The PeMS algorithms for accurate, real-time estimates of g-factors and speeds from single-loop detectors
25 Aug 2001-pp 536-541
TL;DR: This study suggests that real-time speed and travel time estimates derived from single-loop detector data assuming a common g-factor for all detectors in the district can be in error by 50 percent, and so they are of little value to travelers.
Abstract: Presents the PeMS algorithms for the accurate, adaptive, real-time estimation of the g-factor and vehicle speeds from single-loop detector data. The estimates are validated by comparison with independent, direct measurements of the g-factor and vehicle speeds from 20 double-loop detectors on I-80 over a three-month period. The algorithm is used to process data from all freeways in Caltrans District 12 (Orange County, CA) over a 20-month period beginning January 1998. Analysis of those data shows that the g-factors for different loops in the district differ by as much as 100 percent, and the g-factor for the same loop can vary up to 50 percent over a 24-hour period. Many transportation districts now post real-time speed and travel time estimates on the World Wide Web. Those estimates often are derived from single-loop detector data assuming a common g-factor for all detectors in the district. This study suggests that those estimates can be in error by 50 percent, and so they are of little value to travelers. The use of the PeMS algorithm will reduce those errors.
Citations
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01 Dec 2003
TL;DR: In this paper, a comprehensive overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks, and route guidance, and selected application results are briefly outlined to illustrate the impact of various control actions and strategies.
Abstract: Traffic congestion in urban road and freeway networks leads to a strong degradation of the network infrastructure and accordingly reduced throughput, which can be countered via suitable control measures and strategies. After illustrating the main reasons for infrastructure deterioration due to traffic congestion, a comprehensive overview of proposed and implemented control strategies is provided for three areas: urban road networks, freeway networks, and route guidance. Selected application results, obtained from either simulation studies or field implementations, are briefly outlined to illustrate the impact of various control actions and strategies. The paper concludes with a brief discussion of future needs in this important technical area.
1,160 citations
01 Aug 2009
TL;DR: In this paper, a traffic monitoring system based on GPS-enabled smartphones exploits the extensive coverage provided by the cellular network, the high accuracy in position and velocity measurements provided by GPS devices, and the existing infrastructure of the communication network.
Abstract: The growing need of the driving public for accurate traffic information has spurred the deployment of large scale dedicated monitoring infrastructure systems, which mainly consist in the use of inductive loop detectors and video cameras. On-board electronic devices have been proposed as an alternative traffic sensing infrastructure, as they usually provide a cost-effective way to collect traffic data, leveraging existing communication infrastructure such as the cellular phone network. A traffic monitoring system based on GPS-enabled smartphones exploits the extensive coverage provided by the cellular network, the high accuracy in position and velocity measurements provided by GPS devices, and the existing infrastructure of the communication network. This article presents a field experiment nicknamed Mobile Century, which was conceived as a proof of concept of such a system. Mobile Century included 100 vehicles carrying a GPS-enabled Nokia N95 phone driving loops on a 10-mile stretch of I-880 near Union City, California, for 8 hours. Data were collected using virtual trip lines, which are geographical markers stored in the handset that probabilistically trigger position and speed updates when the handset crosses them. The proposed prototype system provided sufficient data for traffic monitoring purposes while managing the privacy of participants. The data obtained in the experiment were processed in real-time and successfully broadcast on the internet, demonstrating the feasibility of the proposed system for real-time traffic monitoring. Results suggest that a 2-3% penetration of cell phones in the driver population is enough to provide accurate measurements of the velocity of the traffic flow.
801 citations
TL;DR: A general approach to the real-time estimation of the complete traffic state in freeway stretches is developed based on the extended Kalman filter, based on which a traffic state estimator is designed by use of the extended-Kalman-filtering method.
Abstract: A general approach to the real-time estimation of the complete traffic state in freeway stretches is developed based on the extended Kalman filter. First, a general stochastic macroscopic traffic flow model of freeway stretches is presented, while some simple formulae are proposed to model real-time traffic measurements. Second, the macroscopic traffic flow model along with the measurement model is organized in a compact state-space form, based on which a traffic state estimator is designed by use of the extended-Kalman-filtering method. While constructing the traffic state estimator, special attention is paid to the handling of the boundary conditions and unknown parameters of the macroscopic traffic flow model. A number of simulations are conducted to test the designed traffic state estimator under various traffic situations in a freeway stretch with on/off-ramps and a long inter-detector distance. Some key issues are carefully investigated, including tracking capability of the traffic state estimator, comparison of various estimation schemes, evaluation of different detector configurations, significance of the on-line model parameter estimation, sensitivity of the traffic state estimator to the initial values of the estimated model parameters and to the related standard deviation values, and dynamic tracking of time-varying model parameters. The achieved simulation results are very promising for the subsequent development and testing work that is briefly outlined.
