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Citation |
Hrncir J, Zilecky P, Song Q, Jakob M. IEEE Trans. Intel. Transp. Syst. 2017; 18(3): 493-504. |
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Copyright |
(Copyright © 2017, IEEE (Institute of Electrical and Electronics Engineers)) |
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DOI |
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PMID |
unavailable |
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Abstract |
Increasing the adoption of cycling is crucial for achieving more sustainable urban mobility. Navigating larger cities on a bike is, however, often challenging due to the cities' fragmented cycling infrastructure and/or complex terrain topology. Cyclists would thus benefit from intelligent route planning that would help them discover routes that best suit their transport needs and preferences. Because of the many factors cyclists consider in deciding their routes, employing a multicriteria route search is vital for properly accounting for cyclists' route-choice criteria. A direct application of optimal multicriteria route search algorithms is, however, not feasible due to their prohibitive computational complexity. In this paper, we formalize a multicriteria bicycle routing problem and propose several heuristics for speeding up the multicriteria route search. We evaluate our method on a real-world cycleway network and show that speedups of up to four orders of magnitude over the standard multicriteria label-setting algorithm are possible with a reasonable loss of solution quality. Our results make it possible to practically deploy bicycle route planners capable of producing diverse high-quality route suggestions respecting multiple real-world route-choice criteria. © 2017 Institute of Electrical and Electronics Engineers. Language: en |