Abstract

TRB 2014 - 93rd Transportation Research Board Annual Meeting, WASHINGTON DC, ETATS-UNIS, 12-/01/2014 - 16/01/2014; The travel time variability may significantly influence the driver's route choice. Estimating travel time reliability is thus really appealing to urban infrastructure managers. This could provide better information to drivers, encourage their reassignment on the network, and optimize its use. In this paper, we study any arterial in under-saturated conditions with known fixed-time traffic signals. The kinematic wave model is chosen to simply represent traffic dynamics. A semi-analytical (grid-free) method is applied to determine the separation between vehicle groups at each signal of the arterial. The main contribution of this paper is to present an aggregated diagram that describes the functioning of this arterial. It graphically provides the direct assessment of vehicle travel times with respect to their departure and the traffic flow. This tool only depends on signal settings and is cyclic and invariant for fixed-time signals. We show how to use this diagram to generate probabilistic travel time distributions when some input parameters are uncertain. Furthermore, this diagram appears insightful when the traffic flow is not accurately known.

Abstract

Traffic Granular Flow, DELFT, PAYS-BAS, 28-/10/2015 - 30/10/2015; This paper presents a generic data assimilation framework based on a mesoscopic-LWR model formulated in Lagrangian-space coordinates and using both Lagrangian observations. This is a challenge work since probe trajectories are not directly related to specific vehicle/platoon indexes in the simulation model. Therefore, we develop a method to incorporate probe information and to further estimate states. The proposed method has been validated on a homogeneous road stretch, and it provides promising results for further extension of the framework.

Abstract

The research leading to these results has received funding from the European Research Council under the European Union's Seventh Framework Programme (FP/2007-2013) / ERC Grant Agreement n. 321132, project TRAMAN21. Summarization: First-order traffic flow models of the LWR (Lighthill-Whitham-Richards) type are known for their simplicity and computational efficiency and have, for this reason, been widely used for various traffic engineering tasks. However, these first-order models are not able to reproduce significant traffic phenomena of great interest, such as the capacity drop and stop-and-go waves. This paper presents an overview of modeling approaches, which introduce the ability to reflect the capacity-drop phenomenon into discretized LWR-type first order traffic flow models; and also proposes a new approach. The background and main characteristics of each approach are analyzed with particular emphasis on the practical applicability of such models for traffic simulation, management and control. The presented modeling approaches are tested and validated using real data from a motorway network in the U.K. Presented on: Transportation Research Part B: Methodological