Academic literature on the topic 'Hourly Traffic Volume'
Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles
Consult the lists of relevant articles, books, theses, conference reports, and other scholarly sources on the topic 'Hourly Traffic Volume.'
Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.
You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.
Journal articles on the topic "Hourly Traffic Volume"
1
Sharma, Satish C., Jin Y. Oh, and Jon J. Wyatt. "Estimation of design hourly volume from seasonal traffic counts." Canadian Journal of Civil Engineering 14, no. 6 (December 1, 1987): 728–31. http://dx.doi.org/10.1139/l87-110.
Full textAbstract:
By considering the thirtieth highest hourly volume (30HV) as the design hour volume, this study reexamines a commonly used method of predicting the 30HV as a function of the annual average daily traffice (AADT) volume. Based on Alberta's highway system data, some common limitations of the traditional 30HV–AADT model are pointed out. Also included in the analysis presented is a proposed alternative model which utilizes July/August traffic data to estimate the design hour volume. The alternative model appears to provide more accurate prediction results and it also eliminates the need of subjectively classifying the roads into various groups as required by the 30HV–AADT method. Key words: annual average daily traffice, design hour volume, highway design, road classification, traffic volume counts, transportation.
2
Oh, Ju Sam, Tae Young Heo, and Jin Ki Eom. "Hourly traffic volume estimation: radio frequency identification application." World Review of Intermodal Transportation Research 2, no. 2/3 (2009): 187. http://dx.doi.org/10.1504/writr.2009.023306.
Full text
3
Shafique, Muhammad Awais. "Imputing Missing Data in Hourly Traffic Counts." Sensors 22, no. 24 (December 15, 2022): 9876. http://dx.doi.org/10.3390/s22249876.
Full textAbstract:
Hourly traffic volumes, collected by automatic traffic recorders (ATRs), are of paramount importance since they are used to calculate average annual daily traffic (AADT) and design hourly volume (DHV). Hence, it is necessary to ensure the quality of the collected data. Unfortunately, ATRs malfunction occasionally, resulting in missing data, as well as unreliable counts. This naturally has an impact on the accuracy of the key parameters derived from the hourly counts. This study aims to solve this problem. ATR data from New South Wales, Australia was screened for irregularities and invalid entries. A total of 25% of the reliable data was randomly selected to test thirteen different imputation methods. Two scenarios for data omission, i.e., 25% and 100%, were analyzed. Results indicated that missForest outperformed other imputation methods; hence, it was used to impute the actual missing data to complete the dataset. AADT values were calculated from both original counts before imputation and completed counts after imputation. AADT values from imputed data were slightly higher. The average daily volumes when plotted validated the quality of imputed data, as the annual trends demonstrated a relatively better fit.
4
Kim, Seong Ho, Won Ho Suh, and Jun Gin Kim. "Airport Access Road Traffic Demand Estimation." Applied Mechanics and Materials 764-765 (May 2015): 1356–60. http://dx.doi.org/10.4028/www.scientific.net/amm.764-765.1356.
Full textAbstract:
For most traffic engineering studies, traffic flows are usually analyzed and evaluated on hourly basis. However few studies have been performed that estimate the number of traffic volumes made to an airport as a function of air passengers by time of day. The objective of this paper is to develop a mathematical model which forecasts hourly traffic volume by using hourly airport operation data along with airport user characteristics data. An analytical model was developed. This model can be used to (1) predict the number of vehicles queued at airport entrances intersection or toll plaza, (2) predict optimum toll lane staffing, and (3) analyze the level of congestion on the roadway for different levels of air passenger demand in future.
5
Khan, Zadid, Sakib Mahmud Khan, Kakan Dey, and Mashrur Chowdhury. "Development and Evaluation of Recurrent Neural Network-Based Models for Hourly Traffic Volume and Annual Average Daily Traffic Prediction." Transportation Research Record: Journal of the Transportation Research Board 2673, no. 7 (June 2, 2019): 489–503. http://dx.doi.org/10.1177/0361198119849059.
Full textAbstract:
The prediction of high-resolution hourly traffic volumes of a given roadway is essential for transportation planning. Traditionally, automatic traffic recorders (ATR) are used to collect these hourly volume data. These large datasets are time-series data characterized by long-term temporal dependencies and missing values. Regarding the temporal dependencies, all roadways are characterized by seasonal variations that can be weekly, monthly or yearly, depending on the cause of the variation. Traditional time-series forecasting models perform poorly when they encounter missing data in the dataset. To address this limitation, robust, recurrent neural network (RNN)-based, multi-step-ahead forecasting models are developed for time-series in this study. The simple RNN, the gated recurrent unit (GRU) and the long short-term memory (LSTM) units are used to develop the forecasting models and evaluate their performance. Two approaches are used to address the missing value issue: masking and imputation, in conjunction with the RNN models. Six different imputation algorithms are then used to identify the best model. The analysis indicates that the LSTM model performs better than simple RNN and GRU models, and imputation performs better than masking to predict future traffic volume. Based on analysis using 92 ATRs, the LSTM-Median model is deemed the best model in all scenarios for hourly traffic volume and annual average daily traffic (AADT) prediction, with an average root mean squared error (RMSE) of 274 and mean absolute percentage error (MAPE) of 18.91% for hourly traffic volume prediction and average RMSE of 824 and MAPE of 2.10% for AADT prediction.
