute, London. Institution of Electrical Engineers, 2002.

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Organization, World Health, ed. Global status report on road safety 2013: Supporting a decade of action. World Health Organization, 2013.

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Buchteile zum Thema "Road Traffic Data Security"

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Nguyen, Binh Thanh, Pham Lu Quang Minh, Huynh Vu Minh Nguyet, Do Huu Phuoc, Pham Dinh Tai, and Huy Truong Dinh. "Intelligent Urban Transportation System to Control Road Traffic with Air Pollution Orientation." In Future Data and Security Engineering. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-91387-8_14.

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Mookherji, Srijanee, and Suresh Sankaranarayanan. "Traffic Data Classification for Security in IoT-Based Road Signaling System." In Soft Computing in Data Analytics. Springer Singapore, 2018. http://dx.doi.org/10.1007/978-981-13-0514-6_57.

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Gkotsis, Ilias, Aggelos Aggelis, Leonidas Perlepes, et al. "Supporting Maintenance Tasks and Upgrading Roadworks Through an Integrated Automated System." In Security Informatics and Law Enforcement. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-62083-6_15.

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AbstractAt a time of zero tolerance (zero accidents, zero operating restrictions, zero ice on our roads, etc.), it is increasingly necessary to control risks and to improve the knowledge of road operators with regard to the condition of structures in order to organize preventive and predictive maintenance that minimizes risks at an acceptable cost. Instrumentation, particularly in the context of preventive monitoring, is a valuable tool, as are risk analysis approaches. It allows, in this case, to better understand the behavior of structures, to know their condition, and thus to provide reliab
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Scholler, Rémy, Oumaïma Alaoui-Ismaïli, Jean-François Couchot, Eric Ballot, and Denis Renaud. "Observing Road Freight Traffic from Mobile Network Signalling Data While Respecting Privacy and Business Confidentiality." In Privacy and Identity Management. Between Data Protection and Security. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-99100-5_14.

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Kołodziej, Joanna, Cornelio Hopmann, Giovanni Coppa, Daniel Grzonka, and Adrian Widłak. "Intelligent Transportation Systems – Models, Challenges, Security Aspects." In Cybersecurity of Digital Service Chains. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-04036-8_3.

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AbstractAs cars and other transportation devices become increasingly interconnected, mobility takes on a new meaning, offering new opportunities. The integration of new communications technologies in modern vehicles has generated an enormous variety of data from various communications sources. Hence, there is a demand for intelligent transportation systems that can provide safe and reliable transportation while maintaining environmental conditions such as pollution, CO2 emission, and energy consumption. This chapter provides an overview of the Intelligent Transportation Systems (ITS) models. B
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Várhelyi, András. "Road Safety Inspection and Road Assessment Programme." In Traffic Safety Data. The Institution of Engineering and Technology, 2024. https://doi.org/10.1049/pbtr028e_ch11.

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Owsiński, Jan W., Jarosław Stańczak, Karol Opara, Sławomir Zadrożny, and Janusz Kacprzyk. "The Road Traffic Data." In Reverse Clustering. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-69359-6_4.

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Van den Berghe, Wouter, and Uta Meesmann. "The use of self-reported data in road safety research." In Traffic Safety Data. The Institution of Engineering and Technology, 2024. https://doi.org/10.1049/pbtr028e_ch6.

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MA, Xiaolei, Sen LUAN, and Xiaofei YU. "Traffic Data Management Technology in ITS." In Intelligent Road Transport Systems. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-5776-4_3.

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Mbarek, Abdelilah, Mouna Jiber, Ali Yahyaouy, and Abdelouahed Sabri. "Road-Traffic Data Collection: Handling Missing Data." In Explainable Artificial Intelligence for Intelligent Transportation Systems. CRC Press, 2023. http://dx.doi.org/10.1201/9781003324140-6.