780 citations
Cites background from "The PeMS algorithms for accurate, r..."
...If flows and occupancies are measured instead, mean speeds may be calculated from these values if a g-factor is known or estimated (see Jia et al., 2001 )....
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TL;DR: Results suggest that a 2-3% penetration of cell phones in the driver population is enough to provide accurate measurements of the velocity of the traffic flow, demonstrating the feasibility of the proposed system for real-time traffic monitoring.
Abstract: The growing need of the driving public for accurate traffic information has spurred the deployment of large scale dedicated monitoring infrastructure systems, which mainly consist in the use of inductive loop detectors and video cameras On-board electronic devices have been proposed as an alternative traffic sensing infrastructure, as they usually provide a cost-effective way to collect traffic data, leveraging existing communication infrastructure such as the cellular phone network A traffic monitoring system based on GPS-enabled smartphones exploits the extensive coverage provided by the cellular network, the high accuracy in position and velocity measurements provided by GPS devices, and the existing infrastructure of the communication network This article presents a field experiment nicknamed Mobile Century, which was conceived as a proof of concept of such a system Mobile Century included 100 vehicles carrying a GPS-enabled Nokia N95 phone driving loops on a 10-mile stretch of I-880 near Union City, California, for 8 hours Data were collected using virtual trip lines, which are geographical markers stored in the handset that probabilistically trigger position and speed updates when the handset crosses them The proposed prototype system provided sufficient data for traffic monitoring purposes while managing the privacy of participants The data obtained in the experiment were processed in real-time and successfully broadcast on the internet, demonstrating the feasibility of the proposed system for real-time traffic monitoring Results suggest that a 2-3% penetration of cell phones in the driver population is enough to provide accurate measurements of the velocity of the traffic flow
773 citations
Cites background from "The PeMS algorithms for accurate, r..."
...However, velocities are estimated from single loop detectors, it is known that they include – sometimes substantial – errors, depending on the estimation algorithm used [35, 36]....
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24 Aug 2014
TL;DR: A citywide and real-time model for estimating the travel time of any path (represented as a sequence of connected road segments) in real time in a city, based on the GPS trajectories of vehicles received in current time slots and over a period of history as well as map data sources is proposed.
Abstract: In this paper, we propose a citywide and real-time model for estimating the travel time of any path (represented as a sequence of connected road segments) in real time in a city, based on the GPS trajectories of vehicles received in current time slots and over a period of history as well as map data sources. Though this is a strategically important task in many traffic monitoring and routing systems, the problem has not been well solved yet given the following three challenges. The first is the data sparsity problem, i.e., many road segments may not be traveled by any GPS-equipped vehicles in present time slot. In most cases, we cannot find a trajectory exactly traversing a query path either. Second, for the fragment of a path with trajectories, they are multiple ways of using (or combining) the trajectories to estimate the corresponding travel time. Finding an optimal combination is a challenging problem, subject to a tradeoff between the length of a path and the number of trajectories traversing the path (i.e., support). Third, we need to instantly answer users' queries which may occur in any part of a given city. This calls for an efficient, scalable and effective solution that can enable a citywide and real-time travel time estimation. To address these challenges, we model different drivers' travel times on different road segments in different time slots with a three dimension tensor. Combined with geospatial, temporal and historical contexts learned from trajectories and map data, we fill in the tensor's missing values through a context-aware tensor decomposition approach. We then devise and prove an object function to model the aforementioned tradeoff, with which we find the most optimal concatenation of trajectories for an estimate through a dynamic programming solution. In addition, we propose using frequent trajectory patterns (mined from historical trajectories) to scale down the candidates of concatenation and a suffix-tree-based index to manage the trajectories received in the present time slot. We evaluate our method based on extensive experiments, using GPS trajectories generated by more than 32,000 taxis over a period of two months. The results demonstrate the effectiveness, efficiency and scalability of our method beyond baseline approaches.
