Traffic noise abatement: How different pavements, vehicle speeds and traffic densities affect annoyance levels

In this paper, annoyance ratings from traffic noise recorded on cobblestones, dense asphalt, and open asphalt rubber pavements are assessed with regard to car speeds and traffic densities. It was found that cobblestones pavements are the most annoying; also while open asphalt rubber pavement imposes less annoyance than dense asphalt it is not significantly different. Higher car speeds always lead to greater annoyance, as does higher traffic densities. LAeq and LAmax correlate well with annoyance, but loudness is the best predictor. Roughness and sharpness exhibit inconsistent interactions.     

Modelling the impact of weather conditions on active transportation travel behaviour

Three weather sensitive models are used to explore the relationship between weather and home-based work trips within the City of Toronto, focusing on active modes of transportation. The data are restricted to non-captive commuters who have the option of selecting among five basic modes of auto driver, auto passenger, transit, bike and walk. Daily trip rates in various weather conditions are assessed. Overall, the results confirm that impact of weather on active modes of transportation is significant enough to deserve attention at the research, data collection and planning levels.     

Identifying optimal data aggregation interval sizes for link and corridor travel time estimation and forecasting

With the recent increase in the deployment of ITS technologies in urban areas throughout the world, traffic management centers have the ability to obtain and archive large amounts of data on the traffic system. These data can be used to estimate current conditions and predict future conditions on the roadway network. A general solution methodology for identifying the optimal aggregation interval sizes for four scenarios is proposed in this article: (1) link travel time estimation, (2) corridor/route travel time estimation, (3) link travel time forecasting, and (4) corridor/route travel time forecasting. The methodology explicitly considers traffic dynamics and frequency of observations. A formulation based on mean square error (MSE) is developed for each of the scenarios and interpreted from a traffic flow perspective. The methodology for estimating the optimal aggregation size is based on (1) the tradeoff between the estimated mean square error of prediction and the variance of the predictor, (2) the differences between estimation and forecasting, and (3) the direct consideration of the correlation between link travel time for corridor/route estimation and forecasting. The proposed methods are demonstrated using travel time data from Houston, Texas, that were collected as part of the automatic vehicle identification (AVI) system of the Houston Transtar system. It was found that the optimal aggregation size is a function of the application and traffic condition.

The impact of climate change and weather on transport: An overview of empirical findings

This paper presents a survey of the empirical literature on the effects of climate change and weather conditions on the transport sector. Despite mixed evidence on many issues, several patterns can be observed. On a global scale especially shifts in tourism and agricultural production due to increased temperatures may lead to shifts in passenger and freight transport. The predicted rise in sea levels and the associated increase in frequency and intensity of storm surges and flooding incidences may furthermore be some of the most worrying consequences of climate change, especially for coastal areas. Climate change related shifts in weather patterns might also cause infrastructure disruptions. Clear patterns are that precipitation affects road safety by increasing accident frequency but decreasing severity. Precipitation also increases congestion, especially during peak hours. Furthermore, an increased frequency of low water levels may considerably increase costs of inland waterway transport. Despite these insights, the net impact of climate change on generalised costs of the various transport modes are uncertain and ambiguous, with a possible exception for inland waterway transport.     

Severity of injury resulting from pedestrian–vehicle crashes: What can we learn from examining the built environment?

This paper examines the impact of personal and environmental characteristics on severity of injuries sustained in pedestrian–vehicle crashes using a generalized ordered probit model. The data covers 2000–2004 of pedestrian–vehicle crashes taken from police incident reports for Baltimore City and supplemented with local land use, urban form and transportation information specific to the individual crash locations. The results on personal and behavioral variables confirm previous findings. Women pedestrians involved in crashes tend to be injured less frequently than their male counterparts; children have an increased likelihood of sustaining injuries and older persons are more likely to be fatally injured. Pedestrians who cross against the traffic signal, are not in a crosswalk and are involved in a crash after dark are associated with greater injury risk. Of the built environment policy variables of interest, transit access and greater pedestrian connectivity, such as central city areas, are significant and negatively associated with injury severity. These results suggest that the environmental conditions should be given more scrutiny and be an important consideration when evaluating and planning for pedestrian safety.     

Turn taking behavior in dual earner households with children: a focus on escorting routines

Transportation - This article discusses results of a study on turn taking behavior in escorting children in dual-earner households. Using a multinomial logit model, the probability of different...     

Prevalence of alternative processing rules in the formation of daily travel satisfaction in the context multi-trip,multi-stage,multi-attribute travel experiences

Transportation - Requesting respondents to provide satisfaction ratings for multi-stage trips or daily travel experiences implies they have to value each stage, respectively trip, based on memory...     

Understanding urban mobility patterns from a spatiotemporal perspective: daily ridership profiles of metro stations

Transportation - Smart card data derived from automatic fare collection (AFC) systems of public transit enable us to study resident movement from a macro perspective. The rhythms of traffic...     

Investigating the capacity of continuous household travel surveys in capturing the temporal rhythms of travel demand

Transportation - Continuous household travel surveys have been identified as a potential replacement for traditional one-off cross-sectional surveys. Many regions around the world have either...