Relevant bibliographies by topics / Traffic jams

Contents

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

Academic literature on the topic 'Traffic jams'

Author: Grafiati
Published: 4 June 2021
Last updated: 2 February 2022

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Journal articles on the topic "Traffic jams"

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Jones, Rachel. "Axonal traffic jams." Nature Reviews Neuroscience 4, no. 11 (November 2003): 856–57. http://dx.doi.org/10.1038/nrn1268.

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Nagel, Kai, and Maya Paczuski. "Emergent traffic jams." Physical Review E 51, no. 4 (April 1, 1995): 2909–18. http://dx.doi.org/10.1103/physreve.51.2909.

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C, Keerthika, Narahari Greeshma, Priya Vyshnavi, Vyshnavi Kumar Reddy, K. Indhira, and V. M. Chandrasekaran. "Mathematical Model for Traffic Flow." International Journal of Engineering & Technology 7, no. 4.10 (October 2, 2018): 940. http://dx.doi.org/10.14419/ijet.v7i4.10.26631.

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Every year countless hours are lost in traffic jams. When the density of traffic is sufficiently high small disturbances in vehicle’s accelerations can cause phantom traffic jams. We can relate the traffic flow to mathematics and physics like that of liquids and gases. This paper presents mathematical model for phantom jams and Gauss Jordan elimination for traffic flow.
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Gupta, Himadri Shikhar, and Ramakrishna Ramaswamy. "Backbones of traffic jams." Journal of Physics A: Mathematical and General 29, no. 21 (November 7, 1996): L547—L553. http://dx.doi.org/10.1088/0305-4470/29/21/003.

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Conway, Leslie, Derek Wood, Andrew M. O' Neill, Kristopher E. Daly, Erkan Tüzel, and Jennifer Ross. "Microtubule Motor Traffic Jams." Biophysical Journal 102, no. 3 (January 2012): 368a. http://dx.doi.org/10.1016/j.bpj.2011.11.2011.

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Li, Shu Bin, Yong Lin, Hua Ling Ren, and Jian Cheng Long. "Research on Control Strategies and Optimal Signal Timing for Traffic Congestion Based on Prediction." Applied Mechanics and Materials 40-41 (November 2010): 858–65. http://dx.doi.org/10.4028/www.scientific.net/amm.40-41.858.

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Designing effective control strategies to traffic jams is an important measure to solve the problem of traffic jams in urban traffic network. Most of the green ratio models clear off crowded traffic flow synchronously at each approach of signal intersection in oversaturated traffic, but ignore the difference of traffic flows in different traffic state, and lead to the queue becoming longer and longer at oversaturated signal intersection. In this paper, the cell transmission model is applied to the propagation of traffic jams, the formation and dissipation of traffic jams in urban traffic network. A new method for predicting the traffic states is proposed, and the future traffic states can be achieved, according to the spatial structure of traffic jam propagation. We use an idea of traffic priority as an management measure to design the optimal green ratio in advance, and the improved green ratio model can realize the goal of preventing traffic congestion and clearing off traffic blockage quickly. Simulation results show that the proposed strategies with appropriate application can effectively control jam dissipation and prevent traffic congestion formation.
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Melville, David B., and Ela W. Knapik. "Traffic jams in fish bones." Cell Adhesion & Migration 5, no. 2 (March 2011): 114–18. http://dx.doi.org/10.4161/cam.5.2.14377.

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Li, Tong. "Nonlinear dynamics of traffic jams." Physica D: Nonlinear Phenomena 207, no. 1-2 (July 2005): 41–51. http://dx.doi.org/10.1016/j.physd.2005.05.011.

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Orosz, Gábor, R. Eddie Wilson, and Gábor Stépán. "Traffic jams: dynamics and control." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 368, no. 1928 (October 13, 2010): 4455–79. http://dx.doi.org/10.1098/rsta.2010.0205.

