Changes In Traffic Volume Research Articles

Multistate Safety Evaluation of Intersection Conflict Warning Systems

Intersection conflict warning systems (ICWSs) were evaluated under the FHWA Evaluation of Low-Cost Safety Improvements Pooled Fund Study. The ICWS strategy is intended to reduce the crash frequency by alerting drivers of conflicting vehicles on adjacent approaches at unsignalized intersections. The evaluation used a multistate database of geometric, traffic, and crash data for rural four-legged, two-way, stop-controlled intersections equipped with ICWSs in Minnesota, Missouri, and North Carolina. To account for potential selection bias and regression to the mean, an empirical Bayes before–after analysis was conducted by using safety performance functions (SPFs) for reference groups of similar intersections without ICWS installation. These SPFs also controlled for changes in traffic volumes over time and time trends in crash counts unrelated to the strategy. The aggregate results indicate statistically significant crash reductions at the 5% level for all crash types for two-lane-at-two-lane intersections and four-lane-at-two-lane intersections. For two-lane-at-two-lane intersections, the crash modification factors (CMFs) for total crashes, fatal and injury crashes, and right-angle crashes are 0.73, 0.70, and 0.80, respectively, and for four-lane-at-two-lane intersections, they are 0.83, 0.80, and 0.85, respectively. The benefit–cost (B:C) ratio estimated with conservative cost and service life assumptions is 27:1 for all two-lane-at-two-lane intersections and 10:1 for four-lane-at-two-lane intersections with post-mounted warning signs. The results suggest that the strategy, even with conservative assumptions on cost, service life, and the value of a statistical life, can be highly cost-effective. As this strategy is evolving, this study reflects installation practices to date.

Impact of New Tolls on Existing Roadway Facilities: Hampton Roads, Virginia, Experience

The Midtown and Downtown Tunnels have been two of the most congested facilities in the Hampton Roads area of Virginia. Traffic queues nearly 4 mi long were daily occurrences at both facilities during peak travel periods. To relieve this congestion, construction began in 2012 of an additional two-lane tube at the Midtown Tunnel, along with rehabilitation of the Downtown Tunnel and the original Midtown Tunnel, and the addition of an extension to the Martin Luther King Freeway. To finance the project, whose completion is expected in 2018, toll collection began at the Midtown and Downtown Tunnels on February 1, 2014. The Hampton Roads Transportation Planning Organization (HRTPO) studied the impact of tolling on the regional transportation system by comparing the traffic and transit conditions before and after toll collection was implemented at the Midtown and Downtown Tunnels. This research will assist local decision makers as they determine whether tolls should be included as a funding source for candidate major highway projects. Further, the research will provide other planning agencies with information about the regional travel impacts of tolling, given that tolls were implemented on existing facilities before capacity improvements were completed. This study included an analysis of changes in traffic volumes, queues, delays, and transit conditions and highlighted a survey funded by the HRTPO to assess the public’s views of the project. Among the findings was that peak period delays decreased by 32% at four river-crossing corridors after tolls were implemented.

Developing Updatable Crash Prediction Model for Network Screening: Case Study of Czech Two-Lane Rural Road Segments

This paper focuses on application of crash prediction models in network screening. The two main questions were ( a) What variables should be involved in the model? and ( b) What length should the modeled period be? Answers to these questions should provide guidelines for developing an updatable crash prediction model (i.e., a model that is both reliable and simple so that its updating for periodical network screening is not highly demanding). Data on approximately 1,000 km (600 mi) of a two-lane rural-road network from South Moravia, Czech Republic, were used. On the basis of 8 years of annual crash frequencies, together with exposure and geometrical variables, several variants of prediction models were developed. To study the quality of the models, a series of consistency tests was applied relative to comparison of the models themselves as well as to their diagnostic performance. As a result, simple crash prediction models (that included traffic volume, segment length, and curvature change rate) were found sufficient for network screening. If one supposes that length and curvature are unlikely to change often, only traffic volume data need to be periodically updated. Consistency analyses indicate that this period should be 4 years. Under these conditions, models are being applied in the studied region. Further planned activities include extensions to intersections and also to other Czech regions.

