Effect Of Traffic Density Research Articles

Individual differences, ADHD diagnosis, and driving performance: effects of traffic density and distraction type

The present study examined the impact of individual differences, attention, and memory deficits on distracted driving. Drivers with ADHD are more susceptible to distraction which results in more frequent collisions, violations, and licence suspensions. Consequently, the present investigation had 36 participants complete preliminary questionnaires, memory tasks, workload indices, and four, 4-min simulated driving scenarios to evaluate such impact. It was hypothesised ADHD diagnosis, type of cellular distraction, and traffic density would each differentially and substantively impact driving performance. Results indicated traffic density and distraction type significantly affected the objective driving facets measured, as well as subjective and secondary task performance. ADHD diagnosis directly impacted secondary task performance. Results further showed significant interactions between distraction type and traffic density on both brake pressure and steering wheel angle negatively impacting lateral and horizontal vehicle control. Altogether, these findings provide substantial empirical evidence for the deleterious effect of cellphone use on driving performance. Practitioner summary: This study examined how ADHD diagnosis, traffic density, and distraction type affect driver behaviour. Participants completed driving behaviour questionnaires, memory tasks, workload indices, and driving scenarios. Results showed that ADHD diagnosis impacted secondary task performance, while traffic and distractions significantly impacted driving performance as well secondary task performance and workload.

Using Reinforcement Learning to Improve Airspace Structuring in an Urban Environment

Current predictions on future drone operations estimate that traffic density orders of magnitude will be higher than any observed in manned aviation. Such densities redirect the focus towards elements that can decrease conflict rate and severity, with special emphasis on airspace structures, an element that has been overlooked within distributed environments in the past. This work delves into the impacts of different airspace structures in multiple traffic scenarios, and how appropriate structures can increase the safety of future drone operations in urban airspace. First, reinforcement learning was used to define optimal heading range distributions with a layered airspace concept. Second, transition layers were reserved to facilitate the vertical deviation between cruising layers and conflict avoidance. The effects of traffic density, non-linear routes, and vertical deviation between layers were tested in an open-source airspace simulation platform. Results show that optimal structuring catered to the current traffic scenario improves airspace usage by correctly segmenting aircraft according to their flight routes. The number of conflicts and losses of minimum separation was reduced versus using a single, uniform airspace structure for all traffic scenarios, thus enabling higher airspace capacity.

Ride comfort evaluation of stochastic traffic flow crossing long-span suspension bridge experiencing vortex-induced vibration

The long-span bridge is susceptible to various wind-induced vibrations owing to its high flexibility and low structural damping, among which the vortex-induced vibration (VIV) frequently emerges in recent years resulting in considerable public concerns. Although the VIV is a limited cyclic vibration, it can cause significant negative effects on the ride comfort of vehicles crossing the bridge. Evaluating the ride comfort of vehicles crossing long-span bridges under VIV, therefore, becomes urgent to make decisions on continuing or closing the operations of bridges. In view of this, this paper presents a general ride comfort evaluation procedure for stochastic traffic flow crossing the long-span bridge under VIV, which adequately considers the realistic traffic behavior and the complex interactions among wind, vehicles (traffic flow), and bridge. The developed procedure is validated through the field-monitoring data collected in a recent VIV event of a prototype long-span suspension bridge. On this basis, the ride comfort of vehicles in different traffic flows crossing the prototype bridge under VIV is evaluated through the criteria recommended in the ISO 2631-1 standard based on the overall vibration total value (OVTV). Moreover, the effects of traffic density, traffic proportion, and road roughness on drivers’ ride comfort are studied.

Spatial and temporal memory effects in the Nagel-Schreckenberg model for crowdsourced traffic property determination.

We investigate the spatial and temporal memory effects of traffic density and velocity in the Nagel-Schreckenberg cellular automaton model. We show that the two-point correlation function of vehicle occupancy provides access to spatial memory effects, such as headway, and the velocity autocovariance function to temporal memory effects such as traffic relaxation time and traffic compressibility. We develop stochasticity-density plots that permit determination of traffic density and stochasticity from the isotherms of first- and second-order velocity statistics of a randomly selected vehicle. Specifically, provided ergodicity and stationarity, these stochasticity-density plots permit a direct determination of traffic properties from crowdsourced measurements of velocities of vehicles. We illustrate the predictive prowess of the approach for crowdsourced vehicle speed data collected by anonymous smartphone measurements for the state of Massachusetts, USA, as a powerful alternative to classical traffic property estimates from spatially distributed user counts.

