Piecewise-Linearized Cell Transmission Model and Parameter Calibration Methodology

This paper studies the development of macroscopic freeway traffic models and parameter calibration methodologies that are computationally efficient and suitable for use in real-time traffic monitoring and control applications. Toward the fulfillment of these objectives, a macroscopic traffic model, the switching-mode model (SMM), is presented; it is a piecewise-linearized version of Daganzo's cell transmission model (CTM). The observability and controllability properties of the SMM modes are reviewed because these properties are of fundamental importance in the design of traffic estimators and on-ramp metering controllers. A semiautomated method has been developed for calibrating the CTM and SMM parameters. In this method, a least-squares data-fitting approach is applied to loop detector data to determine free-flow speeds, congestion-wave speeds, and jam densities for specified subsections of a freeway. Bottleneck capacities are estimated from measured mainline and on-ramp flows. The calibration method wa...

Robust variable speed limit control with respect to uncertainties

An integrated macroscopic traffic model is proposed, which integrates a macroscopic urban traffic flow model with a microscopic traffic emission model for individual vehicles. As a macroscopic model, the integrated model is fast enough for on-line control purposes. Nevertheless, the model can still capture the traffic emissions for vehicles in different states compared with using a macroscopic traffic emission model, because of the accuracy of the microscopic traffic emission model. Model Predictive Control is applied to control urban traffic areas based on the integrated traffic model, aiming at reducing both travel delays and traffic emissions.

A cell-based dynamic traffic assignment model: Formulation and properties

Intelligent Vehicle/Highway Systems (IVHS) is a multi-year research/demonstration program which aims at improving the vehicle/highway system operation and management techniques for the post-interstate construction era. The authors first describe the framework of IVHS, which as four major components: (1) advanced traffic management system (ATMS); (2) advanced driver information system (ADIS); (3) commercial vehicle operations (CVO); and (4) advanced vehicle control systems (AVCS). The ATMS related research and development plans to support the real-time traffic management systems and control strategies are considered. The state-of-the-art traffic engineering modeling software is reviewed. The discussion centers around the TRAF system, a family of microscopic and macroscopic traffic simulation software models for surface streets, freeways, and corridor networks. The gap between the capabilities provided by the current traffic modeling software and the functional requirement of the IVHS traffic models is also addressed. >

This paper presents a cell transmission model with a lane-changing and vehicle-tracking (CTM-LV) framework for simulation of international land ports of entry (POEs). The development of the modeling framework is motivated by the need to simulate lane-specific queuing yet permit lane changing of vehicles between queues–-a behavior that was not accounted for or tested by the earlier cell transmission models and that cannot be easily replicated in microscopic traffic simulation models. The CTM-LV's network representation, traffic flow logic, and lane-changing rules are discussed. A simulation experiment is then presented to illustrate the importance of modeling the lane changing between queues that will affect the estimation of average queue length. The concept of CTM-LV has been applied to simulate the northbound traffic at the Bridge of the Americas POE, for passenger cars entering El Paso, Texas, from Ciudad Juarez, Mexico. Finally, a method is proposed to track selected vehicles within the CTM-LV framework so that an individual vehicle's travel time can be calculated and vehicle trajectories compared against data collected by probe vehicles with Global Positioning System receivers.

This research proposes an integrated framework of capacitated vehicle routing problems (CVRP) and traffic flow model (cell transmission model in this research) to assess the effect of time-varying congestion. We develop a framework consisting sequence of mixed integer programs solving the CVRP with updated cost obtained from the traffic flow model. A real-world network with 15 cities and towns is tested with the framework and results show significant travel time reduction from the case where time-varying congestion is not considered. In addition, we consider system optimal type of route choice behavior within the traffic flow model.

Multiple model stochastic filtering for traffic density estimation on urban arterials

Route swapping in dynamic traffic networks

Macroscopic traffic flow models play a significant role in the Intelligent Transportation Systems (ITS), especially for the urban traffic control and the dynamic traffic assignment. Two main problems limit the application of the existing traffic models. One is the traffic dynamics described by the complex nonlinear equations which are difficult to resolve in real time, and the other is that some model parameters need to be calibrated in prior. This paper presents a hybrid macroscopic and microscopic (macro-microscopic) traffic flow model of freeway traffic by extending the cell transmission model (CTM) with the real time speed dynamics. Simple supplying and demanding functions are defined to represent the traffic propagation between the upstream and downstream cell boundaries. A microscopic car-following model is integrated to specify the dynamics of the average speed in each cell. Simulation results with specific traffic data set collected from a 4-kilometre long urban freeway show the performance of the model compared to the well-known METANET model.

This article presents a linear programming formulation to solve the network design problem using the link transmission model (LTM) as the underlying traffic flow model. The original LTM was adapted by incorporating link-sending and receiving flows using linear inequalities. Furthermore, route choice was relaxed, and transfer flow variables were used to model vehicles’ routing decisions within the network. The objective function of the linear program aimed to minimize the total difference between the cumulative vehicle numbers (CVN) at the upstream and at the downstream boundaries of each link subject to flow-conservation and budget constraints. CVN were represented using transfer flows from connected links. The resulting formulation is a linear program that represents a dynamic system optimum traffic flow pattern, embedding the LTM’s network loading procedure. In contrast to the single-destination system optimum dynamic traffic assignment, based on the cell transmission model, the proposed formulation requires considerably fewer decision variables, thus potentially providing a more scalable approach. The proposed formulation was implemented on an example network to illustrate the behavior of the model, and was compared with the cell-based formulation. We show that the model describes free-flow and congested traffic flow states accurately in terms of shock-wave propagation, queuing of vehicles, and optimal total system travel time.

The paper focuses on the calibration of the hybrid multi-scale modelling approach that incorporates multiple levels of traffic flow representation. This paper refers to a model already developed in the literature, the Hybrid Cellular Automata (CA) and Cell Transmission Model (CTM). We use vehicle trajectory data collected from a car-following field experiment on a circular road track to explore the calibration of the CA model concerning various cell lengths through two distinct approaches: simulating all vehicles within the closed loop and simulating each vehicle using data obtained from its respective follower. We also evaluate different methods for the CTM calibration with respect to the CA model. The major findings are: (1) the calibrated parameters obtained using the simulated leader approach display greater regularity across different cell lengths; (2) the Constrained Squared Error [CsqE] method for macroscopic calibrations yielded promising results, showcasing the lowest sum of squared errors between fundamental diagrams.

Urban traffic and induced air quality modeling and simulation: Methodology and illustrative example

Traffic State Estimation on a Two-Dimensional Network by a State-Space Model

This paper proposes a preliminary calibration and validation of a macroscopic traffic flow model for signalised junctions. In fact, on the network signal setting design problem, a reliable modelling approach must be adopted to acknowledge the traffic flow effects, considering two phenomena: queue dispersion and spillback. The proposed model is an extension of the space-time discrete Cell Transmission Model (CTM), which can simulate dispersion and horizontal queue. This preliminary calibration and validation use real-world data collected on an arterial of the city of Salerno (south of Italy). Results showed that the estimated parameters are consistent with the literature.