6
Capparuccini, David Mario, Ardeshir Faghri, Abishai Polus, and Robert E. Suarez. "Fluctuation and Seasonality of Hourly Traffic and Accuracy of Design Hourly Volume Estimates." Transportation Research Record: Journal of the Transportation Research Board 2049, no. 1 (January 2008): 63–70. http://dx.doi.org/10.3141/2049-08.
Full text
7
Liu, Zhaobin, and Satish Sharma. "Predicting Directional Design Hourly Volume from Statutory Holiday Traffic." Transportation Research Record: Journal of the Transportation Research Board 1968, no. 1 (January 2006): 30–39. http://dx.doi.org/10.1177/0361198106196800104.
Full text
8
Zhou, Min, and Virginia P. Sisiopiku. "Relationship Between Volume-to-Capacity Ratios and Accident Rates." Transportation Research Record: Journal of the Transportation Research Board 1581, no. 1 (January 1997): 47–52. http://dx.doi.org/10.3141/1581-06.
Full textAbstract:
The general relationships between hourly accident rates and hourly traffic volume/capacity ( v/c) ratios were examined. A 26 km (16 mi) segment of Interstate I-94 in the Detroit area was selected as the study segment. The v/c ratios were calculated from average hourly traffic volume counts collected in 1993 and 1994 from three permanent count stations. Accident rates were derived from hourly distributed number of accidents in the same 2 years. The correlation between v/c values and accident rates follows a general U-shaped pattern. The study of all observed accidents combined indicates that accident rates are highest in the very low hourly v/c range, decrease rapidly with increasing v/c ratio, and then gradually increase as the v/c ratio continues to increase. U-shaped models also explain the relationship between v/c and accident rates for weekdays and weekend days, multivehicle, rear-end, and property-damage-only accidents. On the other hand, single-vehicle, fixed-object, and turnover accidents, and accidents involving injury and fatality follow a generally decreasing trend with increasing v/c ratio. Traffic conflict is viewed as a major contributing factor to high accident rates observed in the high v/c range, whereas night conditions and driver inattention were identified as explanatory factors for the occurrence of high accident rates in the low v/c ranges.
9
Ma, Fangchen, Jinliang Xu, Chao Gao, and Yufeng Bi. "Study on the Distribution of the Suburban Expressway Hourly Traffic Volume and Modification of the Design Hourly Volume under the Background of the Tourism Economy—Analysis on Design Factors of Normalized Congestion in Suburban Expressway." Sustainability 14, no. 17 (August 29, 2022): 10775. http://dx.doi.org/10.3390/su141710775.
Full textAbstract:
An unreasonable design hourly volume (DHV) greatly impacts road facility construction costs and traffic efficiency. With the rapid rise in the tourism economy and widespread emergence of holiday travel characteristics in China, DHV applicability for suburban expressways requires verification. This study collected annual traffic volume data over 8760 h along Xi’an Ring Expressway from 2017 to 2019. Traffic demand distribution patterns throughout the year and peak hours were analyzed on the basis of the descending order of the obtained hourly traffic volume (HV) and factor data. HV distribution characteristics, 30th highest hourly volume (30 HV) typicality, and DHV factor applicability were investigated. Due to travel characteristics under the background of the tourism economy, the peak HV distribution exhibits polarization characteristics. The recommended value of the design hour traffic factor in the specification corresponded to a number of hours greater than 200, with the 30 HV factor under the background of the tourism economy being 25% higher than the recommended value. Considering the tourism economy, the high level of traffic operation time increased significantly, and the characteristics of a sharp decline in the peak HV disappeared. The 30 HV factor no longer exhibited traditional characteristics. The design causes of traffic congestion are identified herein.
10
Sekuła, Przemysław, Zachary Vander Laan, Kaveh Farokhi Sadabadi, Krzysztof Kania, and Sara Zahedian. "Transferability of a Machine Learning-Based Model of Hourly Traffic Volume Estimation—Florida and New Hampshire Case Study." Journal of Advanced Transportation 2021 (November 26, 2021): 1–15. http://dx.doi.org/10.1155/2021/9944918.