Optimal Adaptation Process of EMS Systems in a Changing and Uncertain Environment

The service quality, which means accessibility of emergency sites, and operating costs of an emergency medical service (EMS) system are directly related to the number of EMS stations and their location. Exogenous changes, like increased traffic volume or structural changes in the underlying urban area cause necessary adaptations of this EMS infrastructure over time. Such EMS system adaptations are made on a strategic level, because the related investments are enormous and modifications are hardly reversible. Due to the high sensitivity of EMS quality to environmental changes (e.g., traffic conditions) an intertemporal smoothing of the EMS system adaptation process is necessary to counteract over-adjustments to short-term disturbances. The complexity of this planning problem increases even more when taking uncertain developments of external influencing factors into consideration. Hence, an optimal dynamic adaptation process for strategic EMS infrastructure planning is presented. Besides optimizing service quality and operating costs, a tempered adaptation process is ensured that respects the initial system state. For this purpose, a deterministic three-objective MILP is developed. To incorporate uncertain developments, three model extensions are suggested. The models are compared in an exemplary application. The developed models overcome the major drawbacks of existing models which neglect the initial system state, environmental changes, or the costs of system adaptation. Thus, the model gives deeper insights to real-world decision situations. By means of model extensions concerning uncertainty, the underlying planning situation is described more realistically, which allows further insights and considers different perspectives of the decision situation.

An uncertainty-managing batch relevance-based approach to network anomaly detection

The main aim in network anomaly detection is effectively spotting hostile events within the traffic pattern associated to network operations, by distinguishing them from normal activities. This can be only accomplished by acquiring the a-priori knowledge about any kind of hostile behavior that can potentially affect the network (that is quite impossible for practical reasons) or, more easily, by building a model that is general enough to describe the normal network behavior and detect the violations from it. Earlier detection frameworks were only able to distinguish already known phenomena within traffic data by using pre-trained models based on matching specific events on pre-classified chains of traffic patterns. Alternatively, more recent statistics-based approaches were able to detect outliers respect to a statistic idealization of normal network behavior. Clearly, while the former approach is not able to detect previously unknown phenomena (zero-day attacks) the latter one has limited effectiveness since it cannot be aware of anomalous behaviors that do not generate significant changes in traffic volumes. Machine learning allows the development of adaptive, non-parametric detection strategies that are based on “understanding” the network dynamics by acquiring through a proper training phase a more precise knowledge about normal or anomalous phenomena in order to classify and handle in a more effective way any kind of behavior that can be observed on the network. Accordingly, we present a new anomaly detection strategy based on supervised machine learning, and more precisely on a batch relevance-based fuzzyfied learning algorithm, known as U-BRAIN, aiming at understanding through inductive inference the specific laws and rules governing normal or abnormal network traffic, in order to reliably model its operating dynamics. The inferred rules can be applied in real time on online network traffic. This proposal appears to be promising both in terms of identification accuracy and robustness/flexibility when coping with uncertainty in the detection/classification process, as verified through extensive evaluation experiments.

A Modeling of the Rainfall’s Impact on the Air Quality via Changes of Vehicle Travel Pattern

The extreme weather conditions negatively affect the traffic flow performance, and the change of traffic systems has significant impacts on the air pollutant emission. This study identifies the correlation between rainfall, traffic volume, travel speed and air pollution concentration (NO2 and PM10) in Seoul. We employed a path analysis using rainfall data from Korea Meteorological Administration and Seoul's air quality and traffic monitoring data in July and August on 2014. It is found that the occurrence of rainfall decreases NO2 and PM10 concentration due to the higher washing effect, while rainfall increases NO2 and PM10 concentration via the changes in traffic volume and traffic speed. The analysis of the rainfall intensity reveals that the rainfall increases NO2 concentration due to the traffic volume increase and the traffic speed reduction if an hourly rainfall is more than 5mm. It is to note that the current model succeeds in identifying the relationship between weather conditions, traffic flow performance and air pollution in a unified and consistent framework, which can be used for better predicting the changes in air pollution concentration.