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This introductory paper reviews the current state-of-the-art scientific methods used for modelling, analysing and controlling the dynamics of vehicular traffic. Possible mechanisms underlying traffic jam formation and propagation are presented from a dynamical viewpoint. Stable and unstable motions are described that may give the skeleton of traffic dynamics, and the effects of driver behaviour are emphasized in determining the emergent state in a vehicular system. At appropriate points, references are provided to the papers published in the corresponding Theme Issue.
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Bons, Paul D., Albrecht Baur, Marlina A. Elburg, Matthias J. Lindhuber, Michael A. W. Marks, Alvar Soesoo, Boudewijn P. van Milligen, and Nicolas P. Walte. "Layered intrusions and traffic jams." Geology 43, no. 1 (January 2015): 71–74. http://dx.doi.org/10.1130/g36276.1.

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Dissertations / Theses on the topic "Traffic jams"

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Barlović, Robert. "Traffic jams cluster formation in low-dimensional cellular automata models for highway and city traffic /." [S.l. : s.n.], 2003. http://deposit.ddb.de/cgi-bin/dokserv?idn=969248830.

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Barlovic, Robert. "Traffic Jams : Cluster Formation in Low-Dimensional Cellular Automata Models for Highway and City Traffic." Gerhard-Mercator-Universitaet Duisburg, 2003. http://www.ub.uni-duisburg.de/ETD-db/theses/available/duett-10312003-150115/.

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Cellular automata (CA) models are quite popular in the field of traffic flow. They allow an effective implementation of real-time traffic computer-simulations. Therefore, various approaches based on CA models have been suggested in recent years. The first part of this thesis focuses on the so-called VDR (velocity-dependent randomization) model which is a modified version of the well known Nagel-Schreckenberg (NaSch) CA model. This choice is motivated by the fact that wide phase separated jams occur in the model. On the basis of random walk theory an analytical approach to the dynamics of these separated jam clusters is given. The predictions are in good agreement with the results of computer simulations and provide a deeper insight into the dynamics of wide jams which seem to be generic for CA approaches and are therefore of special interest. Furthermore, the impact of a localized defect in a periodic system is analyzed in the VDR model. It turns out that depending on the magnitude of the defect stop-and-go traffic can occur which can not be found in the VDR model without lattice defects. Finally, the VDR model is studied with open boundaries. The phase diagrams, obtained by Monte-Carlo simulations, reveal two jam phases with a stripped microscopic structure and for finite systems the existence of a new high-flow phase is shown. The second part of this thesis concentrates on CA models for city traffic with the focus on the Chowdhury-Schadschneider (ChSch) model. In the context of jam clusters the model reveals interesting features since two factors exert influence on the jamming behavior. On the one hand, jams are induced at crossings due to the traffic lights, i.e., cars are forced to stop at a ``red light', and, on the other hand, the dynamics of such induced jams is governed by the NaSch model rules. One part of the investigations covers global (fixed) traffic light strategies. These are found to lead to strong oscillations in the global flow except for the case of randomly switching lights. Furthermore, the impact of adaptive (local) traffic light control is analyzed. It is found that the autonomous strategies can nearly match the global optimum of the ChSch model. In order to provide a more realistic vehicle distribution, the ChSch model is enhanced by a stochastic turning of vehicles and by inhomogeneous densities. Here, the autonomous strategies can outperform the global ones in some cases.
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DeStefanis, Anthony Roland. "Trains, Trucks, and Traffic Jams: The Rise of Automotive Transportation, 1880-1956." W&M ScholarWorks, 1996. https://scholarworks.wm.edu/etd/1539626070.

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Roberg-Orenstein, Penina. "The development and control of traffic jams caused by incidents in rectangular grid networks." Thesis, Middlesex University, 1997. http://eprints.mdx.ac.uk/6564/.