Full textAbstract:
This paper focuses on the problem of model transferability for machine learning models used to estimate hourly traffic volumes. The presented findings enable not only an increase in the accuracy of existing models but also, simultaneously, reduce the cost of data needed for training the models—making statewide traffic volume estimation more economically feasible. Previous research indicates that machine learning volume estimation models that leverage GPS probe data can provide transportation agencies with accurate estimates of hourly traffic volumes—which are fundamental for both operational and planning purposes—and do so with a higher level of accuracy than the prevailing profiling method. However, this approach requires a large dataset for model calibration (i.e., input and continuous count station data), which involves significant monetary investment and data-processing effort. This paper proposes solutions, which allow the model to be prepared using a much smaller dataset, given that a previously collected dataset, which may be gathered in a different place and time period, exists. Based on a broad selection of experiments, the results indicate that the proposed approach is capable of achieving similar model performance while collecting data for a 5 times shorter time period and utilizing 1/4 of the number of continuous count stations. These findings will help reduce the cost of preparing and maintaining the traffic volume models and render the traffic volume estimations more financially appealing.
Dissertations / Theses on the topic "Hourly Traffic Volume"
1
Shrestha, Sajan. "SENSITIVITY OF QUEUE ESTIMATES TO THE SIZE OF THE TIME INTERVAL USED TO AGGREGATE TRAFFIC VOLUME DATA." Cleveland State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=csu1431087335.
Full text
2
Campomanes, Campomanes Alfredo Jorge, and Olivera Joel Moisés López. "Reducción de la congestión vehicular a través de la implementación de la Ola Verde en la Av. Caminos del Inca en el tramo comprendido entre Jr. Batallón Callao Norte y Jr. Cádiz en el distrito de Surco." Bachelor's thesis, Universidad Peruana de Ciencias Aplicadas (UPC), 2019. http://hdl.handle.net/10757/626381.
Full textAbstract:
El congestionamiento vehicular es uno de los problemas que más se agudiza en la ciudad de Lima. Este problema se ve reflejada en casi todas las calles y avenidas principales de la ciudad, debido a factores como el incremento del parque automotor que hacen colapsar la capacidad de la infraestructura y dejan en desuso la gestión de tránsito para la que fue diseñada; dicho de otra manera, el incremento del flujo vehicular ocasiona gran congestión, largas colas, prolongadas demoras y niveles de servicio deficientes. La zona de estudio a tratar se encuentra en el distrito de Surco y la vía intervenida es la avenida Caminos del Inca en el tramo del jirón Batallón Callao hasta el jirón Cádiz atravesando avenidas importantes como Velazco Astete e Higuereta. Esta avenida es una de las más transitadas del distrito de Surco a causa de los centros comerciales, institutos, universidades, entre otros, que se encuentran cercanas a esta importante arteria vial.
Por ello, este trabajo de tesis tiene como objetivo principal disminuir la congestión vehicular de la Av. Caminos del Inca en el tramo de estudio y mejorar los niveles de servicio en sus intersecciones con la implementación de la ola verde a través del modelamiento y simulación en el software Synchro 8.
Para la elaboración de este trabajo se recopilaron datos de campo como el aforo vehicular para determinar la hora punta y el volumen horario de máxima demanda vehicular, asimismo se realizó la medición de los ciclos semafóricos y sus faces en un día típico de la semana. Con todos estos datos compilados en el trabajo de campo, se obtuvieron los grados de saturación y los niveles de servicio actuales para que posteriormente sean evaluadas a fin de implementar la ola verde y optimizar el tránsito.
