Academic literature on the topic 'Travel time (Traffic engineering) – Vancouver – Case studies'
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Journal articles on the topic "Travel time (Traffic engineering) – Vancouver – Case studies"
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El Esawey, Mohamed, and Tarek Sayed. "Travel time estimation in urban networks using limited probes data." Canadian Journal of Civil Engineering 38, no. 3 (March 2011): 305–18. http://dx.doi.org/10.1139/l11-001.
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Travel time is a simple and robust network performance measure that is well understood by the public. However, travel time data collection can be costly especially if the analysis area is large. This research proposes a solution to the problem of limited network sensor coverage caused by insufficient sample size of probe vehicles or inadequate numbers of fixed sensors. Within a homogeneous road network, nearby links of similar character are exposed to comparable traffic conditions, and therefore, their travel times are likely to be positively correlated. This correlation can be useful in developing travel time relationships between nearby links so that if data becomes available on a subset of these links, travel times of their neighbours can be estimated. A methodology is proposed to estimate link travel times using available data from neighbouring links. To test the proposed methodology, a case study was undertaken using a VISSIM micro-simulation model of downtown Vancouver. The simulation model was calibrated and validated using field traffic volumes and travel time data. Neighbour links travel time estimation accuracy was assessed using different error measurements and the results were satisfactory. Overall, the results of this research demonstrate the feasibility of using neighbour links data as an additional source of information to estimate travel time, especially in case of limited coverage.
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Mohammadi, Roozbeh, Amir Golroo, and Mahdieh Hasani. "Effect of Traffic Information on Travel Time of Medium-distance Trips: A Case Study in Tehran." PROMET - Traffic&Transportation 30, no. 3 (June 27, 2018): 281–91. http://dx.doi.org/10.7307/ptt.v30i3.2738.
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In populated cities with high traffic congestion, traffic information may play a key role in choosing the fastest route between origins and destinations, thus saving travel time. Several research studies investigated the effect of traffic information on travel time. However, little attention has been given to the effect of traffic information on travel time according to trip distance. This paper aims to investigate the relation between real-time traffic information dissemination and travel time reduction for medium-distance trips. To examine this relation, a methodology is applied to compare travel times of two types of vehicle, with and without traffic information, travelling between an origin and a destination employing probe vehicles. A real case study in the metropolitan city of Tehran, the capital of Iran, is applied to test the methodology. There is no significant statistical evidence to prove that traffic information would have a significant impact on travel time reduction in a medium-distance trip according to the case study.
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Ma, Zhengfeng, Darong Huang, Changguang Li, and Jianhua Guo. "Travel Time Reliability-Based Signal Timing Optimization for Urban Road Traffic Network Control." Mathematical Problems in Engineering 2020 (December 1, 2020): 1–11. http://dx.doi.org/10.1155/2020/8898062.
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Due to increasing traffic demand, many metropolitan areas are experiencing extensive traffic congestion, which demands for efficient traffic signal timing and optimization. However, conventional efficiency measure-based signal optimization cannot handle the ubiquitous uncertainty in the road networks, demanding for the incorporation of reliability measures into signal optimization, which is still in its early stage. Therefore, targeting this issue, based on the recent studies on recognizing travel time reliability (TRR) as an important reliability measure of road networks, a travel time reliability-based urban road traffic network signal timing optimization model is proposed in this paper, with the objective function to optimize a TTR measure, i.e., buffer time index. The proposed optimization model is solved using the heuristic particle swarm optimization approach. A case study is conducted using microscopic traffic simulation for a road network in the City of Nanjing, China. Results demonstrate that the proposed optimization model can improve travel time reliability of the road traffic network and the efficiency of the road traffic network as well. Future studies are recommended to expand the integration of travel time reliability into traffic signal timing optimization.
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Karmakar, Nabaruna, Seyedbehzad Aghdashi, Nagui M. Rouphail, and Billy M. Williams. "Validation and Calibration of Freeway Reliability Methodology in the Highway Capacity Manual: Method and Case Studies." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 15 (September 28, 2018): 93–104. http://dx.doi.org/10.1177/0361198118798723.