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Urban traffic congestion is becoming a central issue in transport planning. If the present growth in car ownership and use continues, traffic jams are likely to increase in frequency and extent, particularly within the central areas of major cities. Whilst it is important to study the impact of congestion in the field, there is an urgent need for a fundamental understanding of the causes of congestion and the way in which it propagates. But, although a number of control schemes for controlling traffic congestion exist, no comprehensive rationale for an effective dispersal strategy has been developed. This research is mainly concerned with the properties of incident-induced traffic jams on rectangular grid networks, and possible measures for preventing and controlling them. The research investigates the underlying structure of such jams using a combination of theoretical and simulation models developed for this purpose. Using these models, gridlock is identified as a crucial stage in the evolution of traffic jams. However, most conventional traffic management measures aim to increase capacity and hence postpone the onset of gridlock and are unsuitable when gridlock has already set in. This thesis develops several alternative strategies for protecting networks from gridlock and dissipating traffic jams once they have formed. The treatment focuses on the installation of bans at specific network locations. The bans come in two forms: turn or ahead. Turn bans are imposed on selected links to break gridlock cycles at the nucleus of the traffic jam. By contrast, ahead bans are implemented around the traffic jam envelope to reduce input into critical sections of the road. The control strategies are tested extensively using the simulation model and as a result, some general control principles have emerged. These are not intended to be immediately applicable to real networks since they incorporate some simplifying assumptions. However, they point to certain characteristics of traffic jam growth and dispersal which would not be accessible in any other way.
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Zanule, Paul Gudoi. "Road Management System and Road Safety in Uganda." ScholarWorks, 2015. https://scholarworks.waldenu.edu/dissertations/368.

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Traffic collisions cost Uganda millions of dollars each year. The purpose of this descriptive case study was to describe the strategies and processes needed to implement a road management system. Such a system would significantly reduce the fatalities and accidents in Uganda, improve the transportation within Kampala's business district, and increase business profitability. Three conceptual theories framed the research study: management theory, strategic management theory, and criminology theory. Using a snowball sampling strategy, data were collected from open-ended interviews, questionnaires, observations, and archived documents from 20 administrative participants in the government and organizational leaders involved in the transport operations and transport services in the Kampala business district in Uganda. Data were analyzed using 3 phases: (a) interpretational analysis, coding, and grouping segments; (b) structural analysis, consistency, and quality; and (c) reflective analysis, consequences, what, when, where, and how. Five themes or action requirements emerged from the data analysis: to improve transport operations and transport services profitability, reduce traffic jams and fatalities, provide sufficient driving training, maintain road infrastructure, and maintain traffic law enforcement. The findings and recommendations from this study may improve the profitability of businesses, reduce the traffic jams and fatalities, and improve the gross domestic product of Uganda, thereby contributing to positive social change.
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Hoppe, André. "Staus auf Deutschen Bundesautobahnen: Quantifizierung von Verlustzeiten anhand der Analyse historischer Staudaten." Master's thesis, Saechsische Landesbibliothek- Staats- und Universitaetsbibliothek Dresden, 2017. http://nbn-resolving.de/urn:nbn:de:bsz:14-qucosa-222916.

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In dieser Arbeit wird eine Methode vorgestellt, die erstmalig die durch Staus verursachten Verzögerungszeiten auf Bundesautobahnen mithilfe von Annahmen aus der Verkehrsflussdynamik zu schätzen versucht. Dies geschieht anhand einer GPS-gestützten Vollerhebung aller Staus aus den Jahren 2015 und teils auch 2016, welche vom Navigationsdienstleister TomTom zur Verfügung gestellt wurden. Es konnte gezeigt werden, dass für das Jahr 2015 rund 190 Mio. Fahrzeug-Stunden (Anzahl betroffener Fahrzeuge × Staustunden) anfielen, was für die betroffenen Autofahrer einen monetären Wert von ca. vier Milliarden Euro ausmachte. Es wurden zudem Engpässe anhand eines Rankings erstellt, womit dauerhafte Schwerpunkte auf Autobahnen aufgedeckt wurden. Unter einer konkret definierten räumlichen, zeitlichen und sachlichen Abgrenzungen kann diese Methodik sowohl für die Forschung als auch für die Weiterentwicklung von Navigationsdiensten dienen
The estimation of time losses caused by traffic congestions have not previously been assessed by using assumptions of traffic flow dynamics. With a GPS-supported full survey of all jams from the year 2015 and parts of 2016 this master thesis tries to quantify the additional (congested) travel time on German Motorways. The analysis has shown that all jams reported on German highways produced time losses over 190 million vehicle-hours (amount of involved vehicles × congestion hours), which equals a monetary value of four billion euros for the involved drivers. Furthermore the ranking of the respective bottlenecks has been developed over the year and main congestion hotspots on motorways have been revealed. By using a precisely defined local, temporal and objective delimitation, this method could be used for further research and developments of navigation services as well
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Foss, Susan J. "Modeling the Aggregation of Interacting Neurofilaments in the Axon." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1431078489.

