Relevant bibliographies by topics / Speed zoning (Traffic engineering)

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

Academic literature on the topic 'Speed zoning (Traffic engineering)'

Author: Grafiati
Published: 4 June 2021
Last updated: 23 February 2023

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Journal articles on the topic "Speed zoning (Traffic engineering)"

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Cheng-hua, Shi, Wang Ang, Sun Xiao-he, and Yang Wei-chao. "Research on the movement law and traffic safety zoning of spalled blocks in the linings of high-speed railway tunnels." Tunnelling and Underground Space Technology 128 (October 2022): 104614. http://dx.doi.org/10.1016/j.tust.2022.104614.

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Mejias, Luis, and Elizabeth Deakin. "Redevelopment and Revitalization along Urban Arterials." Transportation Research Record: Journal of the Transportation Research Board 1902, no. 1 (2005): 26–34. http://dx.doi.org/10.1177/0361198105190200104.

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Urban arterials are both promising and problematic locations for infill development and urban revitalization. San Pablo Avenue, a multilane urban arterial traversing nine cities and two counties along the eastern shore of San Francisco Bay in California, is considered here. The road developed over a long period: first as a streetcar line, then as an intercity automobile route, and most recently as a subregional traffic and transit route. Land uses from each of these transportation eras are still present along the avenue and range from neighborhood retail to automobile-oriented strip development. Recent transit service improvements and a strong housing market are leading to new developer interest in San Pablo Avenue. Findings are reported from interviews with 11 developers who recently built infill housing and mixed-use projects on or near the arterial. Developers see San Pablo Avenue's accessibility as a major asset but view transit services as a bonus instead of a necessity; transit availability allows developers to argue for reduced transportation impact fees and reduced parking requirements. Other aspects of the arterial's design, including high speeds and unattractive streetscapes, are problematic, as are zoning ordinances that require high parking ratios, large setbacks, and lengthy, discretionary approval processes. Small land parcels, incompatible adjacent uses, and high development costs are also drawbacks but, with creative development, are manageable. Local governments could provide incentives for private development along arterials such as San Pablo Avenue by improving street designs, reducing parking requirements, and updating zoning codes and approval processes.
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Zhao, Xueting, Liwei Hu, Xingzhong Wang, and Jiabao Wu. "Study on Identification and Prevention of Traffic Congestion Zones Considering Resilience-Vulnerability of Urban Transportation Systems." Sustainability 14, no. 24 (2022): 16907. http://dx.doi.org/10.3390/su142416907.

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In order to solve the problem of urban short-term traffic congestion and temporal and spatial heterogeneity, it is important to scientifically delineate urban traffic congestion response areas to alleviate regional traffic congestion and improve road network efficiency. Previous urban traffic congestion zoning is mostly divided by urban administrative divisions, which is difficult to reflect the difference of congestion degree within administrative divisions or traffic congestion zoning. In this paper, we introduce the Self-Organizing Feature Mapping (SOFM) model, construct the urban traffic congestion zoning index system based on the resilience and vulnerability of urban traffic systems, and establish the urban traffic congestion zoning model, which is divided into four, five, six, and seven according to the different structures of competition layer topology. The four vulnerability damage capacity indicators of traffic volume, severe congestion mileage, delay time and average operating speed, and two resilience supply capacity indicators of traffic systems, namely, road condition and number of lanes, are used as model input vectors; the data of Guiyang city from January to June 2021 are used as data sets to input four SOFM models for training and testing and the best SOFM model with six competitive topologies is constructed. Finally, the Support Vector Machine (SVM) is used to identify the optimal partition boundary line for traffic congestion. The results show that the four models predict the urban traffic congestion zoning level correctly over 95% on the test set, each traffic congestion zoning evaluation index in the urban area shows different obvious spatial clustering characteristics, the urban traffic congestion area is divided into six categories, and the city is divided into 16 zoning areas considering the urban traffic congestion control types (prevention zone, control zone, closure control zone). The spatial boundary is clear and credible, which helps to improve the spatial accuracy when predicting urban traffic congestion zoning and provides a new methodological approach for urban traffic congestion zoning and zoning boundary delineation.
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Bing, He, Xu Zhifeng, Xu Yangjie, Hu Jinxing, and Ma Zhanwu. "Integrating Semantic Zoning Information with the Prediction of Road Link Speed Based on Taxi GPS Data." Complexity 2020 (November 7, 2020): 1–14. http://dx.doi.org/10.1155/2020/6939328.

