Optimum allocation of traffic sensors using Fuzzy AHP and Topsis

Smart traffic monitoring is a new method of traffic data acquisition. Traffic sensors are the core of such system in consequence optimum allocation of them increases efficiency of monitoring Although big challenges to accomplish this goal is selection of the best methodology for identification of optimum places. Thus this paper tries to propose a new methodology using Fuzzy-AHP and Topsis to determine optimum place for allocation of such devices. To do the analysis a pilot junction in north of Washington was selected. Then effective criteria such as annual average daily traffic (AADT) and accident severity (IR) and average slope and distance from school were determined respecting traffic expert’s idea. Finally Fuzzy-AHP method was used to estimate weight of input criteria, in comparison to famous weighting method such as AHP using fuzzy number for weight estimation of criteria increases efficiency of weight estimation process. Then estimated weight entered to Topsis method to identify appropriate place for sensor allocation. In this step urban links were classified in 3 classes using Topsis score, therefore urban links belongs 1 class were identified as vulnerable link. These links are in in high danger of traffic incident as a result need to be equipped with monitoring traffic instruments such as traffic sensors. Consequently our study tries to propose a new methodology and effective factors for determination of vulnerable urban links that are in high danger of traffic incidents. Therefore the identified links need to be monitored with using appropriate traffic strategy such as geo-sensor traffic network.