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Klumpp, Stefan. "Movements of molecular motors : diffusion and directed walks." Phd thesis, [S.l. : s.n.], 2003. http://pub.ub.uni-potsdam.de/2003/0020/klumpp.pdf.

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Li, Michelle Ai-Ling. "A molecular and phenotypic analysis of traffic jam, a key regulator of gonad morphogenesis." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2001. http://www.collectionscanada.ca/obj/s4/f2/dsk3/ftp04/MQ58897.pdf.

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Grassi, Nicolo'. "Transizione a stati congestionati in modelli di traffico." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2015. http://amslaurea.unibo.it/8948/.

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La congestione del traffico è un fenomeno molto familiare, con il quale si ha a che fare nelle più svariate occasioni. Dal punto di vista fisico, il flusso del traffico rappresenta un sistema di particelle interagenti (i ve- icoli) in condizione di non equilibrio. L’effetto complessivo di un sistema composto da molte particelle interagenti è la creazione di una instabil- ità, osservata empiricamente, nello stato di free flow (scorrimento libero), causata dall’aumentare delle fluttuazioni. In questi casi di parla di phan- tom traffic jam, ovvero una congestione che ha origine senza cause appar- enti, come incidenti o lavori in corso. Sarà dimostrato come la condizione di stop & go si verifichi spontaneamente se la densità media dei veicoli eccede un certo valore critico. L’importanza di poter predire una congestione stradale non è un problema puramente matematico, ma ha risvolti socio-economici non indifferenti. Infatti, le caratteristiche della mobilità e dei sistemi di trasporto sono strettamente legate alla struttura della comunità e alla qualità della vita. Con il seguente studio si cercherà di trovare un osservabile facilmente calcolabile, che potrebbe essere un predittore della formazione di uno stato congestionato con un intervallo di tempo sufficientemente adeguato. A tal fine sono state prese in considerazione misure relative alle condizioni del traffico su strade provinciali dell’Emilia-Romagna, tramite un sistema MTS composto da 3509 spire che registra i passaggi delle macchine; in seguito, per poter avere una comprensione maggiore dei fenomeni che si manifestano durante la transizione a stato congestionato, si è provveduto a creare un modello matematico utilizzato per le simulazioni al computer. I risultati ottenuti dalle simulazioni, poi, sono stati utilizzati per trovare l’osservabile cercato nei dati pervenuti dalle strade campione.
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Books on the topic "Traffic jams"

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Turtles, termites, and traffic jams: Explorations in massively parallel microworlds. Cambridge, Mass: MIT Press, 1994.

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Cole, David R. Traffic Jams: Analysing Everyday Life through the Immanent Materialism of Deleuze & Guattari. Brooklyn, NY: punctum books, 2013.

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Telecommuting: A 21st century solution to traffic jams and terrorism : hearing before the Subcommittee on the Federal Workforce and Agency Organization of the Committee on Government Reform, House of Representatives, One Hundred Ninth Congress, second session, July 18, 2006. Washington: U.S. G.P.O., 2007.

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Eliopulos, Nick. DC Super Friends : Flying High: (2008). New York, USA: Random House Children's Books (a Div. of Random House, Inc.) simultaneously in Canada by Random House of Canada, Ltd., 2008.

