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Evaluating Cycling Routes in a Bicycle SimulatorBerghoefer, Frauke L., Vollrath, Mark 02 January 2023 (has links)
Although cycling becomes more and more popular, many people are still deterred from cycling by various aspects including a lack of perceived safety [1 ]. To o:ffer preferable infrastructure and, hence, to better promote cycling. it is therefore crucial to examine how cyclists evahmte their routes, and to figure out what makes an infrastructure seem unsafe or unattractive.
Some studies have already identified i.mportant route criteria 1ike safety or comfort, and have connected them to certain route attributes. High traffic volumes and cycling on no or poor cycling facilities are experienced as stressful by cyclists [2], [3], and they try to avoid these routes in order to reduce possible interactions with motor vehicles [4]. In contrast, a separated cycling facility, low speed, and low traflic volumes are evaluated as safe and stress-ftee [2], [5]. Furthennore, cyclists prefer oomfortable routes, that is, routes with low gradient and few stops and traffic lights as weil as attractive routes with a green and pleasant su:rrounding [6], [7]. Most ofthe studies investigated those criteria deductively, that is, the researchers analyzed the results theorydriven and in terms of predetermined criteria. In a previous study, we examined them in an inductive and qualitative approach that allowed us to collect criteria with the participants' individual wording and content [8]. We found that cyclists evaluate their route attributes in terms of Mental Comfort, possible interactions with other road users, Physical Comfort, the Base of Use of the infrastructure, and the pleasanlness of the surrounding. Safety and stress were found to be sub-aspects of Mental Comfort, whereas Interaction was associated with attention and concentration due to other road users. The term comfort, however, was mentioned
by participants only in terms of physical comfort. The aim of the present study is to validate these evaluation criteria found in our previous study, and to connect
them to certain route attributes using the experimental approach of a bicycle simulator in combination with qualitative surveys.
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GIS-based Episode Reconstruction Using GPS Data for Activity Analysis and Route Choice Modeling / GIS-based Episode Reconstruction Using GPS DataDalumpines, Ron 26 September 2014 (has links)
Most transportation problems arise from individual travel decisions. In response, transportation researchers had been studying individual travel behavior – a growing trend that requires activity data at individual level. Global positioning systems (GPS) and geographical information systems (GIS) have been used to capture and process individual activity data, from determining activity locations to mapping routes to these locations. Potential applications of GPS data seem limitless but our tools and methods to make these data usable lags behind. In response to this need, this dissertation presents a GIS-based toolkit to automatically extract activity episodes from GPS data and derive information related to these episodes from additional data (e.g., road network, land use).
The major emphasis of this dissertation is the development of a toolkit for extracting information associated with movements of individuals from GPS data. To be effective, the toolkit has been developed around three design principles: transferability, modularity, and scalability. Two substantive chapters focus on selected components of the toolkit (map-matching, mode detection); another for the entire toolkit. Final substantive chapter demonstrates the toolkit’s potential by comparing route choice models of work and shop trips using inputs generated by the toolkit.
There are several tools and methods that capitalize on GPS data, developed within different problem domains. This dissertation contributes to that repository of tools and methods by presenting a suite of tools that can extract all possible information that can be derived from GPS data. Unlike existing tools cited in the transportation literature, the toolkit has been designed to be complete (covers preprocessing up to extracting route attributes), and can work with GPS data alone or in combination with additional data. Moreover, this dissertation contributes to our understanding of route choice decisions for work and shop trips by looking into the combined effects of route attributes and individual characteristics. / Dissertation / Doctor of Philosophy (PhD)
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