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Vehicle identification sensors location problem for large networks
, Article Journal of Intelligent Transportation Systems: Technology, Planning, and Operations ; 2018 ; 15472450 (ISSN) ; Shafahi, Y ; Sharif University of Technology
Taylor and Francis Inc
2018
Abstract
Finding the optimal location for sensors is a key problem in flow estimation. There are several location models that have been developed recently for vehicle identification (ID) sensors. However, these location models cannot be applied to large networks because there are many constraints and integer variables. Based on a property of the location problem for vehicle ID sensors, given the initial vehicle ID sensors that are pre-installed and fixed on the network, this article presents a solution that greatly reduces the size of this location problem. An applied example demonstrates that when 8% of the arcs from a real network that are randomly selected have a vehicle ID sensor, the reductions...
Solving Location Problem for Vehicle Identification Sensors to Observe or Estimate Path Flows in Larg-Scale Networks
, M.Sc. Thesis Sharif University of Technology ; Shafahi, Yousef (Supervisor)
Abstract
Origin-Destination (OD) demand is one of the important requirements in transportation planning. Estimating OD demand could be an expensive and time consuming procedure. These days using vehicle identification sensors for OD estimation has become very common because of its low cost and high accuracy. In this study, we focus on solving location problems of these sensors with the aim of observe and estimate path flows. These problems have only been solved for small-scale networks until recently due to being computationally expensive. These years two basic models have been introduced : one, without considering time of vehicle ID detection and one, with considering that information. In this...
Vehicle Identification Sensors Location Problem with the Purpose of Origin-destination Estimation
, Ph.D. Dissertation Sharif University of Technology ; Shafahi, Yousef (Supervisor)
Abstract
Origin-Destination (OD) table is an important input for managing and controling processes of transportation systems. OD flow estimation based on the observations of traffic sensors is a famous way of attaining this table. Technology developments in recent years reduce the cost and improve the quality of the results for this method. This research explores the methods for applying one of these technologies, vehicle identification systems, with the purpose of OD flow estimation.In this research several location models for vehicle identification systems are presented. These models have better performances comparing to the existing models in the literature. Furthermore, location models for some...
Vehicle identification sensors location problem for large networks
, Article Journal of Intelligent Transportation Systems: Technology, Planning, and Operations ; Volume 23, Issue 4 , 2019 , Pages 389-402 ; 15472450 (ISSN) ; Shafahi, Y ; Sharif University of Technology
Taylor and Francis Inc
2019
Abstract
Finding the optimal location for sensors is a key problem in flow estimation. There are several location models that have been developed recently for vehicle identification (ID) sensors. However, these location models cannot be applied to large networks because there are many constraints and integer variables. Based on a property of the location problem for vehicle ID sensors, given the initial vehicle ID sensors that are pre-installed and fixed on the network, this article presents a solution that greatly reduces the size of this location problem. An applied example demonstrates that when 8% of the arcs from a real network that are randomly selected have a vehicle ID sensor, the reductions...
Vehicle identification sensor models for origin-destination estimation
, Article Transportation Research Part B: Methodological ; Volume 89 , 2016 , Pages 82-106 ; 01912615 (ISSN) ; Shafahi, Y ; Sharif University of Technology
Elsevier Ltd
Abstract
The traditional approach to origin-destination (OD) estimation based on data surveys is highly expensive. Therefore, researchers have attempted to develop reasonable low-cost approaches to estimating the OD vector, such as OD estimation based on traffic sensor data. In this estimation approach, the location problem for the sensors is critical. One type of sensor that can be used for this purpose, on which this paper focuses, is vehicle identification sensors. The information collected by these sensors that can be employed for OD estimation is discussed in this paper. We use data gathered by vehicle identification sensors that include an ID for each vehicle and the time at which the sensor...