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Traffic congestion costs drivers an average of $1,200 a year in wasted fuel and time, with most travelers becoming less tolerant of unexpected delays. Substantial efforts have been made to account for the impact of non-recurring sources of congestion on travel time reliability. The 6th edition of the Highway Capacity Manual (HCM) provides a structured guidance on a step-by-step analysis to estimate reliability performance measures on freeway facilities. However, practical implementation of these methods poses its own challenges. Performing these analyses requires assimilation of data scattered in different platforms, and this assimilation is complicated further by the fact that data and data platforms differ from state to state. This paper focuses on practical calibration and validation methods of the core and reliability analyses described in the HCM. The main objective is to provide HCM users with guidance on collecting data for freeway reliability analysis as well as validating the reliability performance measures predictions of the HCM methodology. A real-world case study on three routes on Interstate 40 in the Raleigh-Durham area in North Carolina is used to describe the steps required for conducting this analysis. The travel time index (TTI) distribution, reported by the HCM models, was found to match those from probe-based travel time data closely up to the 80th percentile values. However, because of a mismatch between the actual and HCM estimated incident allocation patterns both spatially and temporally, and the fact that traffic demands in the HCM methods are by default insensitive to the occurrence of major incidents, the HCM approach tended to generate larger travel time values in the upper regions of the travel time distribution.
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Liu, Yuchen, Jianhong (Cecilia) Xia, and Aloke Phatak. "Evaluating the Accuracy of Bluetooth-Based Travel Time on Arterial Roads: A Case Study of Perth, Western Australia." Journal of Advanced Transportation 2020 (February 21, 2020): 1–19. http://dx.doi.org/10.1155/2020/9541234.
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Bluetooth (BT) time-stamped media access control (MAC) address data have been used for traffic studies worldwide. Although Bluetooth (BT) technology has been widely recognised as an effective, low-cost traffic data source in freeway traffic contexts, it is still unclear whether BT technology can provide accurate travel time (TT) information in complex urban traffic environments. Therefore, this empirical study aims to systematically evaluate the accuracy of BT travel time estimates in urban arterial contexts. There are two major hurdles to deriving accurate TT information for arterial roads: the multiple detection problem and noise in BT estimates. To date, they have not been fully investigated, nor have well-accepted solutions been found. Using approximately two million records of BT time-stamped MAC address data from twenty weekdays, this study uses five different BT TT-matching methods to investigate and quantify the impact of multiple detection problems and the noise in BT TT estimates on the accuracy of average BT travel times. Our work shows that accurate Bluetooth-based travel time information on signalised arterial roads can be derived if an appropriate matching method can be selected to smooth out the remaining noise in the filtered travel time estimates. Overall, average-to-average and last-to-last matching methods are best for long (>1 km) and short (≤1 km) signalised arterial road segments, respectively. Furthermore, our results show that the differences between BT and ground truth average TTs or speeds are systematic, and adding a calibration is a pragmatic method to correct inaccurate BT average TTs or speeds. The results of this research can help researchers and road operators to better understand BT technology for TT analysis and consequently to optimise the deployment location and configuration of BT MAC address scanners.
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Banks, James H. "Performance Measurement for Traffic Management Systems." Transportation Research Record: Journal of the Transportation Research Board 1634, no. 1 (January 1998): 39–45. http://dx.doi.org/10.3141/1634-05.
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Performance measurement refers to attempts to quantify some aspect of the performance of an organization. A study was conducted to analyze needs, opportunities, and techniques for measuring performance of transportation management centers (TMCs). Opportunities and needs were identified by analyzing the interrelationships among performance measurement objectives, objects, and study designs. This analysis suggests that before-and-after evaluation studies of traffic management actions and monitoring of traffic data to detect system changes are the most appropriate forms of performance measurement for TMCs. Important potential measures of effectiveness for traffic management systems include travel time and related measures, ramp delay, traffic volumes, accident rates, traffic information accuracy, incident duration, and equipment status. Techniques are available for quantifying these measures, although there are a number of concerns with data accuracy, especially where travel times are estimated from loop-detector data. Case studies of two California TMCs suggest that, although sophisticated data collection systems are available or planned, the institutional infrastructure to carry out performance measurement may be lacking.
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Coloma, Juan Francisco, Marta Garcia, and Raúl Guzmán. "Effects of Bypass in Small and Non-congested Cities: A Case Study of the City Badajoz." PROMET - Traffic&Transportation 30, no. 4 (September 10, 2018): 479–89. http://dx.doi.org/10.7307/ptt.v30i4.2748.
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Small cities with less than 200,000 inhabitants do not usually suffer from chronic congestion problems. However, private vehicles are used excessively, making it necessary to implement measures to encourage further use of public transport and pedestrian mobility to make it more sustainable. Bypasses improve level of service (LOS) by removing cars from the city center, leading to significant reductions in overall travel time. Most studies so far have been conducted in large cities suffering chronic congestion problems, so the aim of this research is to analyze the effects of bypasses in small and non-congested cities through the construction of a traffic model in Badajoz (Spain), starting with the allocation of the origin-destination travel matrix derived from surveys and traffic counts conducted at the southern and eastern accesses. The traffic model describes the mobility in potentially-capturable future southern traffic relationships and allows insights into different alternatives in the construction of a new high LOS road. This research concludes that small cities with no chronic congestion problems should plan bypasses as close as possible to the city, since they are the most economical, produce greater traffic capture, greater time savings, and eliminate the largest number of CO2 emissions from the urban center. The more distant alternatives have a higher LOS, however, these are longer and more expensive solutions that also capture less traffic and thus eliminate less CO2 emissions.