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Force, Illinois DUI Task. Final report of the Illinois DUI Task Force: Submitted to Governor James Thompson, January 1986. [Springfield, Ill.]: The Task Force, 1986.

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Dann, Jack. The rebel: An imagined life of James Dean. New York: William Morrow, 2004.

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Arnold, E. D. Evaluation of the Cross Alert system on the Virginia Capital Trail in James City County. Charlottesville, Va: Virginia Transportation Research Council, 2008.

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Office, General Accounting. Racial profiling: Limited data available on motorist stops : report to the Honorable James E. Clyburn, chairman, Congressional Black Caucus. Washington, D.C. (P.O. Box 37050, Washington 20013): The Office, 2000.

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None. Traffic Jams: Trains. Dorling Kindersley Publishers Ltd, 2000.

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Rankin, William. Drive Well: Reduce Traffic Jams. Independently Published, 2020.

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Book chapters on the topic "Traffic jams"

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Bak, Per. "On Economics and Traffic Jams." In How Nature Works, 183–98. New York, NY: Springer New York, 1996. http://dx.doi.org/10.1007/978-1-4757-5426-1_11.

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van der Merwe, Andria. "Financial Crises and Liquidity Traffic Jams." In Market Liquidity Risk, 19–38. New York: Palgrave Macmillan US, 2015. http://dx.doi.org/10.1057/9781137389237_2.

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Ong, Rebecca, Fabio Pinelli, Roberto Trasarti, Mirco Nanni, Chiara Renso, Salvatore Rinzivillo, and Fosca Giannotti. "Traffic Jams Detection Using Flock Mining." In Machine Learning and Knowledge Discovery in Databases, 650–53. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23808-6_49.

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Jansen, Gijsbertus R. M. "Commuting: Home Sprawl, Job Sprawl, Traffic Jams." In A Billion Trips a Day, 101–27. Dordrecht: Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-015-8118-9_7.

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Kerner, Boris S. "Origin of Emergence of Empirical Moving Traffic Jams: F$$\rightarrow $$S$$\rightarrow $$J Transitions." In Understanding Real Traffic, 135–43. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-79602-0_10.

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Belhaous, Safa, Soumia Chokri, Sohaib Baroud, Khalid Bentaleb, and Mohammed Mestari. "Evolutionary Heuristic for Avoiding Traffic Jams in Road Network Using A* Search Algorithm." In Innovations in Smart Cities Applications Volume 4, 423–34. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66840-2_32.

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Doreswamy and Osama A. Ghoneim. "Traffic Jams Detection and Congestion Avoidance in Smart City Using Parallel K-Means Clustering Algorithm." In Proceedings of International Conference on Cognition and Recognition, 21–30. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5146-3_3.

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Raubal, Martin, Dominik Bucher, and Henry Martin. "Geosmartness for Personalized and Sustainable Future Urban Mobility." In Urban Informatics, 59–83. Singapore: Springer Singapore, 2021. http://dx.doi.org/10.1007/978-981-15-8983-6_6.

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AbstractUrban mobility and the transport of people have been increasing in volume inexorably for decades. Despite the advantages and opportunities mobility has brought to our society, there are also severe drawbacks such as the transport sector’s role as one of the main contributors to greenhouse-gas emissions and traffic jams. In the future, an increasing number of people will be living in large urban settings, and therefore, these problems must be solved to assure livable environments. The rapid progress of information and communication, and geographic information technologies, has paved the way for urban informatics and smart cities, which allow for large-scale urban analytics as well as supporting people in their complex mobile decision making. This chapter demonstrates how geosmartness, a combination of novel spatial-data sources, computational methods, and geospatial technologies, provides opportunities for scientists to perform large-scale spatio-temporal analyses of mobility patterns as well as to investigate people’s mobile decision making. Mobility-pattern analysis is necessary for evaluating real-time situations and for making predictions regarding future states. These analyses can also help detect behavioral changes, such as the impact of people’s travel habits or novel travel options, possibly leading to more sustainable forms of transport. Mobile technologies provide novel ways of user support. Examples cover movement-data analysis within the context of multi-modal and energy-efficient mobility, as well as mobile decision-making support through gaze-based interaction.
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Höfer, Andreas, Erhard Esl, Daniel Türk, and Veronika Hüttinger. "Conception and Development of a Last Mile Vehicle for Urban Areas." In Small Electric Vehicles, 167–77. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-65843-4_13.

