Relevant bibliographies by topics / Urban traffic flow

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Urban traffic flow'

Author: Grafiati
Published: 5 June 2025
Last updated: 2 August 2025

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Journal articles on the topic "Urban traffic flow"

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Guseynov, Sharif E., and Alexander V. Berezhnoy. "MODELLING OF URBAN TRAFFIC FLOW." Environment. Technology. Resources. Proceedings of the International Scientific and Practical Conference 1 (June 15, 2017): 109. http://dx.doi.org/10.17770/etr2017vol1.2632.

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In this paper non-deterministic motion of urban traffic is studied under certain assumptions. Based on those assumptions discrete and continuous mathematical models are developed: continuous model is written as the Cauchy initial-value problem for the integro-differential equation, whence among other things it is obtained the Fokker-Planck equation. Besides, the sufficient condition ensuring the mathematical legitimacy of the developed continuous model is formulated.
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Dong, Yu Bo. "Discussion on Urban Road Traffic Congestion Algorithm for Automatically Determining." Advanced Materials Research 926-930 (May 2014): 3790–93. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3790.

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Compared with the expressway, most of the traffic flow in urban road network can be denoted as interrupted traffic flow. Based on the current employed equipment for traffic flow collection and traffic signal control in urban roads, different types of traffic flow in urban roads are analyzed with the traffic flow arrival/departure model in transportation engineering. Mathematical models complying with traffic flow changes are utilized to match the traffic flow in both entry and exit road blocks, thus, enabled the automatic detection of traffic incident. This algorithm provides a measurement for
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Chen, Da Shan. "Characteristic Parameters Identification of Macro Traffic Flow on Urban Expressway." Applied Mechanics and Materials 409-410 (September 2013): 1209–12. http://dx.doi.org/10.4028/www.scientific.net/amm.409-410.1209.

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The macroscopic traffic flow parameters characteristic is an important research content in traffic flow theory. Urban expressway plays an important role in the urban road network. It is gradually shifting from large-scale infrastructure-oriented to refinement of traffic management. With the growing of traffic demand and much more traffic congestion and accidents, integrated active traffic management should be involved in urban expressway management on the back ground of car-road coordination. As the backbone road network, traffic flow characteristic parameters have great value for the control
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Liu, Zeyu, and Gongping Yang. "Large-scale traffic flow simulation based on intelligent PSO." MATEC Web of Conferences 355 (2022): 02010. http://dx.doi.org/10.1051/matecconf/202235502010.

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With the rapid development of urban traffic, a large number of vehicles in cities not only bring convenience to people, but also bring a series of traffic problems, including traffic congestion and high traffic accident rates. Driving speed and waiting time of vehicles are two important factors of traffic problems. To simulate the real urban road traffic flow, a one-dimensional traffic flow grid model was proposed, which considered the nearest and next neighbour car at the same time, and connected the front and rear neighbour cars to optimize the traffic flow. The experiment results showed tha
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Zeng, Junwei, Yongsheng Qian, Bingbing Wang, Tingjuan Wang, and Xuting Wei. "The Impact of Traffic Crashes on Urban Network Traffic Flow." Sustainability 11, no. 14 (2019): 3956. http://dx.doi.org/10.3390/su11143956.

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This paper aims to investigate the impact of occasional traffic crashes on the urban traffic network flow. Toward this purpose, an extended model of coupled Nagel–Schreckenberg (NaSch) and Biham–Middleton–Levine (BML) models is presented. This extended model not only improves the initial conditions of the coupled models, but also gives the definition of traffic crashes and their spatial/time distribution. Further, we simulated the impact of the number of traffic crashes, their time distribution, and their spatial distribution on urban network traffic flow. This research contributes to the comp
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Yu, Yi, Hui Gong, and Xianglun Mo. "Analysis of Traffic Flow Equilibrium in Urban Road Network Based on Floating Vehicle Data." E3S Web of Conferences 261 (2021): 03026. http://dx.doi.org/10.1051/e3sconf/202126103026.