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Road link speed is one of the important indicators for traffic states. In order to incorporate the spatiotemporal dynamics and correlation characteristics of road links into speed prediction, this paper proposes a method based on LDA and GCN. First, we construct a trajectory dataset from map-matched GPS location data of taxis. Then, we use the LDA algorithm to extract the semantic function vectors of urban zones and quantify the spatial dynamic characteristics of road links based on taxi trajectories. Finally, we add semantic function vectors to the dataset and train a graph convolutional network to learn the spatial and temporal dependencies of road links. The learned model is used to predict the future speed of road links. The proposed method is compared with six baseline models on the same dataset generated by GPS equipped on taxis in Shenzhen, China, and the results show that our method has better prediction performance when semantic zoning information is added. Both composite and single-valued semantic zoning information can improve the performance of graph convolutional networks by 6.46% and 8.35%, respectively, while the baseline machine learning models work only for single-valued semantic zoning information on the experimental dataset.
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Flintsch, Gerardo W., Brian Ferne, Brian Diefenderfer, Samer Katicha, James Bryce, and Simon Nell. "Evaluation of Traffic-Speed Deflectometers." Transportation Research Record: Journal of the Transportation Research Board 2304, no. 1 (2012): 37–46. http://dx.doi.org/10.3141/2304-05.

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Levinson, David M., and Yuanlin Huang. "Windowed Transportation Planning Model." Transportation Research Record: Journal of the Transportation Research Board 1607, no. 1 (1997): 45–54. http://dx.doi.org/10.3141/1607-07.

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A transportation planning model that integrates regional and local-area forecasting approaches is developed and applied. Although regional models have the scope to model the interaction of demand and congestion, they lack spatial detail. Local-area analysis typically does not consider the feedback between new project loadings and existing levels of traffic. A windowed model, which retains regional trip distribution information and the consistency between travel demand and congestion, permits the use of a complete transportation network and block-level traffic zones while retaining computational feasibility. By combining the two methods a number of important policy issues can be addressed, including the implications of traffic calming, changes in flow due to alternative traffic operation schemes, the influence of microscale zoning changes on nearby intersections, and the impact of travel demand management on traffic congestion.
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Zefreh, Mohammad Maghrour, and Ádám Török. "DISTRIBUTION OF TRAFFIC SPEED IN DIFFERENT TRAFFIC CONDITIONS: AN EMPIRICAL STUDY IN BUDAPEST." Transport 35, no. 1 (2020): 68–86. http://dx.doi.org/10.3846/transport.2019.11725.

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Fundamental diagram, a graphical representation of the relationship among traffic flow, speed, and density, has been the foundation of traffic flow theory and transportation engineering for many years. Underlying a fundamental diagram is the relation between traffic speed and density, which serves as the basis to understand system dynamics. Empirical observations of the traffic speed versus traffic density show a wide-scattering of traffic speeds over a certain level of density, which would form a speed distribution over a certain level of density. The main aim of the current research is to study on the distribution of traffic speed in different traffic conditions in the urban roads since the distribution of traffic speed is necessary for many traffic engineering applications including generating traffic in micro-simulation systems. To do so, the traffic stream is videotaped at various locations in the city of Budapest (Hungary). The recorded videos were analysed by traffic engineering experts and different traffic conditions were extracted from these recorded videos based on the predefined scenarios. Then their relevant speeds in that time interval were estimated with the so-called “g-estimator method” using the outputs of the available loop detectors among the videotaped locations. Then different parametric candidate distributions have been fitted to the speeds by Maximum Likelihood Estimation (MLE) method. Having fitted different parametric distributions to speed data, they were compared by three goodness-of-fit tests along with two penalized criteria (Akaike Information Criterion – AIC and Bayesian Information Criterion – BIC) in order to overcome the over-fitting problems. The results showed that the speed of traffic flow follows exponential, normal, lognormal, gamma, beta and chisquare distribution in the condition that traffic flow followed over-saturated congestion, under saturated flow, free flow, congestion, accelerated flow and decelerated flow respectively.
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Ke, Ruimin, Wan Li, Zhiyong Cui, and Yinhai Wang. "Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact." Transportation Research Record: Journal of the Transportation Research Board 2674, no. 4 (2020): 459–70. http://dx.doi.org/10.1177/0361198120911052.

