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.
- Automatic vehicle identification
- Location theory
- Multi-objective programming
- Scenario analysis
ASJC Scopus subject areas