Showing papers by "Marcela Munizaga published in 2016"
TL;DR: In this article, the authors describe a successful experience of collaboration between academia and the public transport authority to develop tools based on passive data processing for public transport policy and planning in Santiago, Chile.
46 citations
TL;DR: The key conclusion of the workshop is that, although much progress has been made in utilizing big data to improve transportation planning and operations, much remains to be done, both in terms of developing further analysis tools and use cases of big data and of disseminating best practices so that they are adopted across the industry.
16 citations
TL;DR: Results of the application show that the expected in-vehicle time savings of a median busway might be reduced by access time losses due to increased walking distances and road crossing delays, pointing out to the need of including a wider set of impacts when studying the benefits of median busways, beyond in- vehicle time savings only.
Abstract: This paper presents a general framework to estimate the bus user time benefits of a median busway including the effects on travel time and access time. Unlike previous models, we take into account the effects of geometry and the interaction with the demand structure. Models for predicting the bus in-vehicle time benefits of a median dual carriageway busway against mixed traffic condition on 2 and 3 lanes roads are estimated using data from a case study in Santiago (Chile), using a bus travel time model empirically estimated and considering different base case situations, including mixed traffic operations and bus lanes. Results of the application show that the expected in-vehicle time savings of a median busway might be reduced by access time losses due to increased walking distances and road crossing delays. Also, that net time benefits can vary significantly according to the base situation and the structure of demand considered. These findings point out to the need of including a wider set of impacts when studying the benefits of median busways, beyond in-vehicle time savings only. The empirical work presented here is completely based on passive data coming from GPS and smartcards, what makes easier and cheaper to conduct this type of analysis as well as to do it with a comprehensive scope at an early stage of the development of a BRT project. This framework can be extended to other types of dedicated bus lanes provided that a corresponding bus travel time savings model is available.
15 citations