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Traffic speed prediction is a critically important component of intelligent transportation systems. Recently, with the rapid development of deep learning and transportation data science, a growing body of new traffic speed prediction models have been designed that achieved high accuracy and large-scale prediction. However, existing studies have two major limitations. First, they predict aggregated traffic speed rather than lane-level traffic speed; second, most studies ignore the impact of other traffic flow parameters in speed prediction. To address these issues, the authors propose a two-stream multi-channel convolutional neural network (TM-CNN) model for multi-lane traffic speed prediction considering traffic volume impact. In this model, the authors first introduce a new data conversion method that converts raw traffic speed data and volume data into spatial–temporal multi-channel matrices. Then the authors carefully design a two-stream deep neural network to effectively learn the features and correlations between individual lanes, in the spatial–temporal dimensions, and between speed and volume. Accordingly, a new loss function that considers the volume impact in speed prediction is developed. A case study using 1-year data validates the TM-CNN model and demonstrates its superiority. This paper contributes to two research areas: (1) traffic speed prediction, and (2) multi-lane traffic flow study.
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Zhao, Dan, Fengchun Han, Meng Meng, Jun Ma, and Quantao Yang. "Exploring the influence of traffic enforcement on speeding behavior on low-speed limit roads." Advances in Mechanical Engineering 11, no. 12 (2019): 168781401989157. http://dx.doi.org/10.1177/1687814019891572.

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Speeding on low-speed limit roads is a common traffic offense in China, which could be due to the mild traffic safety enforcement. The article aims to explicit the impact of traffic enforcement measures on the speeding behavior on low-speed limit roads. First, field data were collected to demonstrate the severity of speeding by investigating speed distribution; second, a virtual traffic enforcement was designed by considering three factors related to traffic enforcement, and a stated preference survey questionnaire including six scenarios was designed and implemented; finally, a series of generalized regret random minimization models were established to study the relationship of speeding behavior and traffic enforcement as well as drivers’ personal characteristics. From the stated preference survey analysis, the research figures out that other vehicles’ average speed is the most important reference to choose speed rather than traffic penalties, and the model estimation results show that speeding violation grows severe if traffic enforcements are lenient. Therefore, increasing the violation costs is a powerful means of lowering the probability of speeding for individual, thus proceeding the drop of vehicles’ average speed, and the fall of average speed will contribute to decrease speeding subsequently.
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Cathey, F. W., and D. J. Dailey. "Transit Vehicles as Traffic Probe Sensors." Transportation Research Record: Journal of the Transportation Research Board 1804, no. 1 (2002): 23–30. http://dx.doi.org/10.3141/1804-04.

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New algorithms are presented that use transit vehicles as probes for determining traffic speeds and travel times along freeways and other primary arterials. A mass transit tracking system based on automatic vehicle location data and a Kalman filter used to estimate vehicle position and speed are described. A system of virtual probe sensors that measure transit vehicle speeds by using the track data is also described. Examples showing the correlation between probe data and inductance loop speed-trap data are presented. Also presented is a method that uses probe sensor data to define vehicle speed along an arbitrary roadway as a function of space and time, a speed function. This speed function is used to estimate travel time given an arbitrary starting time. Finally, a graphical application is introduced for viewing real-time speed measurements from a set of virtual sensors that can be located throughout King County, Washington, on arterials and freeways.
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Dissertations / Theses on the topic "Speed zoning (Traffic engineering)"

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Thorin, Kristoffer. "Optimal Speed Controller in the Presence of Traffic Lights." Thesis, Uppsala universitet, Avdelningen för systemteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-325352.

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This report presents an approach on how to utilize information on future states of traffic lights to reduce the energy consumption and trip time for a Heavy Duty Vehicle. Model Predictive Control is proposed as a solution to handle the optimisation on-line and the concept is tested for various prediction horizons in which information can be received. Further on, it is investigated if the implemented controller is robust enough to execute the same task in a scenario where only the current state is known and future states are predicted. Comparison with a reference vehicle demonstrates improved fuel economy as well as reduced trip time when the information is given. It is shown that the results are improved as the prediction horizon is extended, but converges after 400-500 meters. As the phases of the traffic lights are predicted, fuel economy can be improved, but it comes at a price from being non-robust with drastic braking and increased trip time as predictions might be inaccurate.
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Yu, Jie Petropulu Athina P. "Modeling of high-speed wireline and wireless network traffic /." Philadelphia, Pa. : Drexel University, 2005. http://dspace.library.drexel.edu/handle/1860/469.

