Lagrangian sensing: traffic estimation with mobile devices

Work, Daniel B.; Tossavainen, Olli-Pekka; Jacobson, Quinn; Bayen, Alexandre M.

doi:10.1109/acc.2009.5160332

Cited by 35 publications

(22 citation statements)

References 19 publications

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“…Currently, some 1,000 taxi mounted probes are collecting traffic data, known as the Mobile Millennium Stockholm project [23], which clearly is insufficient to provide high resolution traffic monitoring to reduce congestion, environmental impact, accidents, and costs. With a required 2-3 % penetration of probes [2], [4], [3] on occupied roads, the implication is that a large number of active probes have to be available to cover a major metropolitan area. More specifically, a large number of probes is required to obtain fine resolution in time and space at less trafficked road segments.…”

Section: The Moving Vehicle Logger Campaignmentioning

confidence: 99%

“…State-of-the art research projects like the Mobile Millennium in the US provided a pilot traffic-monitoring system that used the GPS in cellular phones to gather traffic information, process it, and distribute it back to the phones in real time. Already in 2008, a traffic probing field campaign (known as the Mobile Century field experiment) was carried out which involved 100 private cars carrying GPS-enabled Nokia N95 phones [2], [3]. For the work reported in [2], realtime measurements were collected every third second while the vehicles repeatedly drove loops of 610 miles in length continuously for 8 hours on freeway I-880 near Union City in the San Francisco Bay Area, California.…”

Section: A Road Traffic Monitoringmentioning

confidence: 99%

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Smartphone-Based Measurement Systems for Road Vehicle Traffic Monitoring and Usage-Based Insurance

Händel

Ohlsson²,

Ohlsson

et al. 2014

IEEE Systems Journal

110

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Abstract-A framework is presented to deploy a smartphonebased measurement system for road vehicle traffic monitoring and usage based insurance. Through the aid of a hierarchical model to modularize the description, the functionality is described as spanning from sensor-level functionality and technical specification, up to the top-most business model. The designer of a complex measurement system has to consider the full picture from low-level sensing, actuating, and wireless data transfer to the top-most level including enticements for the individual smartphone owners; the end-users who are the actual measurement probes. The measurement system provides two data streams -a primary stream to support road vehicle traffic monitoring, and a secondary stream to support the usage based insurance program. The former activity has a clear value for a society and its inhabitants, as it may reduce congestion and environmental impacts. The latter data stream drives the business model and parts of the revenue streams which ensure the funding of the total measurement system, and create value for the end-users, service provider and the insurance company. Besides the presented framework, outcome from a measurement campaign is presented, including road vehicle traffic monitoring (primary data stream) and a commercial pilot of usage based insurance based on the driver profiles (secondary data stream). The measurement system is believed to be sustainable, thanks to the incitements offered to the individual end-users, in terms of a favorable pricing for the insurance premium. The measurement campaign itself is believed to have an interest in its own right, as it includes smartphone probing of road traffic with a number of probes in the vicinity of the current state-of-the art, given by the Berkeley Mobile Millennium Project. During the 10 month run of the project, some 4,500 driving hours / 250,000 km of road vehicle traffic data was collected. Index Terms-Complex

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Section: The Moving Vehicle Logger Campaignmentioning

confidence: 99%

Section: A Road Traffic Monitoringmentioning

confidence: 99%

Smartphone-Based Measurement Systems for Road Vehicle Traffic Monitoring and Usage-Based Insurance

Händel

Ohlsson²,

Ohlsson

et al. 2014

IEEE Systems Journal

110

View full text Add to dashboard Cite

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“…"For the first time, we're seeing very rich data on these types of roads, " says Jacobson. The team conducted a pilot study with 100 cars driving 10-16-kilometre loops in February last year and found that the phones captured velocity patterns similar to those obtained by underground sensors, including the congestion resulting from a fivecar accident 2 . When mobile-phone data are fused with other sensor data, "you can get enormous gains in accuracy", says Bayen.…”