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AbstractIn megacities, increasing globalization effects are leading to rapidly increasing prosperity and augmented purchasing power, and thus to a growing need for punctual, cost-effective, and environmentally friendly delivery of goods. A smart, small electric vehicle concept is presented that targets on meeting the requirements for the delivery of goods in urban areas and that is designed especially for the delivery on the last mile. This last mile vehicle (LMV) for cargo transportation is attached to a truck. Whenever it is needed, for example to deliver goods into narrow streets, in pedestrian areas or in case of traffic jams, it can be unfolded and unloaded from the truck and hereby guarantees a flexible and punctual delivery of goods. This flexible on-time delivery is possible because the last mile vehicle is designed, so that the legal regulations of the non-motorized vehicle lane, that is everywhere to be found in Asia, are met. The vehicle is designed with three wheels, a range of 40-60 km and an electric drive train with a continuous power of 2 × 250 W that enables a maximum speed up to 40 km/h of the vehicle. The drive train consists of a battery pack that can be charged electrically from the truck, two inverters, and two electric wheel hub motors. The LMV has been designed and constructed as a prototype and has been tested on non-public roads to prove the vehicle concept. For Europe, it can be classified as an L2e vehicle and with slight modifications; it can be applied on European roads as well.
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Kerner, Boris S. "Empirical Features of Moving Jam Emergence." In The Physics of Traffic, 321–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-40986-1_12.

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Conference papers on the topic "Traffic jams"

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Kuznetsov, A. V., A. A. Avramenko, and D. G. Blinov. "Simulation of Traffic Jam Formation in Fast Axonal Transport." In ASME 2009 Heat Transfer Summer Conference collocated with the InterPACK09 and 3rd Energy Sustainability Conferences. ASMEDC, 2009. http://dx.doi.org/10.1115/ht2009-88345.

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Many neurodegenerative diseases, such as Alzheimer’s disease, are linked to swellings occurring in long arms of neurons. Many scientists believe that these swellings result from traffic jams caused by the failure of intracellular machinery responsible for fast axonal transport; such traffic jam can plug an axon and prevent the sufficient amount of organelles to be delivered toward the synapse of the axon. Mechanistic explanation of the formation of traffic jams in axons induced by overexpression of tau protein is based on the hypothesis that the traffic jam is caused not by the failure of molecular motors to transport organelles along individual microtubules but rather by the disruption of the microtubule system in an axon, by the formation of a swirl of disoriented microtubules at a certain location in the axon. This paper investigates whether a microtubule swirl itself, without introducing into the model microtubule discontinuities in the traffic jam region, is capable of capturing the traffic jam formation. The answer to this question can provide important insight into the mechanics of the formation of traffic jams in axons.
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Li, Tong. "Nonlinear Dynamics of Traffic Jams." In Second International Multi-Symposiums on Computer and Computational Sciences (IMSCCS 2007). IEEE, 2007. http://dx.doi.org/10.1109/imsccs.2007.4392661.

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Li, Tong. "Nonlinear Dynamics of Traffic Jams." In Second International Multi-Symposiums on Computer and Computational Sciences (IMSCCS 2007). IEEE, 2007. http://dx.doi.org/10.1109/imsccs.2007.60.

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Ghadami, Amin, Charles R. Doering, and Bogdan I. Epureanu. "Data-Driven Methods for Detecting Traffic Jams in Vehicular Traffic Systems." In ASME 2020 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2020. http://dx.doi.org/10.1115/imece2020-23691.