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Ghiasi, Amir. "Connected Autonomous Vehicles: Capacity Analysis, Trajectory Optimization, and Speed Harmonization." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7295.

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Emerging connected and autonomous vehicle technologies (CAV) provide an opportunity to improve highway capacity and reduce adverse impacts of stop-and-go traffic. To realize the potential benefits of CAV technologies, this study provides insightful methodological and managerial tools in microscopic and macroscopic traffic scales. In the macroscopic scale, this dissertation proposes an analytical method to formulate highway capacity for a mixed traffic environment where a portion of vehicles are CAVs and the remaining are human-driven vehicles (HVs). The proposed analytical mixed traffic highway capacity model is based on a Markov chain representation of spatial distribution of heterogeneous and stochastic headways. This model captures not only the full spectrum of CAV market penetration rates but also all possible values of CAV platooning intensities that largely affect the spatial distribution of different headway types. Numerical experiments verify that this analytical model accurately quantifies the corresponding mixed traffic capacity at various settings. This analytical model allows for examination of the impact of different CAV technology scenarios on mixed traffic capacity. We identify sufficient and necessary conditions for the mixed traffic capacity to increase (or decrease) with CAV market penetration rate and platooning intensity. These theoretical results caution scholars not to take CAVs as a sure means of increasing highway capacity for granted but rather to quantitatively analyze the actual headway settings before drawing any qualitative conclusion. In the microscopic scale, this study develops innovative control strategies to smooth highway traffic using CAV technologies. First, it formulates a simplified traffic smoothing model for guiding movements of CAVs on a general one-lane highway segment. The proposed simplified model is able to control the overall smoothness of a platoon of CAVs and approximately optimize traffic performance in terms of fuel efficiency and driving comfort. The elegant theoretical properties for the general objective function and the associated constraints provides an efficient analytical algorithm for solving this problem to the exact optimum. Numerical examples reveal that this exact algorithm has an efficient computational performance and a satisfactory solution quality. This trajectory-based traffic smoothing concept is then extended to develop a joint trajectory and signal optimization problem. This problem simultaneously solves the optimal CAV trajectory function shape and the signal timing plan to minimize travel time delay and fuel consumption. The proposed algorithm simplifies the vehicle trajectory and fuel consumption functions that leads to an efficient optimization model that provides exact solutions. Numerical experiments reveal that this algorithm is applicable to any signalized crossing points including intersections and work-zones. Further, the model is tested with various traffic conditions and roadway geometries. These control approaches are then extended to a mixed traffic environment with HVs, connected vehicles (CVs), and CAVs by proposing a CAV-based speed harmonization algorithm. This algorithm develops an innovative traffic prediction model to estimate the real-time status of downstream traffic using traffic sensor data and information provided by CVs and CAVs. With this prediction, the algorithm controls the upstream CAVs so that they smoothly hedge against the backward deceleration waves and gradually merge into the downstream traffic with a reasonable speed. This model addresses the full spectrum of CV and CAV market penetration rates and various traffic conditions. Numerical experiments are performed to assess the algorithm performance with different traffic conditions and CV and CAV market penetration rates. The results show significant improvements in damping traffic oscillations and reducing fuel consumption.
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Riley, Kevin D. "Impacts on vehicular traffic flow due to changes in pedestrian walking speed." Thesis, California State University, Long Beach, 2015. http://pqdtopen.proquest.com/#viewpdf?dispub=1571867.

