The Experts below are selected from a list of 1647 Experts worldwide ranked by ideXlab platform

Francesc Robuste - One of the best experts on this subject based on the ideXlab platform.

  • Travel Time Estimation Travel Time Estimation from Multiple Data Sources
    2016
    Co-Authors: Francesc Soriguera, Dulce Rosas, D. Abeijon, L. Thorson, Francesc Robuste
    Abstract:

    Travel time is the best indicator of the level of service in a road link, and perhaps the most important variable for measuring congestion. This paper presents a method for estimating accurate travel times in Toll Highways using data from multiple sources, as loop detectors and Toll tickets. The proposed methodology consists of a data fusion technique using different travel time estimations in order to obtain a more accurate fused value with less error than individual estimations by itself. Finally results obtained in the application of the methodology to the AP-7 highway, near Barcelona in Spain, are presented

  • travel time measurement in closed Toll Highways
    2010
    Co-Authors: Francesc Soriguera, Dulce Rosas, Francesc Robuste
    Abstract:

    Travel time for a road trip is a drivers' most appreciated traffic information. Measuring travel times on a real time basis is also a perfect indicator of the level of service in a road link, and therefore is a useful measurement for traffic managers in order to improve traffic operations on the network. In conclusion, accurate travel time measurement is one of the key factors in traffic management systems. This paper presents a new approach for measuring travel times on closed Toll Highways using the existing surveillance infrastructure. In a closed Toll system, where Toll plazas are located on the on/off-ramps and each vehicle is charged a particular fee depending on its origin and destination, the data used for Toll collection can also be valuable for measuring mainline travel times on the highway. The proposed method allows estimating mainline travel times on single sections of highway (defined as a section between two neighboring ramps) using itineraries covering different origin-destinations. The method provides trip time estimations without investing in any kind of infrastructure or technology. This overcomes some of the limitations of other methods, like the information delay and the excess in the travel time estimation due to the accumulation of exit times (i.e. the time required to travel along the exit link plus the time required to pay the fee at the Toll gate). The results obtained in a pilot test on the AP-7 Toll highway, near Barcelona in Spain, show that the developed methodology is sound.

Soriguera Martí Francesc - One of the best experts on this subject based on the ideXlab platform.

  • Highway travel time estimation with data fusion
    2016
    Co-Authors: Soriguera Martí Francesc
    Abstract:

    This monograph presents a simple, innovative approach for the measurement and short-term prediction of highway travel times based on the fusion of inductive loop detector and Toll ticket data. The methodology is generic and not technologically captive, allowing it to be easily generalized for other equivalent types of data. The book shows how Bayesian analysis can be used to obtain fused estimates that are more reliable than the original inputs, overcoming some of the drawbacks of travel-time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) from the available data, without recurrent and costly requirements for additional data. The application of the algorithms to empirical testing in the AP-7 Toll highway in Barcelona proves that it is possible to develop an accurate real-time, travel-time information system on closed-Toll Highways with the existing surveillance equipment, suggesting that highway operators might provide their customers with such an added value with little additional investment in technology

  • Highway travel time estimation with data fusion
    2016
    Co-Authors: Soriguera Martí Francesc
    Abstract:

    Travel time information is the key indicator of highway management performance and one of the most appreciated inputs for highway users. Despite this relevance, the interest of highway operators in providing approximate travel time information is quite recent. Besides, highway administrations have only recently begun to gather such information as a means to measure the accessibility service provided by the road, in terms of quality and reliability. In the last century, magnetic loop detectors played a fundamental role in providing traffic volume information and also, with less accuracy, information on average speed and highway occupancy. New traffic monitoring technologies (intelligent cameras, GPS or cell phone tracking, Bluetooth identification, new MeMS detectors, etc.) have appeared in the recent decades and permit considerable improvement in travel time data gathering. Some of the new technologies are cheap (Bluetooth), others are not (cameras); but in any case most of the main Highways are still monitored by magnetic loop detectors. It makes sense to use their basic information and enrich it, when needed, with new data sources. This monograph presents a simple approach for the measurement and short term prediction of highway travel times based on the fusion of inductive loop detector and Toll ticket data. The methodology is generic and it is not technologically captive: it could be easily generalized to other equivalent types of data. Bayesian analysis makes it possible to obtain fused estimates that are more reliable than the original inputs, overcoming some drawbacks of travel time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) of the available data, without falling in the recurrent and costly request of additional data needs. The application of the algorithms to empirical testing in the AP-7 Toll highway in Barcelona proves that it is possible to develop an accurate real-time travel time information system on closed Toll Highways with the existing surveillance equipment. Therefore, highway operators could give this added value to their customers at almost no extra investment.Peer Reviewe

