A multi-class, multi-criteria bicycle traffic assignment model. Issue 7 (3rd May 2021)

• Record Type: Journal Article
• Authors: Ryu, Seungkyu; Chen, Anthony; Su, Jacqueline; Choi, Keechoo
• Is Part Of: International journal of sustainable transportation. Volume 15:Issue 7(2021)
• Page Start: 524
• Page End: 540
• Publication Date: 2021-05-03
• Subjects: Bicycle -- cyclist route choice -- multi-class -- multi-objective shortest path -- traffic assignment; Transportation -- Periodicals; Sustainable development -- Periodicals; 388
• DOI: 10.1080/15568318.2020.1770906
• Languages: English
• ISSNs: 1556-8318

Abstract

Abstract: Cycling is gaining popularity both as a mode of travel in urban communities and as an alternative mode to private motorized vehicles due to its wide range of benefits (health, environmental, and economical). However, this change in modal share is not reflected in current transportation planning and travel demand forecasting modeling processes. The existing practices to model bicycle trips in a network are not sophisticated enough to describe the full cyclist experience in route decision-making. This is evident in the existing practices' methodology: the all-or-nothing assignment uses single attributes such as distance, safety, or a composite measure of safety multiplied by distance. The purpose of this article is to develop a multi-class and multi-criteria bicycle traffic assignment model that not only accounts for multiple user classes by acknowledging that there are different types of cyclists with varying levels of biking experience, but also for relevant factors that may affect each user classes behavior in route choice decisions. The multi-class, multi-criteria bicycle traffic assignment model is developed in a two-stage process. The first stage examines key criteria to generate the set of non-dominated (or efficient) routes for each user class, and the second stage determines the flow allocation to efficient routes by user class. Numerical experiments are then conducted to demonstrate the two-stage approach for the multi-class, multi-criteria bicycle traffic assignment model.