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<p> In January 2012, California adopted federal law requiring city's traffic engineers to decrease the pedestrian walking speeds at signalized intersections from 4fps to 3.5fps. Ten signalized intersections along Atlantic Avenue between Spring Street to Carson Street were selected to evaluate impacts due to pedestrian walking speed changes. One hour peak evening volumes were collected and entered into Synchro by Trafficware to compare intersections and approach delays on 75 and 100 seconds cycle lengths with combination of coordinated and uncoordinated systems. Volume growth rate effects, surveyed pedestrian walking speed, and various observed characteristics at signalized intersection crossing were evaluated. Converting pedestrian walking speed from 4-fps to 3.5fps caused the cycle length to increase from 75 seconds to 90 seconds for coordination purposes. The Synchro results, overall, showed more intersection/approach delay, vehicular growth rates data showed a small effect on the major intersections delay when comparing the two walking speeds, and sampled pedestrian walking speeds indicated that the 15<sup>th</sup> percentile of pedestrians walked at a faster speed than 3.5fps.</p>
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Roux, Jacques. "Establishing and applying speed-flow relationships for traffic on South African freeways." Thesis, Stellenbosch : Stellenbosch University, 2001. http://hdl.handle.net/10019.1/52261.

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Thesis (MEng)--University of Stellenbosch, 2001.<br>ENGLISH ABSTRACT: Peak mornmg traffic-flow data were obtained from video footage of three representative freeway sections on the Nl and N2 westbound towards Cape Town. Flow, speed, and density measurements were made from the footage with the aid of a stopwatch. Many researchers (2-12) have originated and developed models to describe the relationships between traffic flow characteristics (speed, flow, and density) on freeways. In this report, a number of these models have been investigated with data obtained from South African freeways. The ability of each model to predict flow parameters over the entire range of data was evaluated with the aid of statistical methods. The tests were performed by regressing average speed vs. average density. Flow-density and speed-flow relationships were derived through application of the steady-state equation (2.6). In each case, a final model was chosen through visual inspection that consisted of two separate curves, one for the uncongested flow regime and one for the congested flow regime. Furthermore, speed-flow relationships were examined for individual lanes and compared to relationships established for average lanes. The models were also compared to models obtained from overseas studies (1,16,19) as well as from studies done locally (17). A secondary objective of this study is to investigate the performance of existing freeway facilities through application of the relevant models to the traffic-flow data of a particular facility. The current peak-morning performance of the N2 freeway section is investigated in terms of travel-time and travel cost. The particular study section consists of three lanes, the right hand lane being an HOY lane dedicated to taxis and buses. Different hypothetical cases are investigated. The first hypothetical case is an investigation into the traffic situation on the freeway section without the influence of the HOY lane. The second hypothetical case investigates the traffic situation on the section with perfect operation of the HOY lane. The current performance of the N2 section is compared to the performance of each of the hypothetical cases.<br>AFRIKAANSE OPSOMMING: Oggend-spits verkeersvloei data is verkry vanaf drie verteenwoordigende seksies op die Nl en N2 deurpaaie naby Kaapstad met die gebruik van 'n video kamera. Vloei, spoed, end digtheid opnames is gemaak met behulp van 'n stophorlosie. Verskeie navorsers (2-12) het modelle gepostuleer en ontwikkelom die verhoudings tussen verkeersvloei eienskappe (spoed, volume, en digtheid) op deurpaaie te beskryf. In hierdie verslag word 'n aantal van hierdie modelle ondersoek met data wat verkry is van Suid-Afrikaanse deurpaaie. Die vermoë van elke model om vloei eienskappe oor die hele bestek van die data te voorspel is geëvalueer met behulp van statistiese metodes. Statistiese toetse behels 'n regressie analise van gemiddelde spoed teenoor gemiddelde digtheid. Volume-digtheid en spoed-volume verwantskappe is direk afgelei vanaf Vergelyking 2.6. Vir elke geval is 'n finale model m.b.v. visuele inspeksie gekies wat bestaan het uit twee afsonderlike kurwes, een kurwe vir die vryvloei regime en 'n ander kurwe vir hoë-digtheid toestande. Verder word spoedvolume verwantskappe vir afsonderlike deurpad-lane ondersoek en vergelyk met verwantskappe wat verkry is vir gemiddelde lane. Die modelle word ook vergelyk met modelle wat verkry is vanaf oorsese studies (1,16,19), sowel as met modelle wat plaaslik verkry is (17). 'n Sekondêre doel van hierdie studie is om die prestasie van bestaande deurpadfasiliteite te ondersoek deur die verskillende modelle aan te wend tot die verkeersvloei data van 'n betrokke fasiliteit. Die prestasie van die N2 deurpad seksie gedurende oggend-spits verkeer is ondersoek in terme van reistyd en ryskoste. Die betrokke seksie bestaan uit drie lane, waarvan die regter laan gereserveer is vir busse en taxis. Verskeie hipoteses is ook ondersoek. Die eerste hipotese is 'n ondersoek na die verkeers-vloei kondisie op die seksie sonder die invloed van die bus- en taxi-laan. Die tweede hipotese ondersoek die seksie met perfekte werking van die bus- en taxilaan. Die huidige prestasie van die N2 seksie is vergelyk met die prestasie van elk van die hipoteses.
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Ash, Kelly Grant. "Increasing Speed Limit Compliance in Reduced-Speed School Zones." Diss., CLICK HERE for online access, 2006. http://contentdm.lib.byu.edu/ETD/image/etd1271.pdf.

