RESEARCH ARTICLE


Measuring the Reliability of Methods and Algorithms for Route Choice Set Generation: Empirical Evidence from a Survey in the Naples Metropolitan Area



Fulvio Simonelli1, Fiore Tinessa1, *, Ciro Buonocore1, Francesca Pagliara1
1 Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy


Article Metrics

CrossRef Citations:
0
Total Statistics:

Full-Text HTML Views: 1439
Abstract HTML Views: 487
PDF Downloads: 128
Total Views/Downloads: 2054
Unique Statistics:

Full-Text HTML Views: 628
Abstract HTML Views: 253
PDF Downloads: 92
Total Views/Downloads: 973



Creative Commons License
© 2020 Simonelli et al.

open-access license: This is an open access article distributed under the terms of the Creative Commons Attribution 4.0 International Public License (CC-BY 4.0), a copy of which is available at: https://creativecommons.org/licenses/by/4.0/legalcode. This license permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

* Address correspondence to this author at the Department of Civil, Architectural and Environmental Engineering, University of Naples Federico II, Via Claudio 21, 80125 Naples, Italy; Tel: +39 081 7683775; E-mail: fiore.tinessa@unina.it


Abstract

Background:

Route choice set definition is a very sensitive phase of the route choice simulation. Several heuristics, generally based on shortest path algorithm repetition, give as output choice sets that are very large, lading to questions about their behavioural consistency.

Objective:

This paper proposes a comparison of the main route choice set generation methods, contrasting the results of the commonly implemented heuristics with the revealed choice sets of a sample of employees and students moving within the Metropolitan Area of Naples.

Methods:

We described the data collection process and provided a statistical analysis of the sample data. In addition, since coverage measures and performance indicators, usually applied in the literature, do not take into account any possible biases related to the generated choice set cardinality. The current work proposes an analysis of the coverage of routes that are generated by the heuristics towards the revealed routes.

Results:

We observed that when the heuristics did not provide overlapped routes, although giving higher network coverage, they introduced a higher number of links not belonging to any observed route. In general, this may cause significant network loading errors. Therefore, the quality of a method for choice set generation should be measured as a function of the trade-off amongst network coverage and network loading bias due to excessive cardinality of the generated choice-sets.

Conclusion:

We found the randomization method, which is also less computational demanding, provided the best trade-off amongst network coverage and network loading bias

Keywords: Choice set, Route choice, Randomization , Method, Computational demanding, Heuristics, Statistical analysis.