Effectiveness of Predictive Weather-Related Active Transportation and Demand Management Strategies for Network Management

2017 ◽  
Vol 2667 (1) ◽  
pp. 71-87 ◽  
Author(s):  
Zihan Hong ◽  
Hani S. Mahmassani ◽  
Xiang Xu ◽  
Archak Mittal ◽  
Ying Chen ◽  
...  
Keyword(s):  
Traffic Management ◽  
Demand Management ◽  
Management Strategies ◽  
Weather Conditions ◽  
Active Transportation ◽  
Operational Conditions ◽  
Traffic Conditions ◽  
Adverse Weather ◽  
Traffic Performance ◽  
The Impact

This paper presents the development, implementation, and evaluation of predictive active transportation and demand management (ATDM) and weather-responsive traffic management (WRTM) strategies to support operations for weather-affected traffic conditions with traffic estimation and prediction system models. First, the problem is defined as a dynamic process of traffic system evolution under the impact of operational conditions and management strategies (interventions). A list of research questions to be addressed is provided. Second, a systematic framework for implementing and evaluating predictive weather-related ATDM strategies is illustrated. The framework consists of an offline model that simulates and evaluates the traffic operations and an online model that predicts traffic conditions and transits information to the offline model to generate or adjust traffic management strategies. Next, the detailed description and the logic design of ATDM and WRTM strategies to be evaluated are proposed. To determine effectiveness, the selection of strategy combination and sensitivity of operational features are assessed with a series of experiments implemented with a locally calibrated network in the Chicago, Illinois, area. The analysis results confirm the models’ ability to replicate observed traffic patterns and to evaluate the system performance across operational conditions. The results confirm the effectiveness of the predictive strategies tested in managing and improving traffic performance under adverse weather conditions. The results also verify that, with the appropriate operational settings and synergistic combination of strategies, weather-related ATDM strategies can generate maximal effectiveness to improve traffic performance.

scholarly journals Assessing the Impact of Weather on Traffic Intensity

2010 ◽  
Vol 2 (1) ◽  
pp. 60-68 ◽  
Author(s):  
Mario Cools ◽  
Elke Moons ◽  
Geert Wets
Keyword(s):  
Travel Behavior ◽  
Traffic Management ◽  
Management Strategies ◽  
Weather Conditions ◽  
Traffic Intensity ◽  
Weather Effects ◽  
Specific Location ◽  
Traffic Count ◽  
Local Roads ◽  
The Impact

Abstract This paper focuses on the effect of weather conditions on daily traffic intensities (the number of cars passing a specific segment of a road). The main objective is to examination whether or not weather conditions uniformly alter daily traffic intensities in Belgium, or in other words whether or not road usage on a particular location determines the size of the impacts of various weather conditions. This general examination is a contribution that allows policymakers to assess the appropriateness of countrywide versus local traffic management strategies. In addition, a secondary goal of this paper is to validate findings in international literature within a Belgian context. To achieve these goals, the paper analyzes the effects of weather conditions on both upstream (toward a specific location) and downstream (away from a specific location) traffic intensities at three traffic count locations typified by a different road usage. Perhaps the most interesting results of this study for policymakers are the heterogeneity of the weather effects between different traffic count locations, and the homogeneity of the weather effects on upstream and downstream traffic at specific locations. The results also indicate that snowfall, rainfall, and wind speed diminish traffic intensity, and high temperatures increase traffic intensity. Further generalizations of the findings might be possible by studying weather impacts on local roads and by shifting the focus of research toward travel behavior.

scholarly journals Impacts of Snowy Weather Conditions on Expressway Traffic Flow Characteristics

2013 ◽  
Vol 2013 ◽  
pp. 1-6 ◽  
Author(s):  
Jiancheng Weng ◽  
Lili Liu ◽  
Jian Rong
Keyword(s):  
Traffic Flow ◽  
Traffic Management ◽  
Control Strategies ◽  
Flow Characteristics ◽  
Weather Conditions ◽  
Service Levels ◽  
The Road ◽  
Adverse Weather ◽  
Snow Conditions ◽  
The Impact