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Goyal, Mukul. "Internet Traffic Engineering: QoS Translation and Survivability." Columbus, OH : Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc%5Fnum=osu1047407545.

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Thesis (Ph. D.)--Ohio State University, 2003.<br>Title from first page of PDF file. Document formatted into pages; contains xxi, 271 p.: ill. Includes abstract and vita. Advisors: Ming T. Liu and Wu-chi Feng, Dept. of Computer and Information Science. Includes bibliographical references (p. 261-271).
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Fleischer, Christian Georg. "Measuring Vehicle Speed with Occlusion Handling in Vision-based Traffic Surveillance." The Ohio State University, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=osu1238132349.

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Schoepflin, Todd Nelson. "Algorithms for estimating mean vehicle speed using uncalibrated traffic management cameras /." Thesis, Connect to this title online; UW restricted, 2003. http://hdl.handle.net/1773/6034.

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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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Books on the topic "Speed zoning (Traffic engineering)"

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ITE Technical Council Committee TENC-97-12., ed. Survey of speed zoning practices. Institute of Transportation Engineers, Technical Council Committee TENC-97-12, 2001.

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Florida. Bureau of Traffic Engineering., ed. Speed zoning for highways, roads & streets in Florida: For compliance with Florida Statutes, Chapter 316. Florida Dept. of Transportation, Bureau of Traffic Engineering, 1985.

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Forbes, Gerry J. Methods and practices for setting speed limits: An informational report. Institute of Transportation Engineers, 2012.

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Engineers, Institute of Transportation. Methodologies for the determination of advisory speeds: An informational report of the Institute of Transportation Engineers. Institute of Transportation Engineers, 2010.

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Engineers, Institute of Transportation. Methodologies for the determination of advisory speeds: An informational report of the Institute of Transportation Engineers. Institute of Transportation Engineers, 2010.

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Kay, Fitzpatrick, National Cooperative Highway Research Program., and National Research Council (U.S.). Transportation Research Board., eds. Design speed, operating speed, and posted speed practices. Transportation Research Board, National Research Council, 2003.

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Gattis, J. L. Designing horizontal curves for low-speed environments. University of Arkansas, Mack-Blackwell National Rural Transportation Study Center, 2003.

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Montana. Highway Traffic Safety Division. Speed zone study for streets and highways. The Division, 1988.

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Massachusetts. Metropolitan Area Planning Council. Trip reduction zoning: With a sample application for the city of Cambridge. The Council, 1988.

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Chui, Margaret K. The value of travel time: New estimates developed using a speed-choice model. Texas Transportation Institute, Texas A&M University System, 1986.

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Book chapters on the topic "Speed zoning (Traffic engineering)"

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Salter, R. J. "Merging on to High Speed Roads." In Traffic Engineering. Macmillan Education UK, 1989. http://dx.doi.org/10.1007/978-1-349-10800-8_18.

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Salter, R. J. "Flow, Speed and Density Relationships for Highway Flow." In Traffic Engineering. Macmillan Education UK, 1989. http://dx.doi.org/10.1007/978-1-349-10800-8_8.

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Salter, R. J. "Flow, Speed and Density Relationships Applied to a Highway Bottleneck." In Traffic Engineering. Macmillan Education UK, 1989. http://dx.doi.org/10.1007/978-1-349-10800-8_9.

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Salter, R. J. "Measurement of Highway Traffic Stream Speed Time and Space Mean Speeds." In Traffic Engineering. Macmillan Education UK, 1989. http://dx.doi.org/10.1007/978-1-349-10800-8_1.

