TY - CHAP
T1 - Regional bicycle network evaluation and strategic planning
T2 - A quantitative methodological approach despite limited data sources for cycling
AU - van Dulmen, Alex
AU - Fellendorf, Martin
N1 - Funding Information:
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This research was partly supported by the Austrian Ministry of Climate Action within the Mobility of the Future research program (FFG Grant-No.: 885034). Further support by the Styrian Department of Transport and Construction as well as the Urban Mobility Lab Graz is gratefully acknowledged.
Publisher Copyright:
© National Academy of Sciences: Transportation Research Board 2021.
PY - 2021
Y1 - 2021
N2 - In cases where budgets and space are limited, the realization of new bicycle infrastructure is often hard, as an evaluation of the existing network or the benefits of new investments is rarely possible. Travel demand models can offer a tool to support decision makers, but because of limited data availability for cycling, the validity of the demand estimation and trip assignment are often questionable. This paper presents a quantitative method to evaluate a bicycle network and plan strategic improvements, despite limited data sources for cycling. The proposed method is based on a multimodal aggregate travel demand model. Instead of evaluating the effects of network improvements on the modal split as well as link and flow volumes, this method works the other way around. A desired modal share for cycling is set, and the resulting link and flow volumes are the basis for a hypothetical bicycle network that is able to satisfy this demand. The current bicycle network is compared with the hypothetical network, resulting in preferable actions and a ranking based on the importance and potentials to improve the modal share for cycling. Necessary accompanying measures for other transport modes can also be derived using this method. For example, our test case, a city in Austria with 300,000 inhabitants, showed that a shift of short trips in the inner city toward cycling would, without countermeasures, provide capacity for new longer car trips. The proposed method can be applied to existing travel models that already contain a mode choice model.
AB - In cases where budgets and space are limited, the realization of new bicycle infrastructure is often hard, as an evaluation of the existing network or the benefits of new investments is rarely possible. Travel demand models can offer a tool to support decision makers, but because of limited data availability for cycling, the validity of the demand estimation and trip assignment are often questionable. This paper presents a quantitative method to evaluate a bicycle network and plan strategic improvements, despite limited data sources for cycling. The proposed method is based on a multimodal aggregate travel demand model. Instead of evaluating the effects of network improvements on the modal split as well as link and flow volumes, this method works the other way around. A desired modal share for cycling is set, and the resulting link and flow volumes are the basis for a hypothetical bicycle network that is able to satisfy this demand. The current bicycle network is compared with the hypothetical network, resulting in preferable actions and a ranking based on the importance and potentials to improve the modal share for cycling. Necessary accompanying measures for other transport modes can also be derived using this method. For example, our test case, a city in Austria with 300,000 inhabitants, showed that a shift of short trips in the inner city toward cycling would, without countermeasures, provide capacity for new longer car trips. The proposed method can be applied to existing travel models that already contain a mode choice model.
KW - Bicycle demand model
KW - Bicycle network planning
KW - Microzone demand model
KW - Multimodal demand model
KW - Operations
KW - Travel demand 18 model
UR - http://www.scopus.com/inward/record.url?scp=85120069220&partnerID=8YFLogxK
U2 - 10.1177/03611981211028870
DO - 10.1177/03611981211028870
M3 - Chapter
AN - SCOPUS:85120069220
T3 - Transportation Research Record
SP - 306
EP - 316
BT - Transportation Research Record
PB - SAGE Publications Ltd
ER -