Finalmente, con la implementación de la ola verde y las modificaciones de gestión de tráfico se obtuvieron mejoras notables como optimización de los niveles de servicio en las intersecciones, por ejemplo, en la intersección N° 01 pasó de C a B, en la N° 02 de F a D, en la N° 03 de C a B y en la N° 04 de C a B; asimismo, las esperas en las intersecciones disminuyeron favorablemente como se indica a continuación, en la intersección N° 01 Bajó de 20.1s a 16.7s, en la N° 02 de 332.2s a 35.3s, en la N° 03 de 239.9s a 11.4s y en la N° 04 de 37.0s a 6.3s; de igual forma, el tiempo de recorrido de un punto extremo, intersección N° 01, al otro, Intersección N° 04, mejoró considerablemente de 6 minutos y 30 segundos aproximadamente a 1 minuto y 28 |segundos debido a la sincronización progresiva del color verde de los semáforos en cada intersección.Traffic congestion is one of the most acute problems in the city of Lima. This problem is reflected in almost all the streets and main avenues of the city, due to factors such as the increase in the vehicle fleet that collapses the capacity of the road infrastructure and leaves the traffic management for which it was designed in disuse; In other words, the increase in the flow of vehicles causes great congestion, long queues of vehicles, prolonged delays and poor service levels. The study area to be treated is in the district of Surco and the intervened road is the Caminos del Inca avenue in the stretch from Batallón Callao street to Cádiz street crossing important avenues such as Velazco Astete and Higuereta. This is one of most heavily traveled avenue in the district of Surco because of the shopping centers, institutes, universities, among others, that are close to this important traffic artery. Therefore, this thesis work has as main objective to reduce the vehicular congestion of this avenue and improve the service levels of its intersections with the implementation of the green wave through modeling and simulation in the Synchro 8 software. For the elaboration of this research work, field data were collected, such as the vehicle capacity to determine the peak hour and the hourly volume of maximum vehicular demand, as well as the measurement of the traffic light cycles and their faces in a typical day of the week. With all this data compiled in the field work, saturation degrees and current service levels were obtained so that later they can be evaluated in order to implement the green wave and optimize traffic. Finally, with the implementation of the green wave and traffic management modifications, notable improvements were obtained such as optimization of service levels at intersections, for example, at intersection No. 01 it went from C to B, at No. 02 from F to D, in No. 03 from C to B and in No. 04 from C to B; in the same way, the travel time from an extreme point, intersection No. 01, to the other, Intersection No. 04, improved considerably from 6 minutes and 30 seconds approximately to 1 minute and 28 seconds due to the progressive synchronization of the green colour of the traffic lights in each intersection.
Tesis
Books on the topic "Hourly Traffic Volume"
1
Division, Virginia Traffic Engineering, ed. 1995 24 hour traffic volumes. [Richmond, Va.]: Virginia Dept. of Transportation, Traffic Engineering Division, 1995.
Find full textBook chapters on the topic "Hourly Traffic Volume"
1
Macioszek, Elżbieta. "Relationship between Vehicle Stream in the Circular Roadway of a One-Lane Roundabout and Traffic Volume on the Roundabout at Peak Hour." In Telematics - Support for Transport, 110–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-45317-9_12.
Full textConference papers on the topic "Hourly Traffic Volume"
1
Cook, Mylan R., Kent L. Gee, Mark K. Transtrum, Shane V. Lympany, and Matthew F. Calton. "Toward improving road traffic noise characterization: A reduced-order model for representing hourly traffic volume dynamics." In 181st Meeting of the Acoustical Society of America. ASA, 2021. http://dx.doi.org/10.1121/2.0001636.
Full text
2
Mrad, Sonia, and Rafaa Mraihi. "Short Term Prediction of Hourly Traffic Volume Using Neural Network in Interurban Freeway." In 2019 International Colloquium on Logistics and Supply Chain Management (LOGISTIQUA). IEEE, 2019. http://dx.doi.org/10.1109/logistiqua.2019.8907310.
Full text
3
Lovrić, Ivan, Boris Čutura, Tiziana Campisi, Antonino Canale, and Marko Renčelj. "Dependence of design hourly volume on the function and nature of traffic demand of rural roads." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.1320.
Full textAbstract:
In the first phases of study and design documentation of rural roads, one of the key parameters to determine in the analyses is the Design Hourly Volume (DHV). The required level of service and the feasibility of the project depend to a large extent on a properly established DHV. Essentially, the problem is to determine the value of the K-factor for a certain nth highest hour of the year. This paper points to the need for additional analysis of existing databases of long-term automatic traffic counting, from which the necessary guidance for planners and designers can be derived, enabling them to understand and apply the K-factors in a clearer and more detailed way. Using specific data examples, characteristic sections of rural roads with different functions and types (seasonal variations) of traffic demand were selected to show significant differences in the values of the K-factors for the same selected nth highest hour of the year. Several guidelines (BiH, Slovenia, Croatia, Italy, Serbia) were analysed beforehand to get a better understanding of how the K-factor or DHV is explained and used in different countries. The main objective of the article is to show that, on the basis of the existing databases of continuous automatic counting in these countries, with additional analyses presented in this paper or in a similar form, significant regularities in determining the DHV can be achieved, eliminating difficulties of application in engineering practice. As all guidelines practically recommend the use of HCM in capacity analyses, specific examples are selected to show the difference between the definition of HCM for a route with dominant recreational traffic and our route with dominant tourist traffic (recreational versus tourist).
4
Mohammad, Anas Ahmad, Deepti Muley, Mohammad Shareef Ghanim, and Mohamed Bin Mokhtar Kharbeche. "COVID-19 Preventive Measures & their Impact on Traffic Demand & Safety." In Qatar University Annual Research Forum & Exhibition. Qatar University Press, 2020. http://dx.doi.org/10.29117/quarfe.2020.0302.
