Travel demand corridors: Modelling approach and relevance in the planning process. (January 2017)

• Record Type: Journal Article
• Authors: Bahbouh, Kinan; Wagner, James R.; Morency, Catherine; Berdier, Chantal
• Is Part Of: Journal of transport geography. Volume 58(2017)
• Page Start: 196
• Page End: 208
• Publication Date: 2017-01
• Subjects: Demand corridor -- Origin and Destination (OD) -- Desire lines -- Travel demand -- Transportation planning -- Urban planning -- Trajectory clustering -- Travel surveys -- Travel patterns; Transportation -- Periodicals; Telecommunication -- Periodicals; Transport -- Périodiques; Télécommunications -- Périodiques; Telecommunication; Transportation; Periodicals; 388
• DOI: 10.1016/j.jtrangeo.2016.12.007
• Languages: English
• ISSNs: 0966-6923

Abstract

Abstract: In an ideal world, transportation networks and services would be adapted to the specific travel needs of each individual and would perfectly fit the corresponding desire lines (direct lines between origin and destination points). However, in practice, networks cannot be designed to accommodate each individual trip. Still, it is possible to optimize transportation systems from a collective demand point of view. To move from an individual to a collective scale, individual demands need to be encapsulated into demand corridors. Although current spatial tools and data mining techniques are able to identify corridors from numerous movements by using linear or non-linear trajectory data, their limitations—from a transportation point of view—include the use of non-intuitive parameters and the application of some aggregation processes that make it difficult to retrace the attributes of individual input data that could benefit the richness of the available data after processing. For that reason, we propose a new algorithm called Trajectory Clustering for Desire Lines (TraClus-DL), which can identify corridors from Origin-Destination (OD) information with simple parameters, such as spatial location, angles between lines, and sampling weights. The functionality of TraClus-DL as a diagnostic tool for transportation supply was assessed and tested using data from the 2013 OD travel survey conducted in the Montreal area. The sensitivity of the results, with respect to parameter settings, was evaluated, and a comparison with an existing algorithm was proposed. The results of this study demonstrate that transportation specialists can benefit from the convenience of using TraClus-DL as a corridor identification tool, which includes its potential to perform deep analyses at the corridor level. In addition, this study provides new insights into the possible uses of demand corridors as relevant tools for transportation planning, and in the decision-making processes in which a neutral reference is needed to evaluate how much the transportation supply differs from the collective travel demand. Highlights: New insights into the identification and the potentials of demand corridors is provided. TraClus-DL is able to identify demand corridors from desegregated OD data. TraClus-DL offers the possibility to conduct deep analyses at the corridor level. Demand corridor could be a useful tool to identify potential development axes. Corridor identification challenges include validation and parameter selection.