Evaluation of the impact of traffic volume on site ranking

2017 ◽  
Vol 10 (5) ◽  
pp. 491-505 ◽  
Author(s):  
Wen Cheng ◽  
Gurdiljot Singh Gill ◽  
Luis Loera ◽  
Xiaofei Wang ◽  
Jung-Han Wang
Keyword(s):  
Traffic Volume ◽  
The Impact ◽  
Site Ranking

scholarly journals Extracting Road Traffic Volume in the City before and during covid-19 through Video Remote Sensing

2021 ◽  
Vol 13 (12) ◽  
pp. 2329
Author(s):  
Elżbieta Macioszek ◽  
Agata Kurek
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Road Traffic ◽  
Traffic Volume ◽  
The Road ◽  
Traffic Characteristics ◽  
Annual Average Daily Traffic ◽  
On The Road ◽  
The Impact ◽  
The City

Continuous, automatic measurements of road traffic volume allow the obtaining of information on daily, weekly or seasonal fluctuations in road traffic volume. They are the basis for calculating the annual average daily traffic volume, obtaining information about the relevant traffic volume, or calculating indicators for converting traffic volume from short-term measurements to average daily traffic volume. The covid-19 pandemic has contributed to extensive social and economic anomalies worldwide. In addition to the health consequences, the impact on travel behavior on the transport network was also sudden, extensive, and unpredictable. Changes in the transport behavior resulted in different values of traffic volume on the road and street network than before. The article presents road traffic volume analysis in the city before and during the restrictions related to covid-19. Selected traffic characteristics were compared for 2019 and 2020. This analysis made it possible to characterize the daily, weekly and annual variability of traffic volume in 2019 and 2020. Moreover, the article attempts to estimate daily traffic patterns at particular stages of the pandemic. These types of patterns were also constructed for the weeks in 2019 corresponding to these stages of the pandemic. Daily traffic volume distributions in 2020 were compared with the corresponding ones in 2019. The obtained results may be useful in terms of planning operational and strategic activities in the field of traffic management in the city and management in subsequent stages of a pandemic or subsequent pandemics.

Predicting of atmospheric corrosivity and durability of structural materials. Part II. Impact of urban traffic pollution

2021 ◽  
Vol 26 (2) ◽  
pp. 25-33
Author(s):  
Joanna Kobus ◽  
Rafał Lutze
Keyword(s):  
Zinc Coating ◽  
Environmental Parameters ◽  
Structural Materials ◽  
Traffic Volume ◽  
Urban Traffic ◽  
Traffic Pollution ◽  
Street Traffic ◽  
The Impact

The results of the atmospheric corrosivity assessment in the immediate vicinity of streets of different traffic volume in Warsaw, Krakow and Katowice are derived . On the bases of annual exposures in 2014–2018 years an equation describing the impact of environmental parameters and street traffic volume on corrosion losses of zinc and zinc coating on steel was selected.

The impact of snowfall on crashes, traffic volume, and revenue on the New York State Thruway

2021 ◽  
Author(s):  
David A. Call ◽  
Guy A. Flynt
Keyword(s):  
New York ◽  
New York State ◽  
Traffic Volume ◽  
Crash Risk ◽  
York State ◽  
Inclement Weather ◽  
Daily Data ◽  
Fatal Crashes ◽  
Traffic Volumes ◽  
The Impact

AbstractSnow has numerous effects on traffic, including reduced traffic volumes, greater crash risk, and increased travel times. This research examines how snow affects crash risk, traffic volume, and toll revenue on the New York State Thruway. Daily data from January for a ten-year period (2010-2019) were analyzed for the Thruway from the Pennsylvania state line in western New York to Syracuse.Anywhere from 35-50 percent of crashes are associated with inclement weather, with smaller impacts, proportionally, in areas with greater traffic volumes. As expected, snow was almost always involved when weather was a factor. “Unsafe speed” was the most common cause of crashes in inclement weather with all other factors (e.g., animals, drowsiness) much less likely to play a role. The percentage of crashes resulting in an injury did not change significantly with inclement conditions when compared to crashes occurring in fair conditions, and there were too few fatal crashes to make any inferences about them.Daily snowfall rates predicted about 30 percent of the variation in crash numbers, with every 5.1 cm of snowfall resulting in an additional crash, except in Buffalo where 5.1 cm of snow resulted in an additional 2.6 crashes. Confirming earlier results, daily snowfall had a large impact on passenger vehicle counts while commercial vehicle counts were less affected. Revenue data showed a similar pattern, with passenger revenue typically decreasing by 3-5 percent per 2.5 cm of snow, while commercial revenue decreases were 1-4 percent per 2.5 cm of snow.