Full textAbstract:
COVID-19 has affected the mobility of people significantly due to movement restrictions imposed by government authorities to control the spread of the pandemic. The staged movement restrictions that have been implemented by the government authorities to curb the spread of the disease included the closure of educational institutions and adopt online-based education, restrict commercial activities, and reducing the number of employees at the workplace. This paper presents the impact of these mitigation policies on the traffic volumes, the number of traffic violations, and the number of crashes in the State of Qatar. The hourly distribution of traffic volume showed similar trends before and after the implementation of these policies. Overall, the total traffic decreased by 30% compared to baseline conditions for all selected intersections as well as the Central Business District (CBD) screenline after the implementation of all measures. From the safety perspective, the total traffic violations decreased by 73% in April and May when the restrictions due to all three policies were imposed. During the same time, a decrease of 42% to 54%, 20% to 54%, and around 36% was observed for traffic crashes involving deaths, major loss, and minor damages respectively. Similarly, the total traffic crashes declined by 37% when complete restrictions were in place and COVID-19 was in peak stage. The results of this study will help policymakers and planners to plan/manage the traffic operations in the future during any emergencies. The results can be applied also while managing traffic during the post-Covid era, special and mega-events for temporary traffic management based on real-life data.
5
RADZISZEWSKI, L. "Analysis of Urban Traffic Noise at Weekends – Case Study." In Terotechnology XII. Materials Research Forum LLC, 2022. http://dx.doi.org/10.21741/9781644902059-43.
Full textAbstract:
Abstract. The study carried out an analysis of the urban traffic noise parameters on Sundays and Saturdays. The results of noise simulations according to the Cnossos-EU model were compared with the sound level calculated by a permanent automatic sound and traffic volume monitoring station. The variations in results were evaluated. Analyzes carried out showed that the traffic of passenger vehicles is the main source of road noise. A very good agreement of the noise values determined according to the Cnossos-EU model and the measured ones was obtained. The maximum noise values on Sundays are only slightly smaller than on Saturdays. The shape of the noise diagram and the noise values at individual hours of the day on Saturdays are different than on Sundays. An experimental model of noise variability at weekends has been proposed. The equations describing the variability of the equivalent sound level were validated. Fit factor R2 of the proposed equations to the experimental data ranges from 0.85 to 0.94.
6
Cvitanić, Dražen, and Biljana Maljković. "The impact of different saturation headway values on intersection capacity." In 6th International Conference on Road and Rail Infrastructure. University of Zagreb Faculty of Civil Engineering, 2021. http://dx.doi.org/10.5592/co/cetra.2020.996.
Full textAbstract:
Elements of the city road network that determine its capacity are signalized intersections. Their capacity depends of many factors: traffic volume and distribution, traffic flow structure, signal timing, and number of bicyclists and pedestrians. However, the starting parameter for calculation of intersection capacity is saturation headway. This research explores the influence of weather conditions and purpose of trip on saturation headway. Saturation headways were determined on few intersections in the morning peak hour of working and weekend day, in good and bad weather conditions. The impact of different trip purposes and different weather conditions on intersection capacity is analysed, as well as the influence of using mean and median values of saturation headway when calculating the intersection capacity.
7
"Experimental Research on the Bearing Capacity of the Widening Segment of Precast Small Box Girder." In Structural Health Monitoring. Materials Research Forum LLC, 2021. http://dx.doi.org/10.21741/9781644901311-37.
Full textAbstract:
Abstract: Widening the existing expressway is an important way to solve the problems like road traffic congestion and level of service declining in the existing highway network. Besides, for the highway with large traffic volume and lack of detour roads, it is inevitable to open to traffic at the same time of construction. Taking a 20 m precast small box girder bridge widening project as the research object, the ABAQUS finite element entity model of the whole bridge and full-scale segment experiment is established, and the boundary conditions and loading force values of the segment model are determined by the similarity analysis. The numerical simulation calculation of the deflection difference between both sides of the joint and the joint reinforcement strain of the full-scale segment test model is performed, and results are compared with the experimental measured values, so as to verify the rationality of the finite element model. Moreover, this research further studies the shear transfer mechanism and bearing capacity of concrete joints with the finite element calculation, and the force-displacement curve of concrete joint loading in whole process is calculated. According to results, the early strength of concrete develops rapidly, while the deflection difference on both sides of the joint drops rapidly, and the deflection difference basically remains unchanged after 8 hours of casting. The shear transfer of joint concrete in the overall analysis model and section test model develops rapidly in the early stage, since then tends to be stable gradually. Results of the bearing capacity test describe that when the bottom reinforcement of the joint reaches the tensile strength and the deflection of the joint increases rapidly, the ultimate bearing capacity could be reached, and the most unfavorable part of the test joint could bear 17 times of 55t wheel load. It is demonstrated that the traffic control scheme of closing and widening the joint adjacent to the lane in the first three days could ensure the reliable casting performance of the concrete joint when the traffic is not interrupted. The research results would provide technical guidance for the design and construction of the same type of bridge.