How does variation in winter weather affect deer—vehicle collision rates?

Understanding how deer move in relationship to roads is critical, because deer are in vehicle collisions, and collisions cause vehicle damage, as well as human injuries and fatalities. In temperate climates, mule deer Odocoileus hemionus have distinct movement patterns that affect their spatial distribution in relationship to roads. In this paper, we analyzed deer movements during two consecutive winter seasons with vastly different conditions to determine how deer—vehicle collision rates responded. We predicted that deer—vehicle collision rates would be higher when precipitation and snow depth were higher. We used meteorological data from local weather stations to describe temperature, precipitation and snow depth. We monitored deer movements with global positioning system telemetry to document distance of deer to roads, elevation use and road crossing rates. We also documented changes in deer abundance and traffic volumes, which were potentially confounding variables. We found that precipitation decreased 50% and snow depth decreased 48% between winters. In response, deer used habitats that were 16% higher in elevation and that were 213% farther from roads with high traffic volumes. Consequently, crossing rates also decreased as much as 96% on roads with high traffic volumes. Reduced crossing rates were likely responsible for much of the 75% decrease in deer—vehicle collisions that occurred during the second winter. Abundance and traffic volume also can be important factors affecting deer—vehicle collisions rates. However, it is unlikely they were the major drivers of variation in deer—vehicle collisions during our study, because traffic volumes did not change between years and deer abundance only decreased 7%. Our data suggest a mechanism by which variation in winter conditions can contribute to differences in deer—vehicle collision rates between years. These findings have significant management implications for deer—vehicle collision mitigation.

Investigating the impact of urban grade-separation on pedestrian PM2.5 exposure

For urban intersections, grade separations have been deemed a way of mitigating traffic congestion. However, the environmental impact of various grade separations, especially on pedestrian exposure to traffic-related air pollution, is unknown. Particulate matter of 2.5 µm or less (PM2.5) near roadsides comes mainly from vehicle emissions and has negative respiratory health effects. Pedestrian PM2.5 exposure at ground level at different types of intersection and are studied and compared here. Based on realistic survey data at a current at-grade intersection, and reasonable assumptions about traffic speed and volume changes, MOVES modeling software used the highest resolution approach of operating mode distribution to calculate PM2.5 emission inventory for three scenarios: at-grade intersection, overpass grade separation, and underpass grade separation. Pedestrian PM2.5 exposure concentrations were estimated using the AERMOD model. The results of the case study show that both underpass and overpass intersections largely decrease pedestrian PM2.5 exposure, at almost the same amplitude. From the viewpoint of regional environmental impacts, however, the underpass-type intersection is recommended for replacing the at-grade intersection, in order to both reduce traffic congestion and better contain pollution. The findings of this research indicate that, as three-dimensional urban transportation design is becoming a more popular measure for relieving traffic congestion, environmental analysis will become an increasingly critical part of intersection design.

Approaches to Adaptive Lighting on Roadways

Adaptive lighting is an approach to lighting design that proposes to change the light level on a roadway on the basis of the needs of drivers. A review of the literature and building the connection between crashes and light level allowed the development of a system to select roadway luminance levels and then modify these levels on the basis of the needs of the driver. This adaptive lighting system uses parameters such as traffic volume, ambient light levels, pavement marking quality, intersection density, and, most important, the presence of pedestrians to allow lighting design criteria to be selected through a weighting system. As these parameters (such as traffic volume) change, a new light requirement is determined, and the lighting system can be adjusted with controllable luminaires and a master control system. Guidelines for the implementation of this system and an example are provided.