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Wang, Jianping, Stephen Patek, Haiyong Wang, and Jörg Liebeherr. "Traffic Engineering with AIMD in MPLS Networks." In Protocols for High Speed Networks. Springer Berlin Heidelberg, 2002. http://dx.doi.org/10.1007/3-540-47828-0_13.

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Masada, Tomonari, and Atsuhiro Takasu. "Traffic Speed Data Investigation with Hierarchical Modeling." In Future Data and Security Engineering. Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-26135-5_10.

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Di, Shengde, Jian Zhou, Guohui Shen, and Hongbo Wu. "Speed management method of national highway based on risk assessment." In Frontier Research: Road and Traffic Engineering. CRC Press, 2022. http://dx.doi.org/10.1201/9781003305002-41.

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Kumar, Rishabh, Lavepreet Singh, Yuvraj Bhardwaj, Manish Singh, and Rajneesh Kumar. "Green Power Generation from Road Traffic Using Speed Breaker." In Lecture Notes in Mechanical Engineering. Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-9613-8_21.

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Xia, Xue, and Jing-yuan Gai. "Road traffic conflict prediction model based on speed dispersion in mixed traffic environment." In Green Building, Environment, Energy and Civil Engineering. CRC Press, 2016. http://dx.doi.org/10.1201/9781315375106-71.

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Zhang, X. L., J. L. Xu, and X. H. Tong. "Study on main line speed in interchange diversion zone of freeway." In Frontier Research: Road and Traffic Engineering. CRC Press, 2022. http://dx.doi.org/10.1201/9781003305002-55.

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Conference papers on the topic "Speed zoning (Traffic engineering)"

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Liu, Lijiao, and Jihui Ma. "The Impact of Urban Complex Function Zoning on Traffic." In 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017). Atlantis Press, 2017. http://dx.doi.org/10.2991/emim-17.2017.77.

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Liqun Li, Long Chen, and Daxing Huang. "Study on traffic demand management strategies of rail transit based on urban functional zoning." In 2010 International Conference on Future Information Technology and Management Engineering (FITME). IEEE, 2010. http://dx.doi.org/10.1109/fitme.2010.5655701.

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Liu, Yaowu, Zhangyong Hu, Qiang Su, and Jiazhen Huo. "Energy Saving of Elevator Group Control Based on Optimal Zoning Strategy with Interfloor Traffic." In 2010 International Conference on Information Management, Innovation Management and Industrial Engineering (ICIII). IEEE, 2010. http://dx.doi.org/10.1109/iciii.2010.399.

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Makki, Ahmed Adnan, Trung Thanh Nguyen, June Ren, William Hurst, and Dhiya Al-jumeily. "Utilizing Automatic Traffic Counters to Predict Traffic Flow Speed." In 2019 12th International Conference on Developments in eSystems Engineering (DeSE). IEEE, 2019. http://dx.doi.org/10.1109/dese.2019.00153.

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Bhatt, Vijay Deep, Sachin Singh Khati, Diwesh Pandey, and Hem Chandra Pant. "Wireless traffic system with speed control." In 2nd International Conference on Computer and Automation Engineering (ICCAE 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccae.2010.5451924.

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Hosseini, S. H., B. Moshiri, A. Rahimi-Kian, and B. N. Araabi. "Traffic speed prediction using mutual information." In 2012 25th IEEE Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2012. http://dx.doi.org/10.1109/ccece.2012.6334975.

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Ren, Shen, Lin Han, Zengxiang Li, and Bharadwaj Veeravalli. "Spatial-temporal traffic speed bands data analysis and prediction." In 2017 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM). IEEE, 2017. http://dx.doi.org/10.1109/ieem.2017.8290003.

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Liu, Zheng, Lei Chen, and Yongxin Tong. "Realtime Traffic Speed Estimation with Sparse Crowdsourced Data." In 2018 IEEE 34th International Conference on Data Engineering (ICDE). IEEE, 2018. http://dx.doi.org/10.1109/icde.2018.00038.

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Shawky, Mohamed, Iyad Sahnoon, and Ahmed Al-Zaidy. "Predicting Speed-Related Traffic Violations on Rural Highways." In The 2nd World Congress on Civil, Structural, and Environmental Engineering. Avestia Publishing, 2017. http://dx.doi.org/10.11159/icte17.117.