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Konferenzberichte zum Thema "Road Traffic Data Security"

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Olug, Eren, Kiymet Kaya, Resul Tugay, and Sule Gunduz Oguducu. "IBB Traffic Graph Data: Benchmarking and Road Traffic Prediction Model." In 2024 IEEE 29th International Workshop on Computer Aided Modeling and Design of Communication Links and Networks (CAMAD). IEEE, 2024. https://doi.org/10.1109/camad62243.2024.10943048.

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Ran, Junhao Frank, Yifan Wu, Delaram Pirhayatifard, João Mattos, and Arlei Silva. "TrafficPulse: A Road-Sensor Assisted Traffic Tweet Misinformation Detection System." In 2025 IEEE Security and Privacy Workshops (SPW). IEEE, 2025. https://doi.org/10.1109/spw67851.2025.00044.

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Li, Jingyi, Shengping Dong, and Xinquan Zu. "Urban Road Network Traffic State Recognition Based on Road DNA Feature Sequence Matching." In 2025 8th International Conference on Artificial Intelligence and Big Data (ICAIBD). IEEE, 2025. https://doi.org/10.1109/icaibd64986.2025.11082058.

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S, Sivamurugan, Vedapriya N, Vijayashree K, and Nithya P. "Road Traffic Forecasting Using Air Pollution and Atmospheric Data." In 2024 International Conference on Power, Energy, Control and Transmission Systems (ICPECTS). IEEE, 2024. https://doi.org/10.1109/icpects62210.2024.10780058.

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Kumar, Srinivas Suresh, Yeswanth Babu, JS Guru Sabbarish, and A. Jasmine Gilda. "Image Detection for Criminal Investigation using Road Traffic Data." In 2025 2nd International Conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering (RMKMATE). IEEE, 2025. https://doi.org/10.1109/rmkmate64874.2025.11042558.

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R. C, Annwin Remilka, Devicharan M, and Sarojini Premalatha J. "Road Safety with Deep Learning Voice Based Traffic Sign." In 2025 International Conference on Data Science, Agents & Artificial Intelligence (ICDSAAI). IEEE, 2025. https://doi.org/10.1109/icdsaai65575.2025.11011743.

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El Faouzi, Nour-Eddin. "Data fusion in road traffic engineering: an overview." In Defense and Security, edited by Belur V. Dasarathy. SPIE, 2004. http://dx.doi.org/10.1117/12.541354.

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de Mouzon, Olivier, and Nour-Eddin El Faouzi. "Real-time data fusion of road traffic and ETC data for road network monitoring." In Defense and Security Symposium, edited by Belur V. Dasarathy. SPIE, 2007. http://dx.doi.org/10.1117/12.719446.

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Abdullah, Tariq, and Symon Nyalugwe. "A Data Mining Approach for Analysing Road Traffic Accidents." In 2019 2nd International Conference on Computer Applications & Information Security (ICCAIS). IEEE, 2019. http://dx.doi.org/10.1109/cais.2019.8769587.

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"Public Security Road Traffic Management Strategy Based on Big Data Application." In 2020 5th International Conference on Technologies in Manufacturing, Information and Computing. Francis Academic Press, 2020. http://dx.doi.org/10.25236/ictmic.2020.053.

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Berichte der Organisationen zum Thema "Road Traffic Data Security"

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Fedyk, D., and C. Hopps. A YANG Data Model for IP Traffic Flow Security. RFC Editor, 2023. http://dx.doi.org/10.17487/rfc9348.

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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
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Chien, Stanley, Yaobin Chen, Lauren Christopher, Mei Qiu, and Zhengming Ding. Road Condition Detection and Classification from Existing CCTV Feed. Purdue University, 2022. http://dx.doi.org/10.5703/1288284317364.

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The Indiana Department of Transportation (INDOT) has approximately 500 digital cameras along highways in populated areas of Indiana. These cameras are used to monitor traffic conditions around the clock, all year round. Currently, the videos from these cameras are observed one-by-one by human operators looking for traffic conditions and incidents. The main objective of this research was to develop an automatic, real-time system to monitor traffic conditions and detect incidents automatically. The Transportation and Autonomous Systems Institute (TASI) of the Purdue School of Engineering and Tec
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Liu, Hongrui, and Rahul Ramachandra Shetty. Analytical Models for Traffic Congestion and Accident Analysis. Mineta Transportation Institute, 2021. http://dx.doi.org/10.31979/mti.2021.2102.

