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http://hdl.handle.net/1942/28310
Title: | Path complexity for observed and predicted bicyclist routes | Authors: | Koch, Thomas KNAPEN, Luk Dugundji, Elenna |
Issue Date: | 2019 | Publisher: | Elsevier | Source: | Shakshuki, Elhadi (Ed.). The 10th International Conference on Ambient Systems, Networks and Technologies (ANT 2019) / The 2nd International Conference on Emerging Data and Industry 4.0 (EDI40 2019) / Affiliated Workshops, Elsevier,p. 393-400 | Series/Report: | Procedia Computer Science | Series/Report no.: | 151 | Abstract: | Everyday route choices made by bicyclists are known to be more difficult to explain than vehicle routes, yet prediction of these choices is essential for guiding infrastructural investment in safe cycling. In this paper we study how the concept of route complexity can help generate and analyze plausible choice sets in the demand modeling process. % Defining route complexity to be the minimal number of shortest path segments that form a given complete route, we characterize the routes bicyclists take in large set of GPS traces gathered voluntarily by persons traveling to everyday activities at work, school, friends, etc. The complexity of a given path in a graph is the minimum number of shortest paths that is required to specify that path. Complexity is a path attribute which is considered to be important for route choice in a similar way as the number of left turns, the number of speed bumps, distance and other. The complexity was determined for a large set of observed routes and for routes in the generated choice sets for the corresponding origin-destination pairs. The respective distributions seem to significantly differ so that the choice sets do not reflect the traveler preferences. This paper looks at how the observed routes compare to routes generated by Breadth First Search Link Elimination and Double Stochastic Generation Function method. | Keywords: | Route choice generation; choice sets; route complexity | Document URI: | http://hdl.handle.net/1942/28310 | DOI: | 10.1016/j.procs.2019.04.054 | ISI #: | WOS:000577067400050 | Rights: | 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer review under the responsibility of the Conference Program Chair | Category: | C1 | Type: | Proceedings Paper | Validations: | ecoom 2021 vabb 2021 |
Appears in Collections: | Research publications |
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Path-complexity-for-observed-and-predicted-bicycli_2019_Procedia-Computer-Sc.pdf | Published version | 351.71 kB | Adobe PDF | View/Open |
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