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Chawuthai, Rathachai, Kasidit Pruekwangkhao, and Thanunchai Threepak. "Spatial-Temporal Traffic Speed Prediction on Thailand Roads." In 2021 7th International Conference on Engineering, Applied Sciences and Technology (ICEAST). IEEE, 2021. http://dx.doi.org/10.1109/iceast52143.2021.9426257.

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Reports on the topic "Speed zoning (Traffic engineering)"

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Adsit, Sarah E., Theodora Konstantinou, Konstantina Gkritza, and Jon D. Fricker. Public Acceptance of INDOT’s Traffic Engineering Treatments and Services. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317280.

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As a public agency, interacting with and understanding the public’s perspective regarding agency activities is an important endeavor for the Indiana Department of Transportation (INDOT). Although INDOT conducts a biennial customer satisfaction survey, it is occasionally necessary to capture public perception regarding more specific aspects of INDOT’s activities. In particular, INDOT needs an effective way to measure and track public opinions and awareness or understanding of a select set of its traffic engineering practices. To evaluate public acceptance of specific INDOT traffic engineering activities, a survey consisting of 1.000 adults residing within the State of Indiana was conducted. The survey population was representative in terms of age and gender of the state as of the 2010 U.S. Census. The survey was administered during the months of July and August 2020. Public awareness regarding emerging treatments not currently implemented in Indiana is low and opposition to the same new technologies is prominent. Older or female drivers are less likely to be aware of emerging treatments, and older drivers are more likely to oppose potential implementation of these treatments. Although roundabouts are commonplace in Indiana, multi-lane roundabouts remain controversial among the public. Regarding maintenance and protection of traffic during work zones and considering full or partial roadway closure, public preference is for partial closure; this preference is stronger in rural areas. The public equally agrees and disagrees that INDOT minimizes construction related traffic delays. Approximately 76% of Indiana drivers believe themselves to above average drivers, while an additional 23% believe themselves to be average. Driver perceptions of average highway speeds speed are not aligned with posted speed limit as the perceived average speed on Indiana’s urban freeways and rural and urban state highways is considerably higher than the actual speed limit.
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Bäumler, Maximilian, Madlen Ringhand, Christian Siebke, Marcus Mai, Felix Elrod, and Günther Prokop. Report on validation of the stochastic traffic simulation (Part B). Technische Universität Dresden, 2021. http://dx.doi.org/10.26128/2021.243.

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This document is intended to give an overview of the validation of the human subject study, conducted in the driving simulator of the Chair of Traffic and Transportation Psychology (Verkehrspsychologie – VPSY) of the Technische Universität Dresden (TUD), as well of the validation of the stochastic traffic simulation developed in the AutoDrive project by the Chair of Automotive Engineering (Lehrstuhl Kraftfahrzeugtechnik – LKT) of TUD. Furthermore, the evaluation process of a C-AEB (Cooperative-Automatic Emergency Brake) system is demonstrated. The main purpose was to compare the driving behaviour of the study participants and the driving behaviour of the agents in the traffic simulation with real world data. Based on relevant literature, a validation concept was designed and real world data was collected using drones and stationary cameras. By means of qualitative and quantitative analysis it could be shown, that the driving simulator study shows realistic driving behaviour in terms of mean speed. Moreover, the stochastic traffic simulation already reflects reality in terms of mean and maximum speed of the agents. Finally, the performed evaluation proofed the suitability of the developed stochastic simulation for the assessment process. Furthermore, it could be shown, that a C-AEB system improves the traffic safety for the chosen test-scenarios.
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Kress, Marin. Vessel speed analysis before and after dredging near Missouri River mile 282 in November 2020. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/43283.

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The purpose of this Coastal and Hydraulics Engineering Technical Note (CHETN) is to present information on vessel traffic before, during, and after a dredging event around river mile 282 of the Missouri River in November 2020 along with contextual information about tonnage and commodities that utilize this navigation project.
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Chien, Stanley, Lauren Christopher, Yaobin Chen, Mei Qiu, and Wei Lin. Integration of Lane-Specific Traffic Data Generated from Real-Time CCTV Videos into INDOT's Traffic Management System. Purdue University, 2023. http://dx.doi.org/10.5703/1288284317400.

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