Pavement evaluation : phase I, pavement evaluation equipment /

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Analysis of road potential and bottlenecks based on operating speed

Vehicle detectors have been installed at approximately every 300 meters on each lane on Tokyo metropolitan expressway. Various traffic data such as traffic volume, average speed and time occupancy are collected by vehicle detectors. We can understand traffic characteristics of every point by comparing traffic data collected at consecutive points. In this study, we focused on average speed, analyzed road potential by operating speed during free-flow conditions, and identified latent bottlenecks. Furthermore, we analyzed effects for road potential by the rainfall level and day of the week. It’s expected that this method of analysis will be utilized for installation of ITS such as drive assist, estimation of parameters for traffic simulation and feedback to road design as congestion measures.

Are safety-related features of the road environment associated with smaller declines in physical activity among youth?

This study examined how objective measures of the local road environment related to safety were associated with change in physical activity (including active transport) among youth. Few longitudinal studies have examined the impact of the road environment on physical activity among children/adolescents in their neighborhoods. Participants were children aged 8–9 years (n=170) and adolescents aged 13–15 years (n=276) in 2004. Data were collected in 2004 and 2006 during followup of participants recruited initially in 2001 from 19 primary schools in Melbourne, Australia. Walking/cycling to local destinations was parent-reported for children and self-reported by adolescents. Moderate-to-vigorous physical activity (MVPA) during nonschool hours was recorded using accelerometers. Road environment features in each participant’s neighborhood (area within 800 m radius of their home) were measured objectively using a Geographical Information System. Linear regression analyses examined associations between road features and changes in active transport (AT) and MVPA over 2 years. Children’s AT increased but MVPA levels decreased in both age groups; on average, younger girls recorded the greatest declines. The number of traffic/pedestrian lights was associated with ΔAT among younger girls (B=0.45, p=0.004). The total length of walking tracks (in meters) was associated with ΔAT among younger girls (B=0.0016, p=0.015) and adolescent girls (B=0.0016, p=0.002). For adolescent boys, intersection density was associated with ΔAT (B=0.03, p=0.030). Slow points were associated with ΔMVPA among younger boys before school (B=1.55, p=0.021), while speed humps were associated with ΔMVPA among adolescent boys after school (B=0.23, p=0.015). There were many associations for adolescent girls: for example, the total length of local roads (B=0.49, p=0.005), intersection density (B=0.05, p=0.036), and number of speed humps (B=0.33, p=0.020) were associated with ΔMVPA during nonschool hours. Safety-related aspects of the built environment are conducive to physical activity among youth and may help stem age-related declines in physical activity. Passive road safety interventions may promote AT and physical activity among less active girls, in particular.

Air pollution levels measured at traffic hot spots : Brisbane urban corridor study

Air pollution levels were monitored continuously over a period of 4 weeks at four sampling sites along a busy urban corridor in Brisbane. The selected sites were representative of industrial and residential types of urban environment affected by vehicular traffic emissions. The concentration levels of submicrometer particle number, PM2.5, PM10, CO, and NOx were measured 5-10 meters from the road. Meteorological parameters and traffic flow rates were also monitored. The data were analysed in terms of the relationship between monitored pollutants and existing ambient air quality standards. The results indicate that the concentration levels of all pollutants exceeded the ambient air background levels, in certain cases by up to an order of magnitude. While the 24-hr average concentration levels did not exceed the standard, estimates for the annual averages were close to, or even higher than the annual standard levels.

Quantification of motor vehicle emission factors from on road measurements

Assessment and prediction of the impact of vehicular traffic emissions on air quality and exposure levels requires knowledge of vehicle emission factors. The aim of this study was quantification of emission factors from an on road, over twelve months measurement program conducted at two sites in Brisbane: 1) freeway type (free flowing traffic at about 100 km/h, fleet dominated by small passenger cars - Tora St); and 2) urban busy road with stop/start traffic mode, fleet comprising a significant fraction of heavy duty vehicles - Ipswich Rd. A physical model linking concentrations measured at the road for specific meteorological conditions with motor vehicle emission factors was applied for data analyses. The focus of the study was on submicrometer particles; however the measurements also included supermicrometer particles, PM2.5, carbon monoxide, sulfur dioxide, oxides of nitrogen. The results of the study are summarised in this paper. In particular, the emission factors for submicrometer particles were 6.08 x 1013 and 5.15 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd respectively and for supermicrometer particles for Tora St, 1.48 x 109 particles per vehicle-1 km-1. Emission factors of diesel vehicles at both sites were about an order of magnitude higher than emissions from gasoline powered vehicles. For submicrometer particles and gasoline vehicles the emission factors were 6.08 x 1013 and 4.34 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively, and for diesel vehicles were 5.35 x 1014 and 2.03 x 1014 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively. For supermicrometer particles at Tora St the emission factors were 2.59 x 109 and 1.53 x 1012 particles per vehicle-1 km-1, for gasoline and diesel vehicles, respectively.