8
Galinskaitė, Lina, Gytautas Ignatavičius, and Vaidotas Valskys. "DEPENDENCE OF VEHICLE COLLISIONS WITH ROE DEER ON SPATIAL AND TEMPORAL FACTORS IN LITHUANIA." In 11th International Conference “Environmental Engineering”. VGTU Technika, 2020. http://dx.doi.org/10.3846/enviro.2020.651.
Full textAbstract:
Rising road densities, vehicle speeds limits and traffic volumes, combined with recent growth in the population density of various deer species, have increased the risk of DVCs across the world, causing a great deal of animal suffering, traffic safety problems and socio-economic costs. Object of this investigation was to find out collisions trend with roe deer (Capreolus capreolus) in Lithuania. The aim of our study was to determine where in Lithuania accidents occure more frequently and evaluate these accidents in time. In 2013–2017 number of AVCs in Lithuania was recorded more then 12 011 times, over half of 7155 occur with roe deer. The temporality of accidents was studied under three scales – daily, weekly and seasonal. Daily peaks start at 7:00 (8.75%), 8:00 (6.08%). Evening peaks, start at 17:00 (7.71%), other at 22:00 (10.64%) hours. Week collisions with roe deer increase on Friday 14.9%. The risk of collision with roe deer varies over the year – the majority of crashes occur in May 14.7% and November 10.7%. In spatial study localization of collision data with ArcGIS 10.3. It was found that road surrounding landscape dominated by agricultural land collisions occurred at a maximum of 29.77%. 19.10% collisions were recorded in the forest area. In built-up areas 11.85%. Analysis of these trends allow to simulate and predict when and where the highest risk of DVCs occurs. In conclusion, this could give valuable information and constitute a manageable tool for the road managers, planners, scientist, wildlife conservationist who are interested in these type of accidents in regions of Lithuania.
9
Carroll, Ernest A., and Dan B. Rathbone. "Using an Unmanned Airborne Data Acquisition System (ADAS) for Traffic Surveillance, Monitoring, and Management." In ASME 2002 International Mechanical Engineering Congress and Exposition. ASMEDC, 2002. http://dx.doi.org/10.1115/imece2002-32916.
Full textAbstract:
This paper presents the history of and current status of a U.S. DOT and NASA sponsored program designed to demonstrate the feasibility of using a small-unmanned airborne data acquisition system (ADAS) for traffic surveillance, monitoring, and management. ADAS is ideally suited for application in monitoring traffic flow, traffic congestion, and supporting ITS assets. GeoData Systems (GDS), Inc., with principal offices at 10565 Lee Highway, Suite 100, Fairfax, VA 22030 has developed a revolutionary new class of airborne data acquisition systems. In this effort, GDS has teamed with traffic experts DBR & Associates; P.O. Box 12300 Burke, VA. The GDS ADAS has a gross takeoff weight of less than 55 lbs, which includes both the airframe and sensors. It is capable of sustained flight for periods in excess of two hours while carrying a sensor payload of up to 20 lbs. ADAS has nine interchangeable sensor platforms under development to include a hyper-spectral visible-near-IR sensor, a multi-spectral visible near-IR mid-IR sensor, a synthetic aperture radar (SAR) sensor, and a highly flexible high-resolution real-time video sensor. The GDS high-resolution real-time video sensor is ideally suited for traffic monitoring and other highway monitoring applications. The ADAS platform is capable of flying under a combination of pre-programmed Differential Global Positioning Satellite (DGPS) based navigation and manual direct ground control. The ADAS is being fully tested and is planned for use in several DOD base-monitoring studies this year. It should be noted that the ADAS has several levels of backup systems, which allows for a safe descent to the ground via parachute in a worst-case scenario. The system and any liability resulting from its use are fully insured by a major provider. The use of ADAS in traffic surveillance, monitoring, and management is unique and, as far as can be ascertained, has not been used in an official capacity in this way. Because of its ability to collect traffic data, survey traffic conditions, and collect highway inventory and environmental data in a cost-effective manner, and because every metropolitan area needs to collect at least some traffic data, the potential payoff from applying the ADAS is significant. The estimated potential payoff resulting from the use of the ADAS was calculated by taking into consideration information from a recent study conducted for the Federal Highway Administration by the Volpe National Transportation Systems Center1. Using a reported average amount of funds expended annually for traffic data collection by transportation agencies in metropolitan areas with a population of over 200,000 and taking into consideration the estimated budget for staff involved in data collection, it is calculated that transportation agencies in an average metropolitan area spend approximately $5 million per year in traffic data collection. The ADAS can play a cost-saving role in about half of all data collection procedures and can reduce the total cost by 20 percent. Nationally, this could produce an annual savings of $75 million. An additional area where the ADAS can play a useful role is in incident management. It is well documented that more than half of the traffic congestion in the U.S. is caused by incidents, and the problem is getting worse: The percentage of congestion due to incidents is estimated to increase to 70 percent by the year 20053. The Federal Highway Administration further estimates that incident-related traffic congestion will cost the U.S. more than $75 billion in the year 2005, mainly