scholarly journals The Impact of Emergency Parking Bays on Quasi-Eight-Lane Expressway Traffic Operations

2020 ◽  
Vol 12 (8) ◽  
pp. 3432
Author(s):  
Zhen Yang ◽  
Xiaocan Chen ◽  
Dazhi Sun
Keyword(s):  
High Volume ◽  
Traffic Volume ◽  
Simulation Software ◽  
Traffic Operations ◽  
Microscopic Simulation ◽  
Lane Changing ◽  
Traffic Demand ◽  
The Road ◽  
Traffic Operation ◽  
The Impact

Recently, with the discrepancy between increasing traffic demand and limited land resources, more and more expressways are choosing to use hard shoulders to expand into quasi-six-lane or quasi-eight-lane roads. Therefore, more emergency parking bays are used in place of traditional parking belts. However, there are no standards defining clear and unified specifications for the design of parking bays. This paper aimed to investigate the impact of emergency parking bays on expressway traffic operations with various traffic volumes and setting conditions. Based on the Monte Carlo method, VISSIM (Verkehr in Städten Simulation, a microscopic simulation software) simulation experiments were conducted using measured traffic operation data from one expressway in Zhejiang province. The probability of unsafe deceleration, lane-changing maneuvers and delay times were considered as the safety and efficiency indexes in this simulation study. The simulation results indicated that the emergency parking vehicle had an increasing impact on the following vehicle as the traffic volume increased. However, the impact pattern was found to be insensitive to the changing of the bay taper length. For low traffic volume, compared with the arrival vehicle, the departure vehicle had more impact on the traffic operation of the mainline. However, the impact of the arrival vehicle became more remarkable as the traffic volume increased. After parking, the waiting time for merging into the mainline was reduced as the volume decreased or as the bay taper increased. Furthermore, reductions caused by varying bay tapers were more significant under high volume conditions. Finally, this study suggests that parking bays are inapplicable when the occupancy of the road space exceeds 20% (about 3000 veh/h), because they would cause significant impact on the safety and efficiency of the expressway. The results of this paper are useful for the design and implementation of emergency parking bays.

scholarly journals CONGESTION EFFECTS OF AUTONOMOUS TAXI FLEETS

Transport ◽  
2018 ◽  
Vol 33 (4) ◽  
pp. 971-980 ◽  
Author(s):  
Michal Maciejewski ◽  
Joschka Bischoff
Keyword(s):  
Traffic Congestion ◽  
Autonomous Vehicles ◽  
Large Scale ◽  
Traffic Volume ◽  
City Centre ◽  
Conventional Vehicle ◽  
Road Capacity ◽  
Private Car ◽  
The One ◽  
The Impact

Fleets of shared Autonomous Vehicles (AVs) could replace private cars by providing a taxi-like service but at a cost similar to driving a private car. On the one hand, large Autonomous Taxi (AT) fleets may result in increased road capacity and lower demand for parking spaces. On the other hand, an increase in vehicle trips is very likely, as travelling becomes more convenient and affordable, and additionally, ATs need to drive unoccupied between requests. This study evaluates the impact of a city-wide introduction of ATs on traffic congestion. The analysis is based on a multi-agent transport simulation (MATSim) of Berlin (Germany) and the neighbouring Brandenburg area. The central focus is on precise simulation of both real-time AT operation and mixed autonomous/conventional vehicle traffic flow. Different ratios of replacing private car trips with AT trips are used to estimate the possible effects at different stages of introducing such services. The obtained results suggest that large fleets operating in cities may have a positive effect on traffic if road capacity increases according to current predictions. ATs will practically eliminate traffic congestion, even in the city centre, despite the increase in traffic volume. However, given no flow capacity improvement, such services cannot be introduced on a large scale, since the induced additional traffic volume will intensify today’s congestion.

scholarly journals Exploring the Influence of Truck Proportion on Freeway Traffic Safety Using Adaptive Network-Based Fuzzy Inference System

2019 ◽  
Vol 2019 ◽  
pp. 1-13 ◽  
Author(s):  
Shiwen Zhang ◽  
Yingying Xing ◽  
Jian Lu ◽  
H. Michael Zhang
Keyword(s):  
Traffic Safety ◽  
Fuzzy Inference System ◽  
Fuzzy Inference ◽  
Traffic Volume ◽  
Learning Ability ◽  
Adaptive Network ◽  
Freeway Traffic ◽  
Inference System ◽  
Traffic Conflicts ◽  
The Impact

