196 research outputs found

    Assessing planning decisions by activity type during the scheduling process

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    Existing activity-based models still make assumptions about scheduling decision processes that are not well-informed by empirical evidence. In this article, a step forward is taken to better understand the activity-scheduling process and to improve activity-based models. In particular, different planning decision mechanisms depending on several activity type classifications are explored. First, models describing the planning of several aggregate activity types are considered. For these activities, three planning decisions are studied: location, planning time horizon and rescheduling. The 'with whom' planning decision is also studied when subtypes of recreational/entertainment activities are investigated in depth. Significant differences are found in modelling results for each activity type and subtype and each planning decision. These results confirm the existence of different mechanisms underlying the activity-travel decision process when activity types and subtypes are considered. Important conclusions related to the improvement of microsimulation models are highlighted.Ruiz Sánchez, T.; Roorda, MJ. (2011). Assessing planning decisions by activity type during the scheduling process. Transportmetrica. 7(6):417-442. doi:10.1080/18128602.2010.520276S4174427

    Interplay between telecommunications and face-to-face interactions - a study using mobile phone data

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    In this study we analyze one year of anonymized telecommunications data for over one million customers from a large European cellphone operator, and we investigate the relationship between people's calls and their physical location. We discover that more than 90% of users who have called each other have also shared the same space (cell tower), even if they live far apart. Moreover, we find that close to 70% of users who call each other frequently (at least once per month on average) have shared the same space at the same time - an instance that we call co-location. Co-locations appear indicative of coordination calls, which occur just before face-to-face meetings. Their number is highly predictable based on the amount of calls between two users and the distance between their home locations - suggesting a new way to quantify the interplay between telecommunications and face-to-face interactions

    A method to evaluate equitable accessibility: combining ethical theories and accessibility-based approaches

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    In this paper, we present the case that traditional transport appraisal methods do not sufficiently capture the social dimensions of mobility and accessibility. However, understanding this is highly relevant for policymakers to understand the impacts of their transport decisions. These dimensions include the distribution of mobility and accessibility levels over particular areas or for specific population groups, as well as how this may affect various social outcomes, including their levels of participation, social inclusion and community cohesion. In response, we propose a method to assess the socially relevant accessibility impacts (SRAIs) of policies in some of these key dimensions. The method combines the use of underlying ethics principles, more specifically the theories of egalitarianism and sufficientarianism, in combination with accessibility-based analysis and the Lorenz curve and Gini index. We then demonstrate the method in a case study example. Our suggestion is that policymakers can use these ethical perspectives to determine the equity of their policies decisions and to set minimum standards for local transport delivery. This will help them to become more confident in the development and adoption of new decision frameworks that promote accessibility over mobility and which also disaggregate the costs and benefits of transport policies over particular areas or for specific under-served population groups

    "If only I had taken the other road...": Regret, risk and reinforced learning in informed route-choice

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    This paper presents a study of the effect of regret on route choice behavior when both descriptional information and experiential feedback on choice outcomes are provided. The relevance of Regret Theory in travel behavior has been well demonstrated in non-repeated choice environments involving decisions on the basis of descriptional information. The relation between regret and reinforced learning through experiential feedbacks is less understood. Using data obtained from a simple route-choice experiment involving different levels of travel time variability, discrete-choice models accounting for regret aversion effects are estimated. The results suggest that regret aversion is more evident when descriptional information is provided ex-ante compared to a pure learning from experience condition. Yet, the source of regret is related more strongly to experiential feedbacks rather than to the descriptional information itself. Payoff variability is negatively associated with regret. Regret aversion is more observable in choice situations that reveal risk-seeking, and less in the case of risk-aversion. These results are important for predicting the possible behavioral impacts of emerging information and communication technologies and intelligent transportation systems on travelers' behavior. © 2012 Springer Science+Business Media, LLC

    Exploring the potential of phone call data to characterize the relationship between social network and travel behavior

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    [EN] Social network contacts have significant influence on individual travel behavior. However, transport models rarely consider social interaction. One of the reasons is the difficulty to properly model social influence based on the limited data available. Non-conventional, passively collected data sources, such as Twitter, Facebook or mobile phones, provide large amounts of data containing both social interaction and spatiotemporal information. The analysis of such data opens an opportunity to better understand the influence of social networks on travel behavior. The main objective of this paper is to examine the relationship between travel behavior and social networks using mobile phone data. A huge dataset containing billions of registers has been used for this study. The paper analyzes the nature of co-location events and frequent locations shared by social network contacts, aiming not only to provide understanding on why users share certain locations, but also to quantify the degree in which the different types of locations are shared. Locations have been classified as frequent (home, work and other) and non-frequent. A novel approach to identify co-location events based on the intersection of users' mobility models has been proposed. Results show that other locations different from home and work are frequently associated to social interaction. Additionally, the importance of non-frequent locations in co-location events is shown. Finally, the potential application of the data analysis results to improve activity-based transport models and assess transport policies is discussed.The authors would like to thank the anonymous reviewers for their valuable comments and suggestions to improve the quality of the paper. The research leading to these results has received funding from the European Union Seventh Framework Programme FP7/2007-2013 under grant agreement no 318367 (EUNOIA project) and no 611307 (INSIGHT project). The work of ML has been funded under the PD/004/2013 project, from the Conselleria de Educacion, Cultura y Universidades of the Government of the Balearic Islands and from the European Social Fund through the Balearic Islands ESF operational program for 2013-2017.Picornell Tronch, M.; Ruiz Sánchez, T.; Lenormand, M.; Ramasco, JJ.; Dubernet, T.; Frías-Martínez, E. (2015). Exploring the potential of phone call data to characterize the relationship between social network and travel behavior. Transportation. 42(4):647-668. https://doi.org/10.1007/s11116-015-9594-1S647668424Ahas, R., Aasa, A., Silm, S., Tiru, M.: Daily rhythms of suburban commuters’ movements in the tallinn metropolitan area: case study with mobile positioning data. Transp. Res. 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