Scenario-based multi-objective AVI reader location models under different travel demand patterns

Abstract

Recently, a multi-objective model for locating the automatic vehicle identification (AVI) readers in a transportation network was proposed by the authors along with its solution procedure. The model locates the AVI readers by simultaneously considering three objectives: the equipment and installation cost (e.g. number of AVI readers), the coverage of the AVI system (e.g. number of origin–destination (O–D) pairs), and the amount/quality of travel information obtained (e.g. number of AVI readings). However, only a single travel demand pattern for a certain time period, such as the evening peak hour, was considered in determining the AVI reader locations. Therefore, the recommended AVI system may not be able to guarantee the amount of travel information gathered during other time periods. This study extends our previously proposed model by developing three scenario-based models to accommodate different travel demand patterns observed during the whole day. A case study is provided to illustrate the applicability of the new models and the robustness of the AVI system designed by considering different travel demand patterns.

Keywords:

• automatic vehicle identification
• location theory
• scenario analysis
• multi-objective programming

Acknowledgements

The work of Chen and Chootinan was partially supported by the California Partners for Advanced Transit and Highways Program (MOU 5502) and the National Science Foundation (CMS-0134161), and Pravinvongvuth was partially supported by a dissertation fellowship from Utah State University. The support is gratefully acknowledged.

Notes

Note

1. Note that the PM demand pattern given in Table 1 differs from the one provided in our prior studies (Chen et al. 2004a), because there are 16 more O–D pairs (hence higher total demand) in the current network.