Ioannis Politis

URBAN ROAD PRICING AND SUSTAINABLE TRANSPORTATION SYSTEMS: THE THESSALONIKI CENTRAL AREA CASE

Urban road pricing involves direct charging of drivers for the use of the road network, usually during peak periods. The main objectives for the introduction of a road pricing scheme, in a congested city network, include reduction of delays, environmental improvement and revenue increase. These objectives are closely associated with the concepts of sustainable mobility in urban areas with respect to social equity, economic effi ciency and environmental responsibility. This paper attempts to estimate the potential interrelation between urban road pricing and sustainable mobility management policy by modelling the impacts (traffi c network operation, environmental indices and revenue) of a hypothetic implementation of cordon tolls in the city centre of Thessaloniki (situated in northern Greece), which faces severe traffi c and environmental problems. The evaluation was carried out using the SATURN traffi c simulation model, which was developed at the Institute for Transport Studies, University of Leeds, UK. SATURN is a well-known transport analysis model which is widely used. In order to assess the impacts of traffi c scenarios, the software runs a simulation-assignment procedure simultaneously using commonly accepted algorithms that originate from transport theory such as all-or-nothing assignment, Wardorp’s principles. The road network used in SATURN for the purposes of this research consists of 813 nodes and 293 zones. Furthermore, an analysis was carried out regarding the contribution of the extracted model indicators to the establishment of an overall strategy concerning sustainable transportation and mobility in Thessaloniki’s central area. Various scenarios were examined depending on the year of the analysis and the alternative transport mode in use. These scenarios were compared with different road charging scenarios. Parameters such as traffi c volumes, speed, vehicle emissions were estimated. A comparative analysis of these values in conjunction with the defi nition of sustainable mobility and development in general was performed, concluding that innovative measures can reassign the trip patterns in urban areas, thereby improving the transport system operation in terms of sustainability. Undoubtedly, the use of powerful assessment tools such as SATURN for the evaluation of the impacts of various Transportation Demand Management measures like road charging will provide valuable assistance to policy makers and the transportation planners involved in the specifi c process.

Ordinal and binary logistic logit models for examination of behavioral, infrastructure and perception factors influencing biking

In the context of this paper, two logistic regression logit models are developed in order to examine a number of parameters (behavioral, infrastructure and perceptional) that might have an effect on biking potential. Almost 200 bicyclists were interviewed at the city of Thessaloniki, Greece and two models were built; an ordinal logistic model measuring the frequency of biking and a binary logistic model estimating the possibility of perceiving the bicycle road of the city as attractive or not. The ordinal model, indicated that the bicyclist aged between 25–39 years old have less possibilities to stop biking. Additionally, from the odd ratio calculation it was found that people who state that are very well informed about the benefits of biking are more unlike by 65% to use seldom the bicycle road compare to those that state that are just enough informed. Finally, amongst other important outcomes, the binary model predicted that only 7% of those who say that the bike road is safe will not perceived the bicycle road as attractive; the respective proportion for those who say that bike road is not safe is 17%.

Applying Behavior Change Theory to Predict Travel Behavior of University Commuters

Selecting the right alternatives to an existing travel mode for commuting to a major trip generator at the center of a metropolitan area is often a complex project. In this chapter, the Aristotle University of Thessaloniki, Greece is the major trip generator in a study that compares the predictions of two approaches, both of which use discrete choice modeling, regarding the number of commuters who are willing to change travel mode if the right alterative is offered to them. The first is the conventional approach that, using travel cost and travel time as the main travel mode choice determinants, is applied to a selected (aggregate) sample of the commuter population. The second approach uses the same determinants but stratifies the sample into four strata according to the behavioral change stage to which the commuters belong. The model results indicate that the predicted travel mode choice behavior differs significantly among the persons in the sample depending on which behavioral change stage they are in. This study suggests that transport policy makers might better devise targeted interventions to maximize the positive socioeconomic and environmental impacts of travel mode alternatives.