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In the US, over 38,000 people die in road crashes each year, and 2.35 million are injured or disabled, according to the statistics report from the Association for Safe International Road Travel (ASIRT) in 2020. In addition, traffic congestion keeping Americans stuck on the road wastes millions of hours and billions of dollars each year. Using statistical techniques and machine learning algorithms, this research developed accurate predictive models for traffic congestion and road accidents to increase understanding of the complex causes of these challenging issues. The research used US Accident
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Sakhare, Rahul Suryakant, Jairaj Desai, Jijo K. Mathew, John McGregor, Mischa Kachler, and Darcy M. Bullock. Measuring and Visualizing Freeway Traffic Conditions: Using Connected Vehicle Data. Purdue University, 2024. http://dx.doi.org/10.5703/1288284317751.

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Historically, a network of roadside sensors and cameras have been used to monitor freeway conditions. Although these systems are effective, they are typically not operational in and around work zones. Furthermore, it is often not financially viable to deploy in-road sensors and cameras in rural areas. Connected vehicle trajectory data has emerged as a viable source of data and provides a unique opportunity for monitoring freeways. This monograph describes how these connected vehicles can be used to directly measure queue lengths and travel times and this description is summarized in a graphica
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Kumar, Kaushal, and Yupeng Wei. Attention-Based Data Analytic Models for Traffic Flow Predictions. Mineta Transportation Institute, 2023. http://dx.doi.org/10.31979/mti.2023.2211.

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Traffic congestion causes Americans to lose millions of hours and dollars each year. In fact, 1.9 billion gallons of fuel are wasted each year due to traffic congestion, and each hour stuck in traffic costs about $21 in wasted time and fuel. The traffic congestion can be caused by various factors, such as bottlenecks, traffic incidents, bad weather, work zones, poor traffic signal timing, and special events. One key step to addressing traffic congestion and identifying its root cause is an accurate prediction of traffic flow. Accurate traffic flow prediction is also important for the successfu
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Tarko, Andrew P., Qiming Guo, and Raul Pineda-Mendez. Using Emerging and Extraordinary Data Sources to Improve Traffic Safety. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317283.

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The current safety management program in Indiana uses a method based on aggregate crash data for conditions averaged over several-year periods with consideration of only major roadway features. This approach does not analyze the risk of crashes potentially affected by time-dependent conditions such as traffic control, operations, weather and their interaction with road geometry. With the rapid development of data collection techniques, time-dependent data have emerged, some of which have become available for safety management. This project investigated the feasibility of using emerging and exi
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Robinson, W. Full-scale evaluation of multi-axial geogrids in road applications. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/43549.

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The U.S. Army Engineer Research and Development Center (ERDC) constructed a full-scale unsurfaced test section to evaluate the performance of two prototype geogrids, referred to as NX950 and NX750, in road applications. The test section consisted of a 10-in.-thick crushed aggregate surface layer placed over a very weak 2 California Bearing Ratio (CBR) clay subgrade. Simulated truck traffic was applied using one of ERDC’s specially designed load carts outfitted with a single-axle dual wheel truck gear. Rutting performance and instrumentation response data were monitored at multiple traffic inte
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Mathew, Sonu, and Srinivas S. Pulugurtha. Effect of Weather Events on Travel Time Reliability and Crash Occurrence. Mineta Transportation Institute, 2022. http://dx.doi.org/10.31979/mti.2022.2035.

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The magnitude of the effect of adverse weather conditions on road operational performance varies with the type of weather condition and the road characteristics of the road links and adjacent links. Therefore, the relationship between weather and traffic is always a concern to traffic engineers and planners, and they have extensively explored ways to integrate weather information into transportation systems. Understanding the influence of weather on operational performance and safety helps traffic engineers and planners to proactively plan and manage transportation systems. The main objective
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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
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