Advanced impact integration platform for cooperative road use

In order to improve networks efficiency, a considerable number of studies has been addressing the potential of eco-friendly assignment solutions as alternative approaches to reduce emissions and/or fuel use. So far the majority of studies generally assumes that the most eco-friendly solutions are the ones that minimize the absolute amount of emissions produced along a certain trip. In this work a platform based on both empirical GPS data and microscopic simulation models of traffic, emissions, noise, and road safety was developed to examine in depth 4 routes of an origin-destination pair over a Portuguese city. In addition to the integrated externalities assessment based on state of the art techniques, a novelty of this work was the preliminary inclusion of social criteria in defining sustainable assignment solutions. This paper provides new insights about sustainable traffic management issues and addresses multiple novel route choice indicators. Specifically we found that the relative variation of the individual costs and total pollution produced among 4 routes varies to a factor of 1.4 while the variation of the potentially exposed population ranges up to a factor of 10. The main results confirm the need to take into account real-time urban activity patterns in order to effectively implement sustainable traffic management measures

Use of Multisource Global Positioning System Data to Characterize Multiday Driving Patterns and Fuel Usage in a Large Urban Region

The paper describes the use of GPS data obtained from both commercial and project-specific sources to examine the travel behavior and fuel consumption patterns of drivers over a three-day period in Gauteng Province, South Africa. Data for commercial (truck and light delivery vehicle) traffic are obtained from a commercial fleet management provider, which continuously tracks the movements of 42,000 vehicles. Data for private car users come from a panel of 720 drivers, whose multiday driving activity is tracked using mobile passive GPS loggers. We analyze and compare the driving behavior of the two driver populations in terms of total distance travelled, spatial patterns (e.g. the amount of travel on different road types) and temporal variations (e.g. variations across time of day and across multiple days). The detailed nature of GPS data also permits the estimation of fuel consumption at a very disaggregate level (by link and time of day), and the identification of differences between user groups, which have significant implications for transport and energy policy. We introduce a new indicator, the recovery ratio, to assess the relationship of fuel use to distance travelled on different classes of roads, to help identify equity distortions across user groups. Lastly, we comment on research needs related to the collection and integration of GPS data from multiple sources for model calibration and program evaluation.South African National Roads Agency Ltd. (SANRAL)http://trb.metapress.com/content/0361-1981/hb201