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Abstract Ground vehicle traffic jams are a serious issue in today’s society. Despite advances in traffic flow management in recent years, predicting traffic jams is still a challenge. Recently, novel techniques have been developed in complex systems theory to enable forecasting emergent behaviors in dynamical systems. Forecasting methods have been developed based on exploiting the phenomenon of critical slowing down, which occurs in dynamical systems near certain types of bifurcations and phase transitions. Herein, we explore recently developed tools of tipping point forecasting in complex systems, namely early warning indicators and bifurcation forecasting methods, and investigate their application to predict traffic jams on roads. The measurements required for forecasting are recorded dynamical features of the system such as headways between cars in traffic or density of cars on road. Forecasting approaches are applied to simulated and experimental traffic flow conditions. Results show that one can successfully predict proximity to the critical point of congestion as well as traffic dynamics after this critical point using the proposed approaches. The methodologies presented can be used to analyze stability of traffic models and address challenges related to the complexity of traffic dynamics.
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Romaszko, Lukasz. "IEEE ICDM 2010 Contest: Traffic Prediction -- Jams." In 2010 IEEE International Conference on Data Mining Workshops (ICDMW). IEEE, 2010. http://dx.doi.org/10.1109/icdmw.2010.48.

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Fekete, Sándor P., Christiane Schmidt, Axel Wegener, and Stefan Fischer. "Recognizing Traffic Jams with Hovering Data Clouds." In Second International Symposium on Leveraging Applications of Formal Methods, Verification and Validation (isola 2006). IEEE, 2006. http://dx.doi.org/10.1109/isola.2006.30.

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Kühne, Reinhart. "Statistics of extremes, traffic jams and natural disasters." In SPIE Fourth International Symposium on Fluctuations and Noise, edited by János Kertész, Stefan Bornholdt, and Rosario N. Mantegna. SPIE, 2007. http://dx.doi.org/10.1117/12.724798.

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Porfyri, K. N., I. K. Nikolos, A. I. Delis, and M. Papageorgiou. "Stability Analysis of a Macroscopic Traffic Flow Model for Adaptive Cruise Control Systems." In ASME 2015 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/imece2015-50977.

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Abstract:
Since the early days of traffic engineering, traffic flow stability has attracted a lot of attention, as the frequent occurrence of traffic jams, caused by small perturbations in traffic flow such as a sudden deceleration of a vehicle, deteriorate the performance of traffic flow and the utilization of the available infrastructure. Such traffic jams are usually related to instabilities in traffic flow, resulting in the formation of stop-and-go waves, propagating upstream the traffic flow. Emerging technologies in the field of Vehicle Automation and Communication Systems (VACS), such as Adaptive Cruise Control (ACC) systems, appear to be a remedy to reduce the amplitude or to eliminate the formation of such traffic instabilities. To this end, this work aims to derive a stability threshold of a novel macroscopic model, developed to simulate the flow of ACC-equipped vehicles, and study the impact of such vehicles on the stabilization of the traffic flow, with respect to small perturbations. The adopted macroscopic approach reflecting ACC traffic dynamics is based on the gas-kinetic (GKT) traffic flow model. The analytic results show that ACC vehicles enhance the stabilization of the traffic flow; the instability region is very narrow and by reducing the ACC time-gap setting it moves to higher values of density.
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Jiang, Peng, Zhenning Dong, Yujing Wang, Yuelong Su, and Zhiheng Li. "Empirical Study of Phantom Traffic Jams on Urban Expressway." In 2018 Ninth International Conference on Intelligent Control and Information Processing (ICICIP). IEEE, 2018. http://dx.doi.org/10.1109/icicip.2018.8606713.

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10

Mandziuk, Jacek, and Maciej Swiechowski. "Simulation-based approach to Vehicle Routing Problem with traffic jams." In 2016 IEEE Symposium Series on Computational Intelligence (SSCI). IEEE, 2016. http://dx.doi.org/10.1109/ssci.2016.7850028.

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