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Based on the floating vehicle data, this paper analyzes the equilibrium of urban road network traffic flow. This can guide traffic flow distribution and provide reliable basis for traffic control. This paper starts with the quantitative analysis of the traffic network equilibrium, on the basis of verifying the validity of the floating car data, divides the urban road network into regions, and constructs an analysis model of the traffic flow equilibrium of the urban road network. The urban road traffic distribution model is constructed in accordance with the number of road traffic segments. On
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Jiang, Jixiao, Anastasia Alexandrovna Feofilova, Anastasia Gennad’evna Shevtsova, and Victoria Vladimirovna Vasilyeva. "TRAFFIC FLOW PREDICTION BASED ON CONVOLUTIONAL NEURAL NETWORK MODEL." World of transport and technological machines 87, no. 4-1 (2024): 126–33. https://doi.org/10.33979/2073-7432-2024-4-1(87)-126-133.

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Traffic flow prediction mainly uses traffic flow data obtained by intelligent transportation systems to predict future traffic flows to better plan traffic. Because the traffic flow prediction model based on neural network can predict the traffic status of a single road section very well. Therefore, in view of the complex and uncertain characteristics of urban road traffic flow, this paper uses traffic flow short-term prediction theory and convolutional neural network (CNN) to analyze and predict urban road traffic flow.
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Liu, Xuelian, Huazhi Yuan, Jie Hu, and Xinlong Jiao. "Single-Point Adaptive Control Method for Urban Mixed Traffic Flow." Journal of Advanced Transportation 2020 (September 14, 2020): 1–7. http://dx.doi.org/10.1155/2020/8827824.

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In urban traffic, motor vehicles, nonmotor vehicles, pedestrians, and other traffic are mixed, which seriously affects the urban traffic efficiency. At the intersections of urban roads especially, the priority setting of various travel modes is crucial to improve the urban traffic efficiency. In the urban hybrid traffic system, the architecture and algorithm flowchart of the single-point adaptive control system for urban hybrid traffic flow are presented. The control effect of this method is verified by VISSIM software. The simulation results show that the traffic efficiency of the priority ob
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Qin, Jiayu, Gang Mei, and Lei Xiao. "Building the Traffic Flow Network with Taxi GPS Trajectories and Its Application to Identify Urban Congestion Areas for Traffic Planning." Sustainability 13, no. 1 (2020): 266. http://dx.doi.org/10.3390/su13010266.

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Traffic congestion is becoming a critical problem in urban traffic planning. Intelligent transportation systems can help expand the capacity of urban roads to alleviate traffic congestion. As a key concept in intelligent transportation systems, urban traffic networks, especially dynamic traffic networks, can serve as potential solutions for traffic congestion, based on the complex network theory. In this paper, we build a traffic flow network model to investigate traffic congestion problems through taxi GPS trajectories. Moreover, to verify the effectiveness of the traffic flow network, an act
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Abramova, Liudmyla, Valerii Shyrin, Hennadii Ptytsia, and Serhii Kapinus. "Dynamic control over traffic flow under urban traffic conditions." Eastern-European Journal of Enterprise Technologies 4, no. 3 (106) (2020): 34–43. http://dx.doi.org/10.15587/1729-4061.2020.210170.

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Dissertations / Theses on the topic "Urban traffic flow"

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Martin, Peter Terence. "Urban traffic movement prediction from automatic flow detection." Thesis, University of Nottingham, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334986.

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Mongeot, Helene. "Traffic incident modelling in mixed urban networks." Thesis, University of Southampton, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286751.

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Fong, Pui San. "Assessment of roundabout in urban road network :a case study of Macau." Thesis, University of Macau, 2017. http://umaclib3.umac.mo/record=b3691706.

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Cowburn, G. J. "Bayesian mixture modelling with application to road traffic flow." Thesis, University of Sunderland, 2003. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.269160.

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Stenberg, Josefin, and Sabina Syed. "Optimal Multi-Commodity Network Flow of Autonomous Vehicles in Urban Traffic." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-297491.

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The focus of this thesis was to find, visualize and analyze the optimal flow of autonomous vehicles in urban traffic with respect to fuel consumption using linear optimization. Two different formulations based on multi-commodity network flow were implemented which resulted in a static and a dynamic model of the traffic. The static model was applied to Kungsholmen, an urban district in central Stockholm, Sweden, while the dynamic model was considered on a small-scale. These models led to large linear programs which were solved by applying different algorithms to the problems in various software
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Zhang, Xiaoyan. "The dynamic behaviour of road traffic flow : stability or chaos?" Thesis, Middlesex University, 1995. http://eprints.mdx.ac.uk/10685/.