Changes in air quality at near-roadway schools after a major freeway expansion in Las Vegas, Nevada

Near-roadway ambient black carbon (BC) and carbon monoxide (CO) concentrations were measured at two schools adjacent to a freeway and at an urban background school 2 km from the freeway to determine the change in concentrations attributable to vehicle emissions after the three-lane expansion of U.S. Highway 95 (US 95) in Las Vegas, Nevada. Between summer 2007 and summer 2008, average weekday small-vehicle volume increased by 40% ± 2% (standard error). Average weekday large-vehicle volume decreased by 17% ± 5%, due to a downturn in the economy and an associated decline in goods movement. Average vehicle speed increased from 58 to 69 mph, a 16% ± 1% increase. The authors compared BC and CO concentrations in summer 2007 with those in summer 2008 to understand what effect the expansion of the freeway may have had on ambient concentrations: BC and CO were measured 17 m north of the freeway sound wall, CO was measured 20 m south of the sound wall, and BC was measured at an urban background site 2 km south of the freeway. Between summer 2007 and summer 2008, median BC decreased at the near-road site by 40% ± 2% and also decreased at the urban background site by 24% ± 4%, suggesting that much of the change was due to decreases in emissions throughout Las Vegas, rather than only on US 95. CO concentrations decreased by 14% ± 2% and 10% ± 3% at the two near-road sites. The decrease in BC concentrations after the expansion is likely due to the decrease in medium- and heavy-duty-vehicle traffic resulting from the economic recession. The decrease in CO concentrations may be a result of improved traffic flow, despite the increase in light-duty-vehicle traffic.ImplicationsMonitoring of BC and CO at near-road locations in Las Vegas demonstrated the impacts of changes in traffic volume and vehicle speed on near-road concentrations. However, urban-scale declines in concentrations were larger than near-road changes due to the impacts of the economic recession that occurred contemporaneously with the freeway expansion.

Vpliv turizma na značilnosti cestnega prometa v Koprskem primorju

Koprsko primorje je najbolj obiskano turistično območje v Sloveniji. Velik turistični obisk vpliva tudi na značilnosti prometa na tem območju. Analiza podatkov o dnevnem številu vozil za števna mesta prometa na tem območju je pokazala, da so spremembe v obsegu prometa v veliki meri povezane z razpoložljivostjo prostega časa in vremenom. Kljub temu so glede intenzivnosti in opaznosti tovrstnih vplivov znotraj območja precejšnje razlike, saj se na njem prepletajo vplivi turizma, drugih gospodarskih dejavnosti in lokalnega prebivalstva.

Effects of vehicle technologies, traffic volume changes, incidents and work zones on greenhouse gas emissions production

This paper quantifies the effects of newer, more efficient vehicle technologies, traffic volume changes, incidents and work zones on emissions production from on-road traffic. The effects are studied using microscopic traffic simulation and developed emissions estimation tools that together can capture emissions effects from the operating parameters of vehicles. An emissions estimation tool is used to estimate CO2, CO, CH4, THC, NOx, SOx, PM10 and PM2.5 emissions from on-road traffic. A case study of Montgomery County, Maryland’s I-270-MD-355 corridor, including connecting arterials, was conducted. This indicates that vehicle composition greatly affects the amount of emissions, and significant potential for reaching emissions reduction goals exists through improvements in vehicle mix efficiencies within the traffic composition. Further work zones and traffic incidents reduce the amount of emissions produced due to reduced average speeds, while per vehicle emissions rise over the span of the simulation network and simulation period. Models are also developed to support GHG emissions analyses for other comparable roadways.

Forecast of Passenger and Freight Traffic Volume based on Elasticity Coefficient Method and Grey Model

The increase in passenger and freight traffic in a region reflects the development of railways, highways, waterways, aviation, and pipeline. With the growth of economy, China's transportation develops rapidly. However, the passenger and freight traffic present different growth features in different regions. Therefore, a reasonable forecast model for passenger and freight traffic and the analysis of relationship between regional transportation and economy are important for transportation planning. The elasticity coefficient between the passenger traffic volume, freight traffic volume and gross domestic product (GDP) is calculated based on the data from 2001 to 2010 in different regions in China. Then, the relationship between the change of regional traffic volume and regional economic development is obtained. With the analysis of the pros and cons for different forecast models, Elasticity Coefficient Method, GM (1, 1) model, and DGM model have been used to forecast passenger and freight traffic volumes from 2011 to 2015. In order to improve the accuracy of the forecast results, the combined models based on the variance reciprocal and the optimal weighting are applied to optimize the forecasting model. Among all the forecast models, the combined model with optimal weights outperforms other models with a relative error less than 0.006% for the freight traffic volume. The accuracy of forecast models on passenger and freight traffic volume has been improved, which provides a reasonable basis for the planning and development of the transportation system.