Snowy weather will significantly degrade expressway operations, reduce service levels, and increase driving difficulty. Furthermore, the impact of snow varies in different types of roads, diverse cities, and snow densities due to different driving behavior. Traffic flow parameters are essential to decide what should be appropriate for weather-related traffic management and control strategies. This paper takes Beijing as a case study and analyzes traffic flow data collected by detectors in expressways. By comparing the performance of traffic flow under normal and snowy weather conditions, this paper quantitatively describes the impact of adverse weather on expressway volume and average speeds. Results indicate that average speeds on the Beijing expressway under heavy snow conditions decrease by 10–20 km/h when compared to those under normal weather conditions, the vehicle headway generally increases by 2–4 seconds, and the road capacity drops by about 33%. This paper also develops a specific expressway traffic parameter reduction model which proposes reduction coefficients of expressway volumes and speeds under various snow density conditions in Beijing. The conclusions paper provide effective foundational parameters for urban expressway controls and traffic management under snow conditions.

scholarly journals Modelling speed behaviour in rural highways: Safety analysis of driving under adverse road-weather conditions

PLoS ONE ◽  
2021 ◽  
Vol 16 (8) ◽  
pp. e0256322
Author(s):  
Rillagoda G. N. Yasanthi ◽  
Babak Mehran ◽  
Wael K. M. Alhajyaseen
Keyword(s):  
Traffic Safety ◽  
Traffic Management ◽  
Management Strategies ◽  
Weather Conditions ◽  
Minimum Variance ◽  
Unbiased Estimation ◽  
Simultaneous Occurrence ◽  
Traffic Conditions ◽  
Safety Risks ◽  
Time Of Travel

This study proposes a methodical approach to model desired speed distributions under different road-weather and traffic conditions followed by identification of road-weather conditions with potentially higher safety risks in rural divided highways located in extremely cold regions. Desired speed distributions encompassing unique combinations of adverse road-weather and traffic conditions are modelled as normal distributions characterized by their means and standard deviations formulated based on two principal statistical theorems and techniques i.e., Central Limit Theorem and Minimum Variance Unbiased Estimation. Combination of the precipitation conditions, road surface conditions, time of the day, temperature, traffic flow and the heavy vehicle percentage at the time of travel were considered in defining the combinations of road-weather and traffic conditions. The findings reveal that simultaneous occurrence of particular precipitation and pavement conditions significantly affect the characteristics of the desired speed distribution and potentially expose drivers to elevated safety risks. Jurisdictions experiencing extreme road-weather conditions may adapt the proposed methodology to assess speed behaviour under different road-weather conditions to establishing and deploying weather-responsive traffic management strategies such as variable speed limit to regulate speeding and improve traffic safety in winter.

Modelling of 10 Gbps Free Space Optics Communication Link Using Array of Receivers in Moderate and Harsh Weather Conditions

2017 ◽  
Vol 38 (3) ◽  
Author(s):  
Amit Gupta ◽  
Nagpal Shaina
Keyword(s):  
Free Space ◽  
Weather Conditions ◽  
Quality Data ◽  
Laser Source ◽  
Communication Link ◽  
Free Space Optical ◽  
Space Optics ◽  
Received Power ◽  
Adverse Weather ◽  
The Impact

AbstractIntersymbol interference and attenuation of signal are two major parameters affecting the quality of transmission in Free Space Optical (FSO) Communication link. In this paper, the impact of these parameters on FSO communication link is analysed for delivering high-quality data transmission. The performance of the link is investigated under the influence of amplifier in the link. The performance parameters of the link like minimum bit error rate, received signal power and Quality factor are examined by employing erbium-doped fibre amplifier in the link. The effects of amplifier are visualized with the amount of received power. Further, the link is simulated for moderate weather conditions at various attenuation levels on transmitted signal. Finally, the designed link is analysed in adverse weather conditions by using high-power laser source for optimum performance.

Comparison of two gap-filling techniques for nitrous oxide fluxes from agricultural soil

2019 ◽  
Vol 99 (1) ◽  
pp. 12-24 ◽  
Author(s):  
Rezvan Taki ◽  
Claudia Wagner-Riddle ◽  
Gary Parkin ◽  
Rob Gordon ◽  
Andrew VanderZaag
Keyword(s):  
Missing Values ◽  
Interpolation Method ◽  
Weather Conditions ◽  
Linear Interpolation ◽  
Bias Error ◽  
Research Station ◽  
Ann Model ◽  
Gap Filling ◽  
Adverse Weather ◽  
The Impact