due to lost time and wasted fuel. Comprehensive, accurate surveillance of major incidents will result in a more effective overall response. It can facilitate the process of completing police documentation of incidents, which further reduce their duration. A recent study4 showed that a 23-minute reduction in average incident duration in the Atlanta area saved $45 million in one year. The ADAS is able to provide real time overhead video feeds of an incident and the surrounding traffic situation. In addition, the ADAS can record the incident on video, capturing especially those incidents that are not within the visibility range of any CCTV system, therefore reducing the recording burden of police officers. The valuable role that airborne real-time video can play has been recognized by transportation agencies: The Virginia Department of Transportation (VDOT) has commented enthusiastically on this approach: “…VDOT definitely supports the use of an Unmanned Airborne Sensor for traffic management during a highway incident.” In addition, the Director of the Center for Advanced Transportation Technology of the University of Maryland also has responded positively, writing that, “A project which evaluates the effectiveness of an unmanned airborne data acquisition system in monitoring traffic flow seems to be a step in the right direction toward identifying appropriate and cost-effective remote sensing applications.” Further, in a recent study conducted by the Virginia Transportation Research Council in cooperation with the Federal Highway Administration, researchers concluded that: “the air video reduces the time and personnel needed to acquire data from the field. Further, aerial video may facilitate an objective evaluation of a jurisdiction’s incident response procedures. Finally, aerial video may allow a transportation agency to adopt a proactive approach to traffic management by identifying and evaluating potential problems before they occur. Specifically, problems include the use of residential neighborhoods to bypass congested arterials and heavily used facilities needing snow removal.” Our project is demonstrating how the ADAS can be used in traffic surveillance monitoring and management. The study team is using input from transportation agencies at the state and local level to fine-tune the design of the ADAS application and the analysis and evaluation of the results. Areas where the ADAS can be applied effectively and efficiently are being identified. When completed, the end product of this effort will be a document that will indicate when it is cost-effective to use ADAS relative to other possible methods of data collection and analysis.
10
Dai, Xiyan, and Lee Yu-Chi. "Investigating preferred listening levels when using noise-canceling headphones among male graduate students." In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001705.
Full textAbstract:
Many pieces of the literature showed that the potential risk of hearing loss was increasing among the general public, especially in adolescents and young adults, caused by prolonged exposure to loud music. Users tended to listen to music with a higher volume in noisy environments (e.g., intersections and subways) than in quiet ones. According to the WHO-ITU standard level for adults (80 dBA for 40 hours a week), the listening habits worse than the recommended standard might cause hearing damage. At present, the increasingly popular Noise-canceling headphones (NCHs) can reduce environmental noise to a certain extent. Whether users would lower the volume of music when using an NCH is a concern of the research. NCHs have different listening modes for dealing with ambient noise. Hence, the primary purpose of this study was to investigate the effect of different NCHs modes on pedestrians’ preferred listening levels (PLLs) in a noisy environment and to evaluate whether their listening levels were in a safe range.Methods: Fifteen male graduate students with normal-hearing ability participated in the study. The independent variable was the modes of NCHs, including Noise Cancellation (NC), Off, and Transparency modes. The PLLs were determined by each participant and recorded as the dependent variable. Before the experiments, participants were asked to report their headphone-use habits for assessing whether they exceeded a safe listening level. During the experiments, the ambient noise of heavy traffic intersections was played through two speakers. Participants were asked to put on the headphone with a specific mode by random orders. Subsequently, each participant was requested to adjust the volume of the music until it “sounded best.” The measurements were repeated twice for the three modes. A one-way repeated measure ANOVA with Bonferroni pairwise comparisons was used for statistical analysis. Results: The results indicated that the headphone modes significantly impacted the PLLs (p<0.001). Based on the Bonferroni pairwise comparisons, participants selected the highest PLLs with the Transparency mode (67.21 dBA), followed by the Off mode (60.77 dBA), and NC mode (55.83 dBA). Besides, the self-reported results showed that the usage of headphones was five days per week and three hours per day on average. From the results, the PLLs selected by the subjects were all lower than 80 dBA, and the average listening time did not exceed 40 hours per week. It implied that the participants' listening habits were at safe listening levels. Conclusion: In a noisy environment, different headphone modes have impacted on PLLs adjustment. The PLLs selected with the NC mode are significantly lower than those with Off mode and Transparency mode. The findings of this study suggested that using NC mode in a noisy environment could reduce the risk of hearing loss compared to the other headphone modes.
