J. Barceló

Dynamic Network Simulation with AIMSUN

The deployment of ITS must be assisted by suitable tools to conduct the feasibility studies required for testing the designs and evaluating the expected impacts. Microscopic traffic simulation has proven to be the suitable methodological approach to achieve these goals. This paper discuses some of the most critical aspects of the dynamic simulation of road networks, namely the heuristic dynamic assignment, the implied route choice models, and the validation methodology, a key issue to determine the degree of validity and significance of the simulation results. The paper is structured in two parts, the first provides an overview on how the main features of microscopic simulation have been implemented in AIMSUN, and the second is devoted to discus in detail the heuristic dynamic assignment.

Vehicle Routing And Scheduling Models, Simulation And City Logistics

The distribution of goods based on road services in urban areas, usually known as City Logistics, contributes to traffic congestion and is affected by traffic congestion, generates environmental impacts and incurs in high logistics costs. Therefore a holistic approach to the design and evaluation of City Logistics applications requires an integrated framework in which all components could work together that is must be modelled not only in terms of the core models for vehicle routing and fleet management, but also in terms of models able of including the dynamic aspects of traffic on the underlying road network, namely if Information and Communication Technologies (ICT) applications are taken into account. This paper reports on the modelling framework developed in the national projects SADERYL-I and II, sponsored by the Spanish “Direccion General de Ciencia y Tecnologia” (DGCYT) and tested in the European Project MEROPE of the INTERREG IIIB Programme. The modelling framework consists of a Decision Support System whose core architecture is composed by a Data Base, to store all the data required by the implied models: location of logistic centres and customers, capacities of warehouses and depots, transportation costs, operational costs, fleet data, etc.; a Database Management System, for the updating of the information stored in the data base; a Model Base, containing the family of models and algorithms to solve the related problems, discrete location, network location, street vehicle routing and scheduling; a Model Base Management System, to update, modify, add or delete models from the Model Base; a GIS based Graphic User Interface supporting the dialogues to define and update data, select the model suitable to the intended problem, generate automatically from the digital map of the road network the input graph for the Network Location and Vehicle Routing models, apply the corresponding algorithm, visualize the problem and the results, etc. To account for the dynamics of urban traffic flows the system includes an underlying dynamic traffic simulation model (AIMSUN in this case) which is able to track individually the fleet vehicles, emulating in this way the monitoring of fleet vehicles in a real time fleet management system, gathering dynamic data (i.e. current position, previous position, current speed, previous speed, etc.) while following the vehicle, in a similar way as the data that in real life an equipped vehicle could provide. This is the information required by a “Dynamic Router and Scheduler” to determine which vehicle will be assigned to the new service and which will be the new route for the selected vehicle

Modelling Advanced Transport Telematic Applications with Microscopic Simulators: The Case of AIMSUN2

The simulation of Advanced Transport Telematic Applications requires specific modelling features, which have not been usually taken into account in the design of microscopic traffic simulation models. This paper discusses the general requirements of some of these applications, and describes how have they been implemented in the microscopic traffic simulator AIMSUN2.

Stochastic Heuristic Dynamic Assignment Based on AIMSUN Microscopic Traffic Simulator

The deployment of intelligent transportation systems must be assisted by suitable tools to conduct the feasibility studies required to test the designs and evaluate the expected impacts. Microscopic traffic simulation has proved to be the suitable methodological approach to achieve these goals. One of the most critical aspects of the dynamic simulation of road networks based on a microscopic approach—namely, how to perform a heuristic dynamic assignment, the implied route choice models, and whether under certain criteria the approach can achieve stochastic user equilibrium—is discussed.

Exploring Link Covering and Node Covering Formulations of Detection Layout Problem

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.

A combined methodology for transportation planning assessment. Application to a case study

Abstract Traffic assignment models based on the user-equilibrium approach are one of the most widely used tools in transportation planning analysis. Resulting flows offer a static average view of the expected use of the road infrastructure under the modeling hypothesis. This information has usually been enough for the planning decisions. The planned infrastructure is probably sufficient for average demand, but time-varying traffic flows, i.e., at peak periods, combined with the influence of road geometry, can produce undesired congestion that can not be forecasted or analysed with the static tools. There is a clear case for a change in the analysis methodology such as combination of a traffic assignment tool, with a microscopic traffic simulator. This paper illustrates, by means of a case study, the combination of a well-known traffic assignment tool, the EMME/2 model, with a microscopic traffic simulator, Advanced Interactive Microscopic Simulator For Urban And Non-Urban Networks (AIMSUN2) with emphasis on the description of the specific interfaces that make consistent the combination of both tools in the Generic Environment for Traffic Analysis and Modeling (GETRAM) environment. Models for complex transportation systems should be the combination of mathematical models and computer models, to overcome, for example, the difficulties of the integration of modeling tools. GETRAM environment has an open and flexible computer architecture suitable for such purposes.

A hybrid simulation framework for advanced transportation analysis

Abstract Two simulation approaches to emulate traffic flow dynamics are mesoscopic modeling which combines aspects of flow theory with explicit treatment of interrupted flows at intersections and allows modeling large networks with high computational efficiency dealing with dynamics aspects in strategic planning and microscopic approaches modeling the individual dynamics of each vehicle by means of car-following, lane changing and other models consistent with traffic flow theory with higher computational cost but allowing a very detailed analysis appropriated for operational planning. Combining meso and micro is methodologically appealing but raises consistency problems on the network representation and the transitions meso-micro-meso. This paper discusses these problems, proposes a solution and illustrates how it works in practice.

Robustness and Computational Efficiency of Kalman Filter Estimator of Time-Dependent Origin-Destination Matrices

Origin–destination (O-D) trip matrices that describe the patterns of traffic behavior across a network are the primary data input used in principal traffic models and, therefore, a critical requirement in all advanced systems supported by dynamic traffic assignment models. However, because O-D matrices are not directly observable, the current practice consists of adjusting an initial or seed matrix from link flow counts that are provided by an existing layout of traffic-counting stations. The availability of new traffic measurements provided by information and communication technologies (ICT) allows more efficient algorithms, namely for real-time estimation of O-D matrices that are based on modified Kalman filtering approaches to exploit the new data. The quality of the estimations depends on various factors such as the penetration of the ICT devices, the detection layout, and the quality of the initial information. The feasibility of real-time applications depends on 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 the network of Barcelonas central business district that explore the sensitivity of the Kalman filter estimates in relation to design factor values.

Robustness and Computational Efficiency of Kalman Filter Estimator of Time-Dependent Origin–Destination Matrices: Exploiting Traffic Measurements from Information and Communications Technologies

Origin–destination (O-D) trip matrices that describe the patterns of traffic behavior across a network are the primary data input used in principal traffic models and, therefore, a critical requirement in all advanced systems supported by dynamic traffic assignment models. However, because O-D matrices are not directly observable, the current practice consists of adjusting an initial or seed matrix from link flow counts that are provided by an existing layout of traffic-counting stations. The availability of new traffic measurements provided by information and communication technologies (ICT) allows more efficient algorithms, namely for real-time estimation of O-D matrices that are based on modified Kalman filtering approaches to exploit the new data. The quality of the estimations depends on various factors such as the penetration of the ICT devices, the detection layout, and the quality of the initial information. The feasibility of real-time applications depends on 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 the network of Barcelonas central business district that explore the sensitivity of the Kalman filter estimates in relation to design factor values.