Micrometeorological methods are ideally suited for continuous measurements of N2O fluxes, but gaps in the time series occur due to low-turbulence conditions, power failures, and adverse weather conditions. Two gap-filling methods including linear interpolation and artificial neural networks (ANN) were utilized to reconstruct missing N2O flux data from a corn–soybean–wheat rotation and evaluate the impact on annual N2O emissions from 2001 to 2006 at the Elora Research Station, ON, Canada. The single-year ANN method is recommended because this method captured flux variability better than the linear interpolation method (average R2 of 0.41 vs. 0.34). Annual N2O emission and annual bias resulting from linear and single-year ANN were compatible with each other when there were few and short gaps (i.e., percentage of missing values <30%). However, with longer gaps (>20 d), the bias error in annual fluxes varied between 0.082 and 0.344 kg N2O-N ha−1 for linear and 0.069 and 0.109 kg N2O-N ha−1 for single-year ANN. Hence, the single-year ANN with lower annual bias and stable approach over various years is recommended, if the appropriate driving inputs (i.e., soil temperature, soil water content, precipitation, N mineral content, and snow depth) needed for the ANN model are available.

scholarly journals EFFECTS OF THE RAINSTORM ON URBAN ROAD TRAFFIC SPEED &mdash; A CASE STUDY OF SHENZHEN, CHINA

2017 ◽  
Vol XLII-2/W7 ◽  
pp. 71-75 ◽  
Author(s):  
Q. Li ◽  
X. Hao ◽  
W. Wang ◽  
A. Wu ◽  
Z. Xie
Keyword(s):  
Traffic Management ◽  
Road Traffic ◽  
Urban Traffic ◽  
Gps Tracking ◽  
Shenzhen City ◽  
Adverse Weather ◽  
Stormy Weather ◽  
Wide Scale ◽  
Traffic Speed ◽  
The Impact

The adverse weather may significantly impact urban traffic speed and travel time. Understanding the influence of the rainstorm to urban traffic speed is of great importance for traffic management under stormy weather. This study aims to investigate the impact of rainfall intensity on traffic speed in the Shenzhen (China) during the period 1 July 2015&amp;ndash;31 August 2016. The analysis was carried out for five 1-h periods on weekdays during the morning periods (6:00 AM&amp;ndash;11:00 AM). Taxi-enabled GPS tracking data obtained from Shenzhen city are used in the analysis. There are several findings in this study. Firstly, nearly half of the roads are significantly affected by the rainstorm. Secondly, the proportion of positive correlated roads is about 35&amp;thinsp;%, but there still are some roads with uncorrelated traffic speed variation rates (SVR) and rainfall intensities. Thirdly, the impact of the rainstorm on traffic speed is not homogeneous but with obvious spatial difference. This research provides useful information that can be used in traffic management on a city-wide scale under stormy weather.

scholarly journals An Advanced Deep Learning Approach for Multi-Object Counting in Urban Vehicular Environments

2021 ◽  
Vol 13 (12) ◽  
pp. 306
Author(s):  
Ahmed Dirir ◽  
Henry Ignatious ◽  
Hesham Elsayed ◽  
Manzoor Khan ◽  
Mohammed Adib ◽  
...  
Keyword(s):  
Deep Learning ◽  
Intelligent Transportation Systems ◽  
Smart Cities ◽  
Weather Conditions ◽  
Research Area ◽  
Transportation Systems ◽  
Detection Accuracy ◽  
Adverse Weather ◽  
Object Counting ◽  
The Impact

Object counting is an active research area that gained more attention in the past few years. In smart cities, vehicle counting plays a crucial role in urban planning and management of the Intelligent Transportation Systems (ITS). Several approaches have been proposed in the literature to address this problem. However, the resulting detection accuracy is still not adequate. This paper proposes an efficient approach that uses deep learning concepts and correlation filters for multi-object counting and tracking. The performance of the proposed system is evaluated using a dataset consisting of 16 videos with different features to examine the impact of object density, image quality, angle of view, and speed of motion towards system accuracy. Performance evaluation exhibits promising results in normal traffic scenarios and adverse weather conditions. Moreover, the proposed approach outperforms the performance of two recent approaches from the literature.

scholarly journals Capacity Analysis for Approach Channels Shared by LNG Carriers

2020 ◽  
Vol 8 (9) ◽  
pp. 697
Author(s):  
Xiang Gao ◽  
Linying Chen ◽  
Pengfei Chen ◽  
Yu Luo ◽  
Junmin Mou
Keyword(s):  
Traffic Management ◽  
Time Windows ◽  
Management Strategies ◽  
Capacity Analysis ◽  
Behavioral Characteristics ◽  
Traffic Capacity ◽  
Approach Channel ◽  
General Cargo ◽  
The Impact