Section: Location Location Locationmentioning

confidence: 99%

Personal technology: Phoning in data

Kwok¹

2009

Nature

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“…The process of incorporating Eulerian and Lagrangian data into a mathematical model to improve the modeling is called data estimation or equivalently inverse modeling. According to the major UC Berkeley field experiment named Mobile Century and then Mobile Millennium [54], it has been shown that even a 2% to 5% penetration rate of probe vehicles into the driver population, Lagrangian sensing provides sufficient and accurate data for estimating traffic velocity or density on highways [22,23,52]. Nevertheless, it has been demonstrated in [49] that the quality of estimation for higher-order traffic quantities including vehicles acceleration/deceleration, emission and fuel consumption rates is dramatically affected when the penetration rate of probe vehicles or the sampling frequency of the current mobile sensors decrease.…”

Section: General Backgroundmentioning

confidence: 99%

A variational formulation for higher order macroscopic traffic flow models: Numerical investigation

Costeseque

Lebacque²

2014

Transportation Research Part B: Methodological

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This paper deals with numerical methods providing semi-analytic solutions to a wide class of macroscopic traffic flow models for piecewise affine initial and boundary conditions. In a very recent paper, a variational principle has been proved for models of the Generic Second Order Modeling (GSOM) family, yielding an adequate framework for effective numerical methods. Any model of the GSOM family can be recast into its Lagrangian form as a Hamilton-Jacobi equation (HJ) for which the solution is interpreted as the position of vehicles. This solution can be computed thanks to Lax-Hopf like formulas and a generalization of the inf-morphism property. The efficiency of this computational method is illustrated through a numerical example and finally a discussion about future developments is provided.Keywords: Traffic flow, Hamilton-Jacobi equation, Lax-Hopf algorithm, Lagrangian. Introduction General backgroundMacroscopic traffic flow modeling. In order to get a realistic estimation of the real-time traffic states on networks, traffic operators and managers need macroscopic traffic flow models. These models must be simple, robust, allowing to get solutions at a low computational cost. The main macroscopic models are based on conservation laws or hyperbolic systems (see [30,19] for a review). The seminal LWR model (for Lighthill-Whitham and Richards) was proposed in [42,51] as a single conservation law with unknown the vehicles density. This model based on a first order Partial Differential Equation (PDE) is very simple and robust but it fails to recapture some empirical features of traffic. In particular, it does not allow to take into account non-equilibrium traffic states mainly in congested situation. More sophisticated models referred to as higher order models were developed to encompass kinematic constraints of real vehicles or also the wide variety of driver behaviors, even at the macroscopic level. In this paper we deal with models of the Generic Second Order Modeling (GSOM) family. Even if these models are more complicated to deal with, they permit to reproduce traffic instabilities (such as the so-called stop-and-go waves, the hysteresis phenomenon or capacity drop) which move at the traffic speed and differ from kinematic waves [53] Traffic flow monitoring. Before the wide propagation of internet handsets, traffic monitoring has mainly been built on dedicated infrastructure which imply quite important installation and maintenance costs. Traffic flow monitoring and management has been deeply modified with the development of new technologies in mobile sensing aiming to provide a quite important quantity of floating car data. Traffic flow models are needed to be well suited such that managers could use both Eulerian and Lagrangian data for improving traffic state estimation. The term Eulerian refers to "classical" fixed equipment giving records of occupancy or flow of vehicles on a freeway section. This kind of measurements come from e.g. fixed inductive loop detectors, Radio Frequency Identification (R...

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Lagrangian sensing: traffic estimation with mobile devices

Cited by 35 publications

References 19 publications

Smartphone-Based Measurement Systems for Road Vehicle Traffic Monitoring and Usage-Based Insurance

Smartphone-Based Measurement Systems for Road Vehicle Traffic Monitoring and Usage-Based Insurance

Personal technology: Phoning in data

A variational formulation for higher order macroscopic traffic flow models: Numerical investigation

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