Assessing the Effect of Traffic Density and Cold Airflows on the Urban Air Quality of a City with Complex Topography Using Continuous Measurements

Abstract: The air quality in cities is affected by many factors such as topography, weather, emission sources, etc. In order to assess the influence of these factors on a certain location, continuous measurements of air quality as well as meteorological parameters are essential. The city of Stuttgart in Germany is known for its unique topography and air quality problems making it a very interesting place to investigate the impact of topography and thermal induced wind systems on the air quality. Stuttgart city center is surrounded by hills, elevated plains where cold air masses are produced during nights with autochthonous weather situations. Due to the varying topography, these cold air masses stream through valleys and gullies into the city centre. In this study, a stationary monitoring station was installed at Marienplatz, Stuttgart where the cold airflows from the valleys and gullies are collected together and enter the city, hence making it the optimum location for this investigation. The air pollutants such as nitrogen oxides (NOX, NO, NO2), ozone (O3), carbon monoxide (CO), Particulate Matter (PM) and Black Carbon (BC) were monitored continuously along with the meteorological parameters such as air temperature, relative humidity, air pressure, wind speed, wind direction, precipitation intensity and global radiation from March 2017 till now. In this paper, the results from March 2017 until December 2019 are presented. The influence of wind speed and wind direction on the concentration of pollutants is interpreted using wind and pollution roses. Temperature roses are plotted to understand the effect of cold airflows that bring fresh and cold air into the city. The traffic data for the federal highway passing by the monitoring station are obtained and the pollutant concentrations are related to the traffic, as it is the dominant source of emission in the city. Key words: air quality monitoring, cold airflows, urban air quality, traffic and air quality, air pollution in Stuttgart, continuous measurements, air pollutants

The effect of traffic density on smog pollution: Evidence from Chinese cities

Urban traffic congestion and smog pollution are critical urban development issues. In this study, the influencing mechanism of traffic density on smog pollution in cities is described from the perspectives of direct emissions, spatial agglomeration, and technology spillover effects. Based on an improved STIRPAT model, we examine a panel of 283 prefecture-level cities in China from 2003 to 2015 and find an inverted U-shaped relationship between traffic density and urban smog pollution in large and medium cities and no significant relationship in small cities. Furthermore, the traffic densities in large and medium cities are on the left side of the curve, so direct emissions remain important. The reduction in smog pollution caused by spatial agglomeration and technology spillovers is not sufficient to offset the increase caused by direct emissions. In advancing urbanization, the government should relax its household registration policy that restricts migration to large cities and should avoid any bias in its construction land distribution toward the mainland and small towns. By doing so, the government will further enhance the economic density and scale, shifting the traffic density to the right side of the inverted U-shaped curve so that spatial agglomeration and technology spillover effects can mitigate smog pollution.

Characterizing the effect of traffic density on ambient CO, NO2, and PM2.5 in Tehran, Iran: an hourly land-use regression model

Economic development and population growth in Tehran has increased demand for goods movement and road transportation. This trend has increased mobile source emissions and citizens’ exposure, imposing severe health risks. We used the framework of Land-Use Regression models to quantify the effect of real-time traffic, within buffer distance, on hourly exposure of CO, NO2, and PM2.5. Effect of residential, industrial, and governmental land-use in addition to the effect of pollution sources, such as construction sites and airport were assessed on air pollution. Meteorological variables were also employed to adjust between day variations. R-squared of the models were 38, 27, and 38% for CO, NO2, and PM2.5, respectively. Time-activity diaries can be combined with the developed LUR models to provide detailed exposure estimation for epidemiological studies. Furthermore, capability of simulating short-term effect of different traffic scenarios enables city administrations to evaluate policies aiming to diminish pollution levels, prior to applying them.