Investigating the safety effects of road width on urban collector roadways

Collector roads are designed to provide a balance between traffic safety, mobility, and land access; however, the literature on the effects of collector lane width on safety is generally inconsistent. This study determines the safety implications of oversized collectors by analyzing collisions statistics, traffic-survey data, and roadway-inventory data from the City of Edmonton. The paper adopts a cross-sectional evaluation methodology by developing negative binomial (NB) safety performance functions (SPFs) for total collisions. Based on the NB SPFs, it was found that segment length, traffic volume, access-point density and midblock change was statistically significant and positively related to collisions, while the width was negatively related to collisions and statistically significant. The interaction term of volume and lane width was found to be positively related to collisions. This suggests that the collision rate for oversized collector roads is higher than that for standard-sized roads. It was also found that both standard-sized and oversized roads, with some form of midblock roadway width change, were less safe than those with uniform width. Converting oversized roads to standard size was found to improve safety only for the roads with an average daily traffic (ADT) volume higher than 4000. The maximum crash reduction was estimated to be as high as 28.9%. This study is timely given the contradicting evidence that exists in current literature regarding the relationship between safety and oversized collector roads. For the present data set, this paper provides guidelines on when to convert oversized collector roads to standard-sized collector roads, to improve safety.

INFLUENCE OF TRAFFIC MIX ON PCU VALUE OF VEHICLES UNDER HETEROGENEOUS TRAFFIC CONDITIONS

Study of the basic traffic flow characteristics like traffic volume is a prerequisite for the effective planning, design, operation and management of roadway systems. Traffic in developing countries like India is heterogeneous in nature, consisting of vehicles of different categories with widely varying dimensional and operational characteristics. The moving vehicles of heterogeneous traffic occupy any convenient lateral position on the road without any lane discipline, based on the availability of space. The interaction between moving vehicles under such traffic condition is highly complex in nature, which can be represented in terms of the amount of impedance caused to flow of traffic by a vehicle type in comparison with that of standard vehicle (passenger car). Passenger Car Unit (PCU) can be an appropriate measure to represent the relative impedance caused by a vehicle in heterogeneous traffic. This paper is concerned with the application of micro-simulation techniques to derive equivalency values (PCU factors) on a purely homogeneous (cars-only) traffic stream as well as on a heterogeneous traffic stream for different categories of road vehicles over a wide range of traffic flow and compositions on four-lane divided urban roads in India. The PCU values obtained for the different types of vehicles, for a wide range of traffic volume and composition, indicate that the PCU values of a vehicle type significantly changes with change in traffic volume and composition.

Potential of Kentucky Freeway Rights-of-Way to Displace Fossil Fuel Consumption through Production of Switchgrass (Panicum virgatum L.)

ABSTRACT The grassland area of freeway rights-of-way in Kentucky was estimated to determine its potential to produce switchgrass (Panicum virgatum L.) for bioenergy feedstock. Kentucky's freeways include 9.2×103 ha of mowed grassland within their rights-of-way. This area could produce approximately 64×103 t/yr of switchgrass, sufficient to make 21×106 L of cellulosic ethanol, or generate 64 GWh of electricity annually. Switchgrass grown on freeway rights-of-way could offset about 0.5% of fossil fuel currently used on Kentucky freeways if converted to ethanol, or 0.8% if converted to electricity for vehicle propulsion. Future changes in vehicle efficiency and traffic volume will have much greater impact on the volume of fossil fuel used on Kentucky freeways than conversion of freeway-grown switchgrass to alternative fuel. Kentucky's state government's projection of a 42% increase in traffic volume by 2025 contrasts with this study's projection of 28% decline derived from extrapolation of linear trends obse...