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Zhang, Junjie, Miaomiao Liu, and Bin Zhou. "Analytical Model for Travel Time-Based BPR Function with Demand Fluctuation and Capacity Degradation." Mathematical Problems in Engineering 2019 (November 3, 2019): 1–13. http://dx.doi.org/10.1155/2019/5916479.
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This study presents a stochastic model based on the link performance function of the Bureau of Public Roads to assess the reliability of travel time in the transportation network. Empirical studies have verified that the variability of travel time can be ascribed to demand fluctuation and the degradation of the capacity of the stochastic network. The mean-variance approach in previous research presented the budget model of travel time, with the capacity of the stochastic network and elastic demand as the sources of uncertainty of travel time. Previous research was devoted to the study of estimation of travel time considering a single factor or a factor independent of these two sources. Meanwhile, this study introduces the current degeneration coefficient of capacity (CDC) and the density distribution function of road section saturation (DDFS) with simultaneous network capacity and traffic demand. Sensitivity analysis method for the parameters of the proposed model is investigated theoretically using the sensitivity model of traffic capacity degradation. Results of case analysis show that the DDFS and CDC have an effect on the decision of travelers regarding the choice of route. The empirical analysis also illustrates the effectiveness of the computational approach and the proposed model.
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Yang, Hong, Kaan Ozbay, and Kun Xie. "Improved Travel Time Estimation for Reliable Performance Measure Development for Closed Highways." Transportation Research Record: Journal of the Transportation Research Board 2526, no. 1 (January 2015): 29–38. http://dx.doi.org/10.3141/2526-04.
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Accurate travel time information not only is valuable for travelers but is critical to transportation agencies for quantifying the performance of their systems. Interest has been increasing in the development of reliable approaches for estimating travel time from various sensor data. Unlike the extensively studied estimation approaches based on point sensor measurements, the use of probe data from closed highway systems has been limited. To complement current understanding, this study developed an approach that used probe data from an electronic toll collection (ETC) system on closed freeways to estimate travel time. This approach differs from studies relying on automatic vehicle identification systems deployed on main lines as well as those estimated from point detectors. The proposed approach breaks down individual journey time into section travel time and fuses the probe data from vehicles that have used the links. The results, which are based on real-world case studies, illustrate the potential of mining ETC data for travel time estimation for both incident-free and incident conditions. In addition, the estimated results capture traffic dynamics better than instantaneous travel time estimates based on point sensor data. More accurate information is thus provided for deriving reliable performance measures to depict travel time reliability.
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Elsa Shaji, Hima, Arun K. Tangirala, and Lelitha Vanajakshi. "Evaluation of Clustering Algorithms for the Prediction of Trends in Bus Travel Time." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 45 (August 8, 2018): 242–52. http://dx.doi.org/10.1177/0361198118791365.
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Providing accurate and reliable travel time information to travellers is essential to improve the quality of public transit systems. With the availability of the latest technologies, it has become possible to collect a large amount of traffic data to analyze and understand these systems better. Traffic in India is characterized by lack of lane discipline and the presence of vehicles of varying static and dynamic characteristics, which makes prediction of bus travel time especially challenging. The aim of this study is to identify both a prediction algorithm that can handle high variability and suitable inputs or regressors to be used. Earlier studies performed offline manual grouping considering the patterns observed, which leads to limitations for automated field implementations. The present study explores the use of data-driven approaches, primarily clustering, to address the challenges for the prediction of bus travel time trends. Discrete wavelet transform (DWT) was used to extract trends from the travel time measurements. Three popular clustering algorithms— k-means, hierarchical, and self organizing maps (SOM)—were used to identify patterns. Travel time trends were then predicted by searching for similar cluster patterns within the historical database using pattern sequence-based forecasting (PSF). A comparison of the performance of these algorithms was carried out based on prediction errors. The clustering +prediction framework developed was also compared with the case when no clustering was done on the regressor dataset.
Dissertations / Theses on the topic "Travel time (Traffic engineering) – Vancouver – Case studies"
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Feng, Wei. "Analyses of Bus Travel Time Reliability and Transit Signal Priority at the Stop-To-Stop Segment Level." PDXScholar, 2014. https://pdxscholar.library.pdx.edu/open_access_etds/1832.
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Transit travel time is affected by many factors including traffic signals and traffic condition. Transit agencies have implemented strategies such as transit signal priority (TSP) to reduce transit travel time and improve service reliability. However, due to the lack of empirical data, the joint impact of these factors and improvement strategies on bus travel time has not been studied at the stop-to-stop segment level.
