Dimitrios Efthymiou

Associations Generation in Synthetic Population for Transportation Applications: Graph-Theoretic Solution

The generation of synthetic populations through simulation methods is an important research topic and has a key application in agent-based modeling of transport and land use. The next step in this research area is the generation of complete synthetic households; this research area requires some way to associate synthetic persons with household positions. This work formulated the person to the position matching problem as a bipartite graph matching and tested two models for determining match utility with data from the 2000 Swiss census. The functions tested were both multinomial logit models, one based on the household size attribute and the other on household type. Synthetic persons were matched into the head position of real households, and then the remaining population was used to run a second match with a separately calibrated version of the size choice model for the spouse position. This method is a long list-based approach that keeps the original marginal consistent. Results show that the size choice model returns the best results for head and spouse positions, although both models provide a good match quality as measured by the distributions of individual attributes in real and matched populations as well as the distributions of unique attribute combinations. Possible extensions include matching to other household positions and evaluating the performance of these synthetic households in modeling applications.

Localization and Driving Behavior Classification with Smartphone Sensors in Direct Absence of Global Navigation Satellite Systems

Global navigation satellite systems have tremendous impact and potential in the development of intelligent transportation systems and mobility services and are expected to deliver significant benefits, including increased capacity, improved safety, and decreased pollution. However, there are situations in which there might not be direct location information about vehicles, for example, in tunnels and in indoor facilities such as parking garages and commercial vehicle depots. Various technologies can be used for vehicle localization in these cases, and other sensors that are currently available in most modern smartphones, such as accelerometers and gyroscopes, can be used to obtain information directly about the driving patterns of individual drivers. The objective of this research is to present a framework for vehicle localization and modeling of driving behavior in indoor facilities or, more generally, facilities in which global navigation satellite system information is not available. Localization technologies and needs are surveyed and the adopted methodology is described. The case studies, which use data from multiple types of sensors (including accelerometers and gyroscopes from two smartphone platforms as well as two reference platforms), provide evidence that the opportunistic smart-phone sensors can be useful in identifying obstacles (e.g., speed humps) and maneuvers (e.g., U-turns and sharp turns). These data, when cross-referenced with a digital map of the facility, can be useful in positioning the vehicles in indoor environments. At a more macroscopic level, a methodology is presented and applied to determine the optimal number of clusters for the drivers’ behavior with a mix of suitable indexes.

Investigation of Lane Flow Distribution on Hard Shoulder Running Freeways

In response to an impending demand growth at an existing reactive managed lane system and to provide a timely and more effective temporary hard shoulder activation, this paper presents the development of short-term prediction models. A lane-oriented attribute—namely, the left-lane flow distribution ratio—is introduced to ameliorate the system by capturing the forthcoming stream dynamics and reconfiguring it to be proactive. To assess the impact on the networks performance of implementing a system for hard shoulder running, an exploratory analysis was performed on the basis of data acquired by seven radar sensors located every 500 m along a Swiss freeway section that was not affected by incoming or exiting traffic. A locally weighted regression was employed to provide more accurate insight into traffic behavior by comparing observations derived during the regular operation of the system and a period in which it was suspended, with respect to seasonality patterns. To describe the impending stream motion by examining different time–volume clusters (off-peak and peak hours), two prediction models were specified according to the time range. The preliminary results of the study for several prediction horizons demonstrate an acceptable prediction uncertainty. The hard shoulder activation prediction confirms the analysis of the findings of this research with regard to the impact on operations.

Built Environment, Travel Attitudes and Travel Behaviour: Quasi-Longitudinal Analysis of Links in the Case of Greeks Relocating from US to Greece

In this study, the possible causal links between the built environment, travel attitudes and travel behaviour of people that have moved between totally different urban and transportation contexts were investigated. A quasi-longitudinal design was developed to collect data about the perceived neighbourhood characteristics, neighbourhood preferences, travel attitudes and changes in car, walking and bicycle usage of 51 Greeks who relocated from the US to Greece. Variable reduction techniques were applied prior to developing our models because of the small sample size. The results of this study offer support for a causal relationship between the built environment and travel behaviour identified in the existing literature. For instance, longer travel time to city center was associated with higher car use, higher density neighbourhoods and increased accessibility to local amenities were associated with increased bike use and better access to a district shopping center was associated with more walking after relocation. Our results also showed that in contexts like Greece, where transport infrastructures are not adequately developed, lack of safe bike conditions and easy access to public transportation are important determinants of bicycle use and walking. Thus, according to our results, promoting sustainable mobility in contexts like Greece would require not only enhancing accessibility through relocation of activities, but also by improving infrastructures for public transport, bicycle and walking.

Measuring the Effects of Economic Crisis on Users’ Perceptions of Public Transport Quality

Research was conducted to measure the effects of the economic crisis on public transport quality, user satisfaction, and transit demand. The survey used in this research extended a research effort that began in 2008; the survey aimed to analyze the variability of users’ satisfaction within different public transport systems. The survey was conducted in Athens, Greece, from November 2012 to January 2013, during the peak of the countrys economic recession. The content of the questionnaire that was used for the needs of the survey was similar to that of 2008 so that the results would be comparable. Passengers were asked to rate how important a series of metro and bus attributes were, their level of satisfaction with those attributes, their overall satisfaction with the main public transport operator they used, and the increase or decrease of their individual demand for public transport. A factor analysis was first performed to identify potential common patterns between the individual importance attributes. Ordered logit models were then estimated with the overall satisfaction as a response variable. Results of the analysis were then compared with the findings of the earlier (precrisis) research; this comparison revealed interesting adaptations in users’ perceptions of the public transport operators’ quality. Moreover, a hybrid choice and latent variable model was estimated to explore the overall satisfaction of the respondents. Finally, a demand model was developed; this model revealed the characteristics that led to the increase (or decrease) of public transit demand in the past 5 years.

Modeling the impact of large-scale transportation infrastructure development on land cover

Abstract Transportation infrastructure and urban development are tightly connected and interact with each other. The objective of this paper is to measure the impact of large-scale transportation infrastructure locations on land cover. Spatial econometric models that link the impact of transportation infrastructure onto the urban evolution have been used with panel data (multiple time points). Land cover information was derived individually from two Landsat TM images (1984 and 2010) by applying a semi-automatic object-based image analysis (OBIA) approach, resulting in six generalized thematic categories. Data from multiple databases have been collected and cross-referenced. The study area is the Athens metropolitan area, Greece, where, during the last few decades, crucial transportation infrastructure has been developed and significant urbanization has been observed. Moreover, a fixed effects model has been developed for a study area, providing additional information for the differences across municipalities. The results of this research provide evidence toward the quantification of the impact of major road transportation infrastructure in urban development and can have applications in other areas that have not been yet fully developed.