488 citations
Cites methods from "The PeMS algorithms for accurate, r..."
...[9, 14, 16] use various models to estimate the travel speed on an individual road segment based on the sensor readings from loop detectors, and then convert the speed into a travel time....
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References
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TL;DR: The PeMS architecture and use are described and traffic engineers can base their operational decisions on knowledge of the current status of the freeway network.
Abstract: Performance Measurement System (PeMS) is a freeway performance measurement system for all of California. It processes 2 GB/day of 30-s loop detector data in real time to produce useful information. At any time managers can have a uniform, comprehensive assessment of freeway performance. Traffic engineers can base their operational decisions on knowledge of the current status of the freeway network. Planners can determine whether congestion bottlenecks can be alleviated by improving operations or by minor capital improvements. Travelers can obtain the current shortest route and travel time estimates. Researchers can validate their theory and calibrate simulation models. PeMS, which has been in stable operation for 18 months, is a low-cost system. It uses the California Department of Transportation (Caltrans) network for data acquisition and is easy to deploy and maintain. It takes under 6 weeks to bring a Caltrans district online, and functionality can be added incrementally. PeMS applications are accessed...
403 citations
"The PeMS algorithms for accurate, r..." refers background in this paper
...However, in congestion, equation ( 3 ) does not hold and we cannot use it to calculate the g-factor....
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...(6) Equation (5) is the same as ( 3 ). We call glnst instantaneous g-factor since it is calculated from the instantaneous volume and occupancy measurements....
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...Moreover, if there is no vehicle driving through a certain loop during the tth measurement, c(t) is zero, and ( 3 ) does not make sense....
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...It is now fully implemented for Districts 7,8, 12. PeMS is being extended to other Caltrans districts The PeMS system comprises (1) a large database that stores historical and real-time data, (2) a set of algorithms including the g-factor and speed estimators that process these data to generate several performance measures (including congestion and travel time); and ( 3 ) a server that delivers this information to managers, engineers, and ......
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...The measurements of traffic are taken on Interstate Highway 80 ( 1-80 ) near Berkeley....
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TL;DR: In this paper, an improved algorithm for estimating velocity from single loop detector data is presented, which is simple enough that it can be implemented using existing controller hardware, and the benefits of this work extend to automated tests of detector data quality at dual loop speed traps.
Abstract: This paper develops an improved algorithm for estimating velocity from single loop detector data. Unlike preceding works, the algorithm is simple enough that it can be implemented using existing controller hardware. The discussion shows how the benefits of this work extend to automated tests of detector data quality at dual loop speed traps. Finally, this paper refutes an earlier study that found conventional single loop velocity estimates are biased.
197 citations
TL;DR: An algorithm for estimating mean traffic speed using volume and occupancy data from a single inductance loop based on the statistics of the measurements obtained from a traffic management system is presented.
Abstract: This paper presents an algorithm for estimating mean traffic speed using volume and occupancy data from a single inductance loop. The algorithm is based on the statistics of the measurements obtained from a traffic management system. The algorithm produces an estimate of speed and provides a reliability test for the speed estimate.
183 citations
01 Oct 2000
TL;DR: The development of the Berkeley Highway Laboratory is presented, which includes surveillance component, eight dual loop speed detector stations and 14 video cameras dedicated research, as well as an analytical component to advance traffic operations and traffic flow theory.
Abstract: This paper presents the development of the Berkeley Highway Laboratory. The laboratory includes surveillance component, eight dual loop speed detector stations and 14 video cameras dedicated research, as well as an analytical component to advance traffic operations and traffic flow theory. The work builds on our experience with the I-880 field experiment and several other traffic studies. The lessons learned from the laboratory will be used to improve traffic surveillance and control, provide new traffic metrics, and enhance traffic models. This paper also presents correction factors that should be beneficial to researchers using the I-880 database.
66 citations
"The PeMS algorithms for accurate, r..." refers background in this paper
...The measurements of traffic are taken on Interstate Highway 80 ( 1-80 ) near Berkeley....
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...(6) Equation ( 5 ) is the same as (3). We call glnst instantaneous g-factor since it is calculated from the instantaneous volume and occupancy measurements....
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