This study utilizes and integrates three databases available along an urban arterial corridor in Portland, Oregon. Data sources include stop-level bus automatic vehicle location (AVL) and automatic passenger count (APC) data provided by the Tri-County Metropolitan Transportation District of Oregon (TriMet), the Sydney Coordinated Adaptive Traffic System (SCATS) signal phase log data, and intersection vehicle count data provided by the City of Portland. Based on the unique collection and integration of these fine granularity empirical data, this research utilizes multiple linear regression models to understand and quantify the joint impact of intersection signal delay, traffic conditions and bus stop location on bus travel time and its variability at stop-to-stop segments. Results indicate that intersection signal delay is the key factor that affects bus travel time variability. The amount of signal delay is nearly linearly associated with intersection red phase duration. Results show that the effect of traffic conditions (volumes) on bus travel time varies significantly by intersection and time of day.
This study also proposed new and useful performance measures for evaluating the effectiveness of TSP systems. Relationships between TSP requests (when buses are late) and TSP phases were studied by comparing TSP phase start and end times with bus arrival times at intersections. Results show that green extension phases were rarely used by buses that requested TSP and that most green extension phases were granted too late. Early green effectiveness (percent of effective early green phases) is much higher than green extension effectiveness. The estimated average bus and passenger time savings from an early green phase are also greater compared to the average time savings from a green extension phase. On average, the estimated delay for vehicles on the side street due to a TSP phase is less than the time saved for buses and automobiles on the major street.
Results from this study can be used to inform cities and transit agencies on how to improve transit operations. Developing appropriate strategies, such as adjusting bus stop consolidation near intersections and optimizing bus operating schedules according to intersection signal timing characteristics, can further reduce bus travel time delay and improve TSP effectiveness.
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黃依凡 and Yee-fang Eva Wong. "A study of the transport needs of patients for medical services, with special emphasis on cost minimization." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2002. http://hub.hku.hk/bib/B42576313.
Full textBooks on the topic "Travel time (Traffic engineering) – Vancouver – Case studies"
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Kropman, J. A. De betekenis van de verplaatsingstijdfactor: Vergelijking van auto- en treinverplaatsingen op de corridor Dordrecht-Rotterdam. Nijmegen: Instituut voor Toegepaste Sociale Wetenschappen, 1993.
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Peter, Schütte Franz, Kreibich Volker, and North Rhine-Westphalia (Germany). Ministerium für Stadtentwicklung und Verkehr., eds. Reisezeitverkürzung im öffentlichen Personennahverkehr. Dortmund: Institut für Landes- und Stadtentwicklungsforschung des Landes Nordrhein-Westfalen, 1991.
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K, Edara Praveen, Guo Jianhua, Smith Brian L. 1967-, McGhee Catherine C, Virginia Transportation Research Council, and Virginia. Dept. of Transportation., eds. Optimal placement of point detectors on Virginia's freeways: Case studies of Northern Virginia and Richmond. Charlottesville, Va: Virginia Transportation Research Council, 2008.
Find full textConference papers on the topic "Travel time (Traffic engineering) – Vancouver – Case studies"
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Layton, Bradley, Lauren Jablonowski, Ryan Kirby, and Nicholas Lampe. "Bicycle Infrastructure Development Strategy for Suburban Commuting." In ASME 2007 International Mechanical Engineering Congress and Exposition. ASMEDC, 2007. http://dx.doi.org/10.1115/imece2007-42233.
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We present a “Bicycle Highway” transportation alternative to automobile commuting by exploring avenues for reducing perceived impediments to bicycle commuting. The three primary goals of the project are: 1) Address the American diabetes and obesity epidemics by making exercising on a daily basis a more desirable and viable alternative. 2) Address the problem of greenhouse gas emissions and pollutants by partially replacing combustion engines with human-powered transportation. 3) Address the problem of the United States’ dependence on foreign oil by diminishing energy demand for short-range transportation. The primary variables we will consider are N, the number of people being transported, d, the distance being traveled, C, the energy cost required to travel the distance, and t, the time required to travel the distance. The Bicycle Highway was found to have a poorer throughput rating when only construction costs were considered, but a better throughput rating when vehicle and fuel costs are introduced. The Bicycle Highway offers a timely and economical solution to the numerous side-effects of the century-long success of the gasoline-powered automobile. A transportation corridor that is designated solely for bicyclists, human-electric hybrid and zero-emission vehicles, would allow for a greater volume of commuter traffic with minimal energetic and entropic impact. This proposed roadway promises to make bicycle travel much safer and will alleviate frustration felt by motorists sharing the road with bicycles. We expect cost-effectiveness of our design to be enhanced further if reductions in obesity, asthma, and lung-disease related costs are considered in future case studies.