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The objective of this thesis is to investigate the dynamic behaviour of road traffic flow based on theoretical traffic models. Three traffic models are examined: the classical car-following model which describes the variations of speeds of cars and distances between the cars on a road link, the logit-based trip assignment model which describes the variations of traffic flows on road links in a road network, and the dynamic gravity trip distribution model which describes the variations of flows between O-D pairs in an O-D network. Some dynamic analyses have been made of the car-following model
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Camynta-Baezie, Gylbet. "Multi-class pseudo-dynamic traffic assignment in a signalized urban road network." Thesis, University of Newcastle Upon Tyne, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.313502.

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Valdes, Diaz Didier M. "Integrated information and traffic control strategies for congested urban freeway corridors /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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Kenworthy, J. R. "Driving cycles, urban form and transport energy /." Access via Murdoch University Digital Theses Project, 1986. http://wwwlib.murdoch.edu.au/adt/browse/view/adt-MU20051103.145933.

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Wang, Shi'an. "Stochastic Dynamic Model of Urban Traffic and Optimum Management of Its Flow and Congestion." Thesis, Université d'Ottawa / University of Ottawa, 2018. http://hdl.handle.net/10393/37254.

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There are a lot more roads being built periodically in most of the countries with the advancement of modern society. In order to promote the overall traffic flow quality within different cities, city traffic management has been playing a more and more essential role during the last few decades. In recent years, a significantly increasing attention has been paid to the management of traffic flow in major cities all over the world. In this thesis, we develop a stochastic dynamic model for urban traffic along with physical constraints characteristic of intersections equipped with traffic light
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Books on the topic "Urban traffic flow"

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National Research Council (U.S.). Transportation Research Board., ed. Traffic flow, capacity, roadway lighting, and urban traffic systems, 1990. Transportation Research Board, National Research Council, 1990.

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Fisk, C. S. Urban road traffic models for economic appraisal. Transit New Zealand, 1992.

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Board, Transportation Research, ed. Urban traffic systems and parking. Transportation Research Board, National Research Council, 1989.

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Schrank, David L. Estimates of urban roadway congestion, 1990. Texas Transportation Institute, Texas A&M University System, 1993.

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Schrank, David L. Estimates of urban roadway congestion, 1990. Office of Traffic Management and Intelligent Vehicle Highway Systems, Federal Highway Administration, 1993.

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Gartner, Nathan H. Urban Traffic Networks: Dynamic Flow Modeling and Control. Springer Berlin Heidelberg, 1995.

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H, Gartner Nathan, Improta Gennaro 1942-, and International Seminar on Urban Traffic Networks (2nd : 1992 : Capri, Italy), eds. Urban traffic networks: Dynamic flow modeling and control. Springer-Verlag, 1995.

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Hanks, James W. Roadway congestion in major urban areas, 1982 to 1987. Texas Transportation Institute, the Texas A&M University System, 1989.

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Arnold, E. D. Congestion on Virginia's urban highways. Virginia Transportation Research Council, in cooperation with the U.S. Dept. of Transportation, Federal Highway Administration, 1988.

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Schrank, David L. Trends in urban roadway congestion--1982 to 1991. Texas Transportation Institute, Texas A & M University System, 1994.

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Book chapters on the topic "Urban traffic flow"

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Fukui, M., T. Yosida, and H. Oikawa. "A Cellular Automaton Model for Dynamic Route Choice Behavior in Urban Roads." In Traffic and Granular Flow’01. Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-10583-2_30.

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Keyvan-Ekbatani, Mehdi, Xueyu Gao, Vikash V. Gayah, and Victor L. Knoop. "Examining Perimeter Gating Control of Urban Traffic Networks with Locally Adaptive Traffic Signals." In Traffic and Granular Flow '15. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-33482-0_73.

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McDonald, John F., Edmond L. d’Ouville, and Louie Nan Liu. "An Engineering Model of Traffic Flow." In Economics of Urban Highway Congestion and Pricing. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5231-4_2.

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Sonis, M. "Catastrophe Effects and Optimal Extensions of Transportation Flows in the Developing Urban System: A Review." In Traffic and Granular Flow ’99. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59751-0_3.