What Drives Effective Competition in the Airline Industry? An Empirical Model of City-Pair Market Concentration

Market concentration is a widely recognized metric of effective competition, as it provides a quantification of the relative success of large, mid-sized and smaller firms in the battle for consumers. Concentration has been a public policy issue in the airline industry since deregulation due to the long-standing airport dominance by major carriers, which is a concern that is recurrently intensified by merger announcements. This paper develops an empirical model to examine the evolution of concentration in the airline markets and its possible drivers. We analyze the case of the Brazilian airline industry in which the two major carriers acquired a combined market share of more than 90% in the late 2000s and have experienced a sharp reversion since then. We test the effects of traffic density and route-airport dominance of flight frequencies on the Herfindahl-Hirschman index (HHI) of city-pair markets. Additionally, we investigate the effects of a potential intensification of airport-dominant airlines’ vertical relationships after airport privatization. Our estimated scenarios reveal that a long-run decline in flight dominance produced a ceteris paribus 23% decrease in the estimated HHI. Additionally, market expansion induced an extra 4% decline in concentration. In contrast, ownership change at privatized airports raised concentration by 9%. Our results also suggest that fighting market concentration with the entry facilitation of new low-cost carriers at primary airports may be an effective policy.

Environmental determinants of celeration behaviour

Celeration (speed change) behaviour of drivers has been posited to be the best predictor of their traffic accident involvement. The origins of this behaviour, however, have not been specified. A model is therefore introduced, where celeration is partly due to the individual disposition of the driver (i.e., driving style), and partly to the environment (road layout, rules and traffic density). Three measurement problems for celeration were studied; the effect of traffic density, of regular versus irregular routes, and weight of the vehicle (loaded/unloaded) on celeration behaviour. Two small samples of truck drivers in Sweden were measured for several months each. There was a strong effect of vehicle load, with behaviour being more cautious with increased weight. Driving on different roads also yielded differences in behaviour, although the design used did not permit conclusions about what caused these. Traffic volume was not found to have any reliable effect on celeration.

The Effect of Traffic Density on Lead Contents in Roadside Soils: An Analysis of Published Data

Data from eight published studies were combined to show that the influence of traffic density on Pb contents in roadside soils increases with proximity to the road.

Perspective and Coplanar Cockpit Displays of Traffic Information: Implications for Maneuver Choice, Flight Safety, and Mental Workload

In 3 experiments, we examined maneuver choice, flight safety, and mental workload across 3-dimensional (3D) perspective and 2-dimensional coplanar cockpit displays of traffic information in a free-flight simulation. In Experiment 1 (30 pilots), we examined dimensionality issues; in Experiments 2 and 3 (18 pilots each), we examined the effects of traffic density, dimensionality, and vertical profile orientation. Collectively, these data may be modeled by trade-offs between the display types: The coplanar suite suffers from scanning-related integration that increases with conflict density; the 3D display suffers from perceptual ambiguity. This research informs our understanding of how displays modulate performance in free-flight environments.

Effect of traffic density on heavy metal content of soil and vegetation along roadsides in Osun state, Nigeria

Effect of traffic density on heavy metal content of soil and vegetation along roadsides in Osun state, Nigeria

Determination of Pb and Cd in road dusts over the period in which Pb was removed from petrol in the UK.

It is commonly agreed that automobile exhaust has been the most important source of Pb pollution in urban areas, and that Cd may come from wear and tear of tyres. This study evaluates the fall in Pb concentrations in road dusts in Manchester as a consequence of the removal of Pb from petrol in January 2000. In the work presented here a slurry graphite furnace atomic absorption methodology for the determination of Pb and Cd in road dusts has been developed and is compared with an acid digestion method in terms of efficiency. The reproducibility and accuracy of the results obtained by acid digestion and the slurry method have been studied and a certified reference material CRM 038 was analysed to confirm the reliability of the proposed methods. Different factors were evaluated throughout this work including: (i) the effect of traffic density on Pb and Cd levels in road dust samples collected weekly during the period of May 1999 until September 2000; (ii) comparison between the Pb and Cd levels in a busy road and a residential street; (iii) the effect of distance from the source on Pb and Cd levels; The results of these experiments show a reduction in Pb levels over the sampling period. The relationship between road dust particle size and Pb and Cd concentration was also investigated in the 4-250 microns size range using the slurry method, showing that there is a relationship between metal concentration and particle size; the highest concentrations being for the smallest particle size.