The transport of liquefied natural gas (LNG) has significant impact on traffic capacity of waterways, especially the approach channels shared by LNG carriers and other types of ships (general cargo ships, container ships, etc.). Few studies take the behavioral characteristics of LNG carriers and their impacts into consideration. In this paper, we propose a framework for capacity analysis of shared approach channels based on the spatial–temporal consumption method. It consists of three modules: (1) the tide module predicts the tidal height and tidal time for identifying the time windows for LNG carriers; (2) the spatial–temporal consumption module is introduced to calculate the capacity of approach channels; (3) the LNG carrier navigation module is for analyzing the characteristics of LNG carriers and the impact on the capacity of approach channels. A spatial–temporal indexed chart is designed to visualize the utilization of the spatial–temporal resources. A case study on the approach channel of Yueqing Bay near the east coast of China is conducted to verify the effectiveness of the framework. The utilization rates of the approach channel and the impact of LNG carriers are presented using our method. The results of the case study indicate that the proposed traffic capacity analyzing framework can provide support for making traffic management strategies.

scholarly journals Evaluating Impacts of Overloaded Heavy Vehicles on Freeway Traffic Condition by a Novel Multi-Class Traffic Flow Model

2018 ◽  
Vol 10 (12) ◽  
pp. 4694 ◽  
Author(s):  
Xiang Wang ◽  
Po Zhao ◽  
Yanyun Tao
Keyword(s):  
Traffic Flow ◽  
Flow Model ◽  
Management Strategies ◽  
Maximum Speed ◽  
Heavy Vehicles ◽  
Fundamental Diagram ◽  
Traffic Condition ◽  
Traffic Flow Model ◽  
Traffic Conditions ◽  
The Impact

Overloaded heavy vehicles (HVs) have significant negative impacts on traffic conditions due to their inferior driving performance. Highway authorities need to understand the impact of overloaded HVs to assess traffic conditions and set management strategies. We propose a multi-class traffic flow model based on Smulders fundamental diagram to analyze the influence of overloaded HVs on traffic conditions. The relationship between the overloading ratio and maximum speed is established by freeway toll collection data for different types of HVs. Dynamic passenger car equivalent factors are introduced to represent the various impacts of overloaded HVs in different traffic flow patterns. The model is solved analytically and discussed in detail in the appendices. The model validation results show that the proposed model can represent traffic conditions more accurately with consideration for overloaded HVs. The scenario tests indicate that the increase of overloaded HVs leads to both a higher congestion level and longer duration.

Investigating the Impact of Rainfall on Travel Speed

2014 ◽  
Vol 71 (3) ◽  
Author(s):  
Nordiana Mashros ◽  
Johnnie Ben-Edigbe ◽  
Hashim Mohammed Alhassan ◽  
Sitti Asmah Hassan
Keyword(s):  
Empirical Studies ◽  
Heavy Rain ◽  
Weather Conditions ◽  
Travel Speed ◽  
Operating Conditions ◽  
Speed Reduction ◽  
Light Rain ◽  
Rainfall Condition ◽  
Adverse Weather ◽  
The Impact

The road network is particularly susceptible to adverse weather with a range of impacts when different weather conditions are experienced. Adverse weather often leads to decreases in traffic speed and subsequently affects the service levels. The paper is aimed at investigating the impact of rainfall on travel speed and quantifying the extent to which travel speed reduction occurs. Empirical studies were conducted on principle road in Terengganu and Johor, respectively for three months. Traffic data were collected by way of automatic traffic counter and rainfall data from the nearest raingauge station were supplied by the Department of Irrigation and Drainage supplemented by local survey data. These data were filtered to obtain traffic flow information for both dry and wet operating conditions and then were analyzed to see the effect of rainfall on percentile speeds. The results indicated that travel speed at 15th, 50th and 85th percentiles decrease with increasing rainfall intensities. It was observed that allpercentile speeds decreased from a minimum of 1% during light rain to a maximum of 14% during heavy rain. Based on the hypothesis that travel speed differ significantly between dry and rainfall condition; the study found substantial changes in percentile speeds and concluded that rainfalls irrespective of their intensities have significant impact on the travel speed.

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