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Pavlyuk, Dmitry. "Spatiotemporal Forecasting of Urban Traffic Flow Volatility." In Lecture Notes in Networks and Systems. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-68476-1_6.

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Haag, G. "An Integrated Model of Transport and Urban Evolution (ITEM)- Traffic and City Development in Emergent Nations." In Traffic and Granular Flow ’99. Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-642-59751-0_26.

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McDonald, John F., Edmond L. d’Ouville, and Louie Nan Liu. "An Empirical Model of Highway Traffic Flow." In Economics of Urban Highway Congestion and Pricing. Springer US, 1999. http://dx.doi.org/10.1007/978-1-4615-5231-4_4.

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Brilon, W., and N. Wu. "Evaluation of Cellular Automata for Traffic Flow Simulation on Freeway and Urban Streets." In Traffic and Mobility. Springer Berlin Heidelberg, 1999. http://dx.doi.org/10.1007/978-3-642-60236-8_11.

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Hoch, Thomas, and Theodorich Kopetzky. "Energy-Efficient Internet of Things Solution for Traffic Monitoring." In Energy-Efficient and Semi-automated Truck Platooning. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-88682-0_10.

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AbstractRecent progress in video-based vehicle sensors allows for a detailed observation of road users on intersections in urban areas. By combining the measured real-life traffic situation with thorough traffic simulations, a cooperative system design for the dynamic management of traffic flow including vehicle platoons is possible. In this chapter, we describe our video-based traffic flow estimation system that we installed at a three-way intersection in the small city of Hallein, Austria. We show that the installed system is able to collect comprehensive information about the traffic situat
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Hermanns, Gerhard, Igor N. Kulkov, Peter Hemmerle, et al. "Simulations of Synchronized Flow in TomTom Vehicle Data in Urban Traffic with the Kerner-Klenov Model in the Framework of the Three-Phase Traffic Theory." In Traffic and Granular Flow '13. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-10629-8_63.

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Conference papers on the topic "Urban traffic flow"

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Sofronova, Elena, and Askhat Diveev. "Control Synthesis Problem of Traffic Flow in Urban Network." In 2024 10th International Conference on Control, Decision and Information Technologies (CoDIT). IEEE, 2024. http://dx.doi.org/10.1109/codit62066.2024.10708292.

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Bhosale, Ashwini, Arshiya Shaikh, Arpita Kamble, Prema Khatri, Yash Kishor Patil, and Nilesh B. Korade. "AI Based Traffic Flow Prediction for Smart Urban Mobility." In 2024 International Conference on Artificial Intelligence and Quantum Computation-Based Sensor Application (ICAIQSA). IEEE, 2024. https://doi.org/10.1109/icaiqsa64000.2024.10882298.

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Guo, Rongge, Francesco Percassi, and Mauro Vallati. "Optimising Traffic Flow Through Synchronised Signal Configurations Along Urban Corridors." In 2024 IEEE 27th International Conference on Intelligent Transportation Systems (ITSC). IEEE, 2024. https://doi.org/10.1109/itsc58415.2024.10920265.

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Karandana, K. L. Y. S., D. D. A. Arthanayake, and M. W. P. Maduranga. "Improved Grading Recurrent Unit Model for Urban Traffic Flow Prediction." In 2025 5th International Conference on Advanced Research in Computing (ICARC). IEEE, 2025. https://doi.org/10.1109/icarc64760.2025.10963234.

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Malcontenti-Wilson, Adam, Hai L. Vu, Peter Cadusch, Philip Branch, Hans van Lint, and Serge Hoogendoorn. "Exploring urban traffic flow dynamics." In 2013 16th International IEEE Conference on Intelligent Transportation Systems - (ITSC 2013). IEEE, 2013. http://dx.doi.org/10.1109/itsc.2013.6728207.

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Reinthaler, M., and J. Zajicek. "Integration of traffic flow relations in a simulation environment." In URBAN TRANSPORT 2009. WIT Press, 2009. http://dx.doi.org/10.2495/ut090121.

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SAHA, ARPITA, SATISH CHANDRA, and INDRAJIT GHOSH. "SATURATION FLOW ESTIMATION AT SIGNALIZED INTERSECTIONS UNDER MIXED TRAFFIC CONDITIONS." In URBAN TRANSPORT 2017. WIT Press, 2017. http://dx.doi.org/10.2495/ut170331.