The truck operation of freeway has an impact on traffic safety. In particular, the gradually increasing in truck proportion will inevitably affect the freeway traffic operation of different traffic volume. In this paper, VISSIM simulation is used to supply the field data and orthogonal experimental is designed for calibrate the simulation data. Then, SSAM modeling is combined to analyze the impact of truck proportion on traffic flow parameters and traffic conflicts. The serious and general conflict prediction model based on the Adaptive Network-based Fuzzy Inference System (ANFIS) is proposed to determine the impact of the truck proportion on freeway traffic safety. The results show that when the truck proportion is around 0.4 under 3200 veh/h and 0.6 under 2600 veh/h, there are more traffic conflicts and the number of serious conflicts is more than the number of general conflicts, which also reflect the relationship between truck proportion and traffic safety. Under 3000 veh/h, travel time and average delay increasing while mean speed and mean speed of small car decreases with truck proportion increases. The mean time headway rises largely with the truck proportion increasing above 3000 veh/h. The speed standard deviation increases initially and then fall with truck proportion increasing. The lane-changing decreases while truck proportion increasing. In addition, ANFIS can accurately determine the impact of truck proportion on traffic conflicts under different traffic volume, and also validate the learning ability of ANFIS.

scholarly journals Two-Stream Multi-Channel Convolutional Neural Network for Multi-Lane Traffic Speed Prediction Considering Traffic Volume Impact

2020 ◽  
Vol 2674 (4) ◽  
pp. 459-470 ◽  
Author(s):  
Ruimin Ke ◽  
Wan Li ◽  
Zhiyong Cui ◽  
Yinhai Wang
Keyword(s):  
Neural Network ◽  
Convolutional Neural Network ◽  
Traffic Flow ◽  
Data Science ◽  
Prediction Models ◽  
Rapid Development ◽  
Traffic Volume ◽  
Speed Prediction ◽  
Traffic Speed ◽  
The Impact

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.

scholarly journals Evaluating the Impact of Increased Fuel Cost and Iran’s Currency Devaluation on Road Traffic Volume and Offenses in Iran, 2011–2019

Safety ◽  
2020 ◽  
Vol 6 (4) ◽  
pp. 49
Author(s):  
Milad Delavary ◽  
Zahra Ghayeninezhad ◽  
Martin Lavallière
Keyword(s):  
Time Series ◽  
Change Point ◽  
Road Traffic ◽  
Traffic Volume ◽  
Change Point Detection ◽  
Fuel Cost ◽  
Currency Devaluation ◽  
General Decline ◽  
Point Detection ◽  
The Impact

Trends and underlying patterns should be identified in the timely distribution of road traffic offenses to increase traffic safety. In this study, a time series analysis was used to study the incidence rate of road traffic violations on Iranian rural roads. Road traffic volume and offenses data from March 2011 to October 2019 were aggregated. Interrupted time series were used to evaluate the impact of increasing fuel cost in June of 2013 and July of 2014 and the currency devaluation of Rial vs. US dollars in July of 2017 on trends and patterns, traffic volume, and number of offenses. A change-point detection (CPD) analysis was also used to identify singular changes in the frequency of traffic offenses. Results show a general decline in the number of overtaking and speeding offenses of −24.31% and −13.23%, respectively, due to the first increase in fuel cost. The second increase only reduced overtaking by 20.97%. In addition, Iran’s currency devaluation reduced the number of overtaking offenses by 26.39%. Modeling a change-point detection and a Mann-Kendall Test of traffic offenses in Iran, it was found that the burden of violations was reduced.

scholarly journals Evaluation Of Traffic Performance Due To The Establishment Of The New Shopping Center

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Mochammad Dwiki ◽  
Diah Ayu Restuti
Keyword(s):  
Rapid Development ◽  
Secondary Data ◽  
Traffic Volume ◽  
Shopping Center ◽  
Traffic Performance ◽  
Building Area ◽  
Road Performance ◽  
The Impact ◽  
The City

The more rapid development of a region will also be followed by the increasing volume of traffic that occurs. With the operation of Sunrise Mall in the city of Mojokerto will bring a change in the increase in traffic volume. The purpose of this study was to determine the magnitude of the generation that occurred due to the opening of Sunrise Mall in the city of Mojokerto. Knowing the traffic performance around Sunrise Mall in the city of Mojokerto in the existing condition which only reviews Degrees of Saturation. Knowing the impact of traffic caused by the operation of Sunrise Mall in the city of Mojokerto. Know the alternatives that can be used to improve intersection, braid and road performance around Sunrise Mall in Mojokerto city and to find out the parking capacity and Parking Space Unit needed at Sunrise Mall in Mojokerto city. Secondary data collection in research includes geometric data on roads, data on traffic volume and intersections, data in and out of the Sunrise Mall building, data on Sunrise Mall characteristics and building area. Results showed that there was an influence of the construction of a new shopping center on traffic performance in the case study of Sunrise Mall Benteng Pancasila Mojokerto Street.

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