Spatial inference of traffic transition using micro-macro traffic variables

This paper proposes an online traffic inference algorithm for road segments in which local traffic information cannot be directly observed. Using macro-micro traffic variables as inputs, the algorithm consists of three main operations. First, it uses interarrival time (time headway) statistics from upstream and downstream locations to spatially infer traffic transitions at an unsupervised piece of segment. Second, it estimates lane-level flow and occupancy at the same unsupervised target site. Third, it estimates individual lane-level shockwave propagation times on the segment. Using real-world closed-circuit television data, it is shown that the proposed algorithm outperforms previously proposed methods in the literature

Examining the potential of floating car data for dynamic traffic management

Traditional traffic monitoring systems are mostly based on road side equipment (RSE) measuring traffic conditions throughout the day. With more and more GPS-enabled connected devices, floating car data (FCD) has become an interesting source of traffic information, requiring only a fraction of the RSE infrastructure investment. While FCD is commonly used to derive historic travel times on individual roads and to evaluate other traffic data and algorithms, it could also be used in traffic management systems directly. However, as live systems only capture a small percentage of all traffic, its use in live operating systems needs to be examined. Here, the authors investigate the potential of FCD to be used as input data for live automated traffic management systems. The FCD in this study is collected by a live country-wide FCD system in the Netherlands covering 6-8% of all vehicles. The (anonymised) data is first compared to available road side measurements to show the current quality of FCD. It is then used in a dynamic speed management system and compared to the installed system on the studied highway. Results indicate the FCD set-up can approximate the installed system, showing the feasibility of a live system

Lagrangian-based Hydrodynamic Model: Freeway Traffic Estimation

This paper is concerned with highway traffic estimation using traffic sensing data, in a Lagrangian-based modeling framework. We consider the Lighthill-Whitham-Richards (LWR) model (Lighthill and Whitham, 1955; Richards, 1956) in Lagrangian-coordinates, and provide rigorous mathematical results regarding the equivalence of viscosity solutions to the Hamilton-Jacobi equations in Eulerian and Lagrangian coordinates. We derive closed-form solutions to the Lagrangian-based Hamilton-Jacobi equation using the Lax-Hopf formula (Daganzo, 2005; Aubin et al., 2008), and discuss issues of fusing traffic data of various types into the Lagrangian-based H-J equation. A numerical study of the Mobile Century field experiment (Herrera et al., 2009) demonstrates the unique modeling features and insights provided by the Lagrangian-based approach.Comment: 17 pages, 7 figures, current version submitted to Transportation Research Part

Grenoble Traffic Lab: An experimental platform for advanced traffic monitoring and forecasting

International audienceThis paper describes the main features of the "Grenoble Traffic Lab" (GTL), a new experimental platform for the collection of traffic data coming from a dense network of wireless sensors installed in the south ring of Grenoble, in France. The main challenges related to the configuration of the platform and data validation are discussed, and two relevant traffic monitoring and forecasting applications are presented to illustrate the operation of GTL

Traffic stream macro and micro analysis in AP-7 turnpike

El present treball té com a objectiu principal l’anàlisi tant macroscòpic com microscòpic del flux de trànsit de l’autopista AP-7. Aquest anàlisi que parteix d’una potent base de dades amb registres vehicle a vehicle, pretén demostrar que únicament prenent les definicions generalitzades d’Edie de les diferents variables calculades correctament, els resultats són vàlids. És a dir que, a partir d’una correcte estimació de les diferents variables del trànsit, els errors es minimitzen i les relacions entre variables es compleixen reduïnt-ne notablement la dispersió. Gràcies doncs a aquesta base de dades de 24 hores de registres vehicle a vehicle el càlcul de les diferents variables del tràfic és possible. A més, la informació registrada al diumenge dia 7 de Setembre de 2008 inclou les dades d’una important congestió de forma que tots els estats del trànsit estan contemplats en aquest anàlisi