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Guo, Xiaoping, and John Black. "Traffic Flow Causing Severance on Urban Street." In Second International Conference on Transportation and Traffic Studies (ICTTS ). American Society of Civil Engineers, 2000. http://dx.doi.org/10.1061/40503(277)97.

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Jun, Gong, Qi Li, Liu Mingyue, and Chen Xiuyang. "Forecasting urban traffic flow by SVR." In 2013 25th Chinese Control and Decision Conference (CCDC). IEEE, 2013. http://dx.doi.org/10.1109/ccdc.2013.6561066.

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GILBERT, D., L. MOORE, and S. SIMPSON. "NOISE AND URBAN TRAFFIC (INTERRUPTED FLOW)." In Spring Conference 1980. Institute of Acoustics, 2025. https://doi.org/10.25144/24914.

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Reports on the topic "Urban traffic flow"

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Liu, Tairan. Addressing Urban Traffic Congestion: A Deep Reinforcement Learning-Based Approach. Mineta Transportation Institute, 2025. https://doi.org/10.31979/mti.2025.2322.

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In an innovative venture, the research team embarked on a mission to redefine urban traffic flow by introducing an automated way to manage traffic light timings. This project integrates two critical technologies, Deep Q-Networks (DQN) and Auto-encoders, into reinforcement learning, with the goal of making traffic smoother and reducing the all-too-common road congestion in simulated city environments. Deep Q-Networks (DQN) are a form of reinforcement learning algorithms that learns the best actions to take in various situations through trial and error. Auto-encoders, on the other hand, are tool
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Siebke, Christian, Maximilian Bäumler, Madlen Ringhand, Marcus Mai, Felix Elrod, and Günther Prokop. Report on integration of the stochastic traffic simulation. Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.246.

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As part of the AutoDrive project, the OpenPASS framework is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. This framework was adapted and further developed. The deliverable D5.13 deals with the construction of the stochastic traffic simulation. At this point of the process, the theoretical design aspects of D4.20 are implemented. D5.13 explains the operating principles of the different modules. This includes the foundations, boundary conditions, and mathematical theory of the traffic simulation.
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Yaseen, Lama, Nourah Al-Hosain, Ibrahem Shatnawi, and Abdelrahman Muhsen. Impact of Urban Traffic on Fuel Consumption Leveraging IoT Data: Case Study of Riyadh City. King Abdullah Petroleum Studies and Research Center, 2024. https://doi.org/10.30573/ks--2024-dp72.

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This study explores the rising trend of traffic congestion in Riyadh and its impact on fuel consumption for passenger cars amid the challenges of rapid urbanization and increasing vehicle use. By utilizing real-time floating car data (FCD) collected by vehicles equipped with Global Positioning System (GPS) technology and communication systems, this study illustrates the potential of the Internet of Things (IoT) and smart city technologies in developing intelligent transportation systems and improving urban mobility management. A spatial analysis of the traffic flow dynamics in Riyadh, focusing
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Siebke, Christian, Maximilian Bäumler, Madlen Ringhand, Marcus Mai, Felix Elrod, and Günther Prokop. Report on design of modules for the stochastic traffic simulation. Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.245.

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As part of the AutoDrive project, OpenPASS is used to develop a cognitive-stochastic traffic flow simulation for urban intersection scenarios described in deliverable D1.14. The deliverable D4.20 is about the design of the modules for the stochastic traffic simulation. This initially includes an examination of the existing traffic simulations described in chapter 2. Subsequently, the underlying tasks of the driver when crossing an intersection are explained. The main part contains the design of the cognitive structure of the road user (chapter 4.2) and the development of the cognitive behaviou
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Siebke, Christian, Maximilian Bäumler, Madlen Ringhand, Marcus Mai, Mohamed Nadar Ramadan, and Günther Prokop. Report on layout of the traffic simulation and trial design of the evaluation. Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.244.

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Within the AutoDrive project, openPASS is used to develop a cognitive stochastic traffic flow simulation for urban intersections and highway scenarios, which are described in deliverable D1.14. The deliverable D2.16 includes the customizations of the framework openPASS that are required to provide a basis for the development and implementation of the driver behavior model and the evaluated safety function. The trial design for the evaluation of the safety functions is described. Furthermore, the design of the driver behavior study is introduced to parameterize and validate the underlying drive
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