Financial Evaluation for Toll Road Projects Considering Traffic Volume and Serviceability Interactions

The rapid increase in both financial demands and the need for large and comprehensive highway infrastructure systems necessitates public authorities to muster support from the private sector. Public-private partnerships (PPP) have been increasingly adopted and cited as one of the most effective project delivery systems, which bring balance to risks and rewards between involved project participants. However, a number of PPP infrastructure projects around the world have been reported to have operating deficits and difficulties in debt-servicing. One of the major reasons for these difficulties is the unrealistic and inaccurate prediction of project investment performance during the initial stages of project viability and profitability analysis. Therefore, the research reported in this paper presents a formulation of a comprehensive framework that evaluates financial viability of PPP toll road projects. The framework utilizes a modified user-equilibrium traffic-assignment algorithm to estimate toll road traffic volume considering critical demand-influencing factors, which include travel time, pavement serviceability, and out-of-pocket user trip expenses. The proposed framework also considers the effects of the rehabilitation maintenance activities on the equilibrium flow pattern and project financial viability. This makes possible an estimation of the maintenance costs and frequency as well as an evaluation of the effects of rehabilitation programs on the traffic volume. The research reported in this paper also demonstrates the difference in traffic-flow patterns with and without interactive changes in pavement performance and traffic volume to demonstrate the need for incorporation of pavement performance and network levels of service into PPP highway project evaluation.

Source apportionment of traffic emissions of particulate matter using tunnel measurements

This study aims to quantify exhaust/non-exhaust emissions and the uncertainties associated with them by combining innovative motorway tunnel sampling and source apportionment modelling. Analytical techniques ICP-AES and GC–MS were used to identify the metallic and organic composition of PM10, respectively. Good correlation was observed between Fe, Cu, Mn, Ni, Pb and Sb and change in traffic volume. The concentration of polycyclic aromatic hydrocarbons and other organics varies significantly at the entrance and exit site of the tunnel, with fluoranthene, pyrene, benzo[a]pyrene, chrysene and benzothiazole having the highest incremented concentrations. The application of Principal Component Analysis and Multiple Linear Regression Analysis helped to identify the emission sources for 82% of the total PM10 mass inside the tunnel. Identified sources include resuspension (27%), diesel exhaust emissions (21%), petrol exhaust emissions (12%), brake wear emissions (11%) and road surface wear (11%). This study shows that major health related chemical species of PM10 originate from non-exhaust sources, further signifying the need for legislation to reduce these emissions.

Dynamic Braess's Paradox in Complex Communication Networks

Braess's paradox shows a counterintuitive scenario where more resources may cause worse traffic performance when all users pursue their personal optimum. Previous study on this topic mainly focused on the specific traffic volume to show the existence of such a paradox. For real-world complex communication networks, on the contrary, the traffic volume changes from time to time. Therefore, it is important to study the traffic performance under this dynamic condition. We find that Braess's paradox does not happen when the traffic volume is sufficiently low or sufficiently high. Between these two extremes, the probability that Braess's paradox happens also changes with the traffic volume. This result is helpful for communication network planning and management.

A before–after study of the effects on safety of environmental speed limits in the city of Oslo, Norway

Starting in the winter of 2004–2005, a temporary speed limit of 60km/h (ordinary speed limit: 80km/h) was introduced on one of the major arterial roads in the city of Oslo, Norway as a measure to reduce air pollution, in particular the spread of micro-particles torn from the road surface by studded tyres. The speed limit, referred to as an environmental speed limit, was in force from November 1 to March 31. Similar speed limits were later introduced on other arterial roads in Oslo. This paper presents a before-and-after study of the effects of these speed limits on accidents. Four study designs were employed: (1) A simple before–after study; (2) A before–after study using the rest of Oslo as comparison group; (3) A before–after study based on accident rates; (4) An empirical Bayes before–after study. The latter design is widely regarded as the best, but its implementation in the current study was not straightforward. The number of injury accidents was reduced by about 25–35% according to all study designs. The estimate of effect did not differ much between the different study designs. It is reasonable to rule out confounding by chance variation, long-term trends, changes in traffic volume and regression-to-the-mean. It cannot be claimed, however, that the entire accident reduction was attributable to the environmental speed limits exclusively.