Origin-Destination (OD) trip matrices, which describe the patterns of traffic behavior across the network, are the primary data input used in principal traffic models and therefore, a critical requirement in all advanced systems that are supported by Dynamic Traffic Assignment models. However, because OD matrices are not directly observable, the current practice consists of adjusting an initial or seed matrix from link flow counts which are provided by an existing layout of traffic counting stations. The availability of new traffic measurements provided by Information and Communication Technologies (ICT) applications allows more efficient algorithms, namely for the real-time estimation of OD matrices based on modified Kalman Filtering approaches exploiting the new data. The quality of the estimations depends on various factors, like the penetration of the ICT devices, the detection layout and the quality of the initial information. Concerning the feasibility of real-time applications, another key aspect is the computational performance of the proposed algorithms for urban networks of sensitive size. This paper presents the results of a set of computational experiments with a microscopic simulation of a network of the business district of Barcelona, which explore the sensitivity of the Kalman Filter estimates with respect to the values of the design factors, and its computational performance.
The primary data input used in principal traffic models comes from origin–destination (O-D) trip matrices, which describe patterns of traffic behavior across a network. O-D matrices are a critical requirement in advanced traffic management or information systems that are supported by dynamic traffic assignment models. However, because O-D matrices are not directly observable, current practice adjusts an initial seed matrix from link flow counts that are provided by an existing layout of traffic-counting stations. The adequacy of the detection layout is critical to determining the quality of the adjusted O-D matrix. The usual approaches to the detection layout problem assume that detectors are located at network links. This paper proposes a modified set that formulates the link detection layout problem with side constraints and presents a new metaheuristic tabu search algorithm with high computational efficiency. Emerging information and communication technologies (ICT), especially those based on the detection of the electronic signature of onboard devices (such as Bluetooth devices), allow the location of sensors at intersections. To take into account explicitly how these ICT sensors operate, this paper proposes a new formulation of a node-covering problem with side constraints, which for practical purposes can be efficiently solved with standard professional solvers such as CPLEX.
Sustainable mobility is not only a technological question, automotive technology will be part of the solution combined with a paradigm shift from car ownership to vehicle usage, and the application of Information and Communication Technologies (ICT) making possible for a user to have access to a mobility service from anywhere to anywhere at any time. Multiple Passenger Ridesharing and its variants look one of the more promising emerging mobility concepts. However, implementations of these systems accounting specifically for time dependencies, and time windows reflecting users' needs raise challenges in terms of real-time fleet dispatching and dynamic route calculation. This paper analyzes and evaluates both aspects by microscopic traffic simulation emulating real-time traffic conditions and a real traffic information system, and interacting with a Decision Support. The simulation framework has been implemented in a model of Barcelona's Central Business District. The paper presents and discusses the achieved results.
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