Reports on the topic "Hourly Traffic Volume"
1
Tarko, Andrew P., Qiming Guo, and Raul Pineda-Mendez. Using Emerging and Extraordinary Data Sources to Improve Traffic Safety. Purdue University, 2021. http://dx.doi.org/10.5703/1288284317283.
Full textAbstract:
The current safety management program in Indiana uses a method based on aggregate crash data for conditions averaged over several-year periods with consideration of only major roadway features. This approach does not analyze the risk of crashes potentially affected by time-dependent conditions such as traffic control, operations, weather and their interaction with road geometry. With the rapid development of data collection techniques, time-dependent data have emerged, some of which have become available for safety management. This project investigated the feasibility of using emerging and existing data sources to supplement the current safety management practices in Indiana and performed a comprehensive evaluation of the quality of the new data sources and their relevance to traffic safety analysis. In two case studies, time-dependent data were acquired and integrated to estimate their effects on the hourly probability of crash and its severity on two selected types of roads: (1) rural freeways and (2) signalized intersections. The results indicate a considerable connection between hourly traffic volume, average speeds, and weather conditions on the hourly probability of crash and its severity. Although some roadway geometric features were found to affect safety, the lack of turning volume data at intersections led to some counterintuitive results. Improvements have been identified to be implemented in the next phase of the project to eliminate these undesirable results.
2
Cheng, Wen, Yongping Zhang, and Edward Clay. Comprehensive Performance Assessment of Passive Crowdsourcing for Counting Pedestrians and Bikes. Mineta Transportation Institute, February 2022. http://dx.doi.org/10.31979/mti.2022.2025.
Full textAbstract:
Individuals who walk and cycle experience a variety of health and economic benefits while simultaneously benefiting their local environments and communities. It is essential to correctly obtain pedestrian and bicyclist counts for better design and planning of active transportation-related facilities. In recent years, crowdsourcing has seen a rise in popularity due to the multiple advantages relative to traditional methods. Nevertheless, crowdsourced data have been applied in fewer studies, and their reliability and performance relative to other conventional methods are rarely documented. To this end, this research examines the consistency between crowdsourced and traditionally collected count data. Additionally, the research aims to develop the adjustment factor between the crowdsourced and permanent counter data and to estimate the annual average daily traffic (AADT) data based on hourly volume and other predictor variables such as time, day, weather, land use, and facility type. With some caveats, the results demonstrate that the Street Light crowdsourcing count data for pedestrians and bicyclists appear to be a promising alternative to the permanent counters.
3
Day, Christopher M., Hiromal Premachandra, and Darcy M. Bullock. Characterizing the Impacts of Phasing, Environment, and Temporal Factors on Pedestrian Demand at Traffic Signals. Purdue University, 2011. http://dx.doi.org/10.5703/1288284317352.
Full textAbstract:
There is a need for more and higher quality data on pedestrian demand patterns for a number of applications in planning, transportation engineering, public health, and other areas. It is particularly desirable to better characterize the influence of daily, weekly, and annual variations; the impact of weather and special events; and the effects of changes in pedestrian phasing. This paper proposes and demonstrates a methodology for quantifying the relative demand for pedestrian service at a signalized intersection by using the percent of signal cycles per hour in which the pedestrian phase was actuated. Although this performance measure does not by itself provide a pedestrian count, it can be used as a surrogate to characterize how pedestrian volumes vary due to operating conditions. More importantly, since this technique does not require new sensors, the data can be collected at thousands of intersections across the nation where pedestrian push buttons are in use. This paper documents findings from over a year of data collection at a signalized intersection on a college campus. The effects of daily/weekly/annual variations, special events, weather (temperature and precipitation), seasonal changes in activity patterns, and changes in pedestrian signal phasing are documented. A Tobit model is used to account for the influences of these variables and understand how they co-influence pedestrian activity. The implementation of an exclusive pedestrian phase is associated with a 9% increase in pedestrian phase utilization at the intersection. This change is associated with a decrease in user cost relative to performing midblock crossings. The modeled impact of snowfall events adds further insight by showing that as the user cost of making midblock crossings increases, pedestrian activity at the intersection increases.