  • Highway travel time estimation with data fusion
    2016
    Co-Authors: Soriguera Martí Francesc
    Abstract:

    Travel time information is the key indicator of highway management performance and one of the most appreciated inputs for highway users. Despite this relevance, the interest of highway operators in providing approximate travel time information is quite recent. Besides, highway administrations have only recently begun to gather such information as a means to measure the accessibility service provided by the road, in terms of quality and reliability. In the last century, magnetic loop detectors played a fundamental role in providing traffic volume information and also, with less accuracy, information on average speed and highway occupancy. New traffic monitoring technologies (intelligent cameras, GPS or cell phone tracking, Bluetooth identification, new MeMS detectors, etc.) have appeared in the recent decades and permit considerable improvement in travel time data gathering. Some of the new technologies are cheap (Bluetooth), others are not (cameras); but in any case most of the main Highways are still monitored by magnetic loop detectors. It makes sense to use their basic information and enrich it, when needed, with new data sources. This monograph presents a simple approach for the measurement and short term prediction of highway travel times based on the fusion of inductive loop detector and Toll ticket data. The methodology is generic and it is not technologically captive: it could be easily generalized to other equivalent types of data. Bayesian analysis makes it possible to obtain fused estimates that are more reliable than the original inputs, overcoming some drawbacks of travel time estimations based on unique data sources. The developed methodology adds value and obtains the maximum (in terms of travel time estimation) of the available data, without falling in the recurrent and costly request of additional data needs. The application of the algorithms to empirical testing in the AP-7 Toll highway in Barcelona proves that it is possible to develop an accurate real-time travel time information system on closed Toll Highways with the existing surveillance equipment. Therefore, highway operators could give this added value to their customers at almost no extra investment.Peer ReviewedPostprint (published version

Francesc Soriguera - One of the best experts on this subject based on the ideXlab platform.

  • Travel Time Estimation Travel Time Estimation from Multiple Data Sources
    2016
    Co-Authors: Francesc Soriguera, Dulce Rosas, D. Abeijon, L. Thorson, Francesc Robuste
    Abstract:

    Travel time is the best indicator of the level of service in a road link, and perhaps the most important variable for measuring congestion. This paper presents a method for estimating accurate travel times in Toll Highways using data from multiple sources, as loop detectors and Toll tickets. The proposed methodology consists of a data fusion technique using different travel time estimations in order to obtain a more accurate fused value with less error than individual estimations by itself. Finally results obtained in the application of the methodology to the AP-7 highway, near Barcelona in Spain, are presented

  • travel time measurement in closed Toll Highways
    2010
    Co-Authors: Francesc Soriguera, Dulce Rosas, Francesc Robuste
    Abstract:

    Travel time for a road trip is a drivers' most appreciated traffic information. Measuring travel times on a real time basis is also a perfect indicator of the level of service in a road link, and therefore is a useful measurement for traffic managers in order to improve traffic operations on the network. In conclusion, accurate travel time measurement is one of the key factors in traffic management systems. This paper presents a new approach for measuring travel times on closed Toll Highways using the existing surveillance infrastructure. In a closed Toll system, where Toll plazas are located on the on/off-ramps and each vehicle is charged a particular fee depending on its origin and destination, the data used for Toll collection can also be valuable for measuring mainline travel times on the highway. The proposed method allows estimating mainline travel times on single sections of highway (defined as a section between two neighboring ramps) using itineraries covering different origin-destinations. The method provides trip time estimations without investing in any kind of infrastructure or technology. This overcomes some of the limitations of other methods, like the information delay and the excess in the travel time estimation due to the accumulation of exit times (i.e. the time required to travel along the exit link plus the time required to pay the fee at the Toll gate). The results obtained in a pilot test on the AP-7 Toll highway, near Barcelona in Spain, show that the developed methodology is sound.

Jardim-gonçalves Ricardo - One of the best experts on this subject based on the ideXlab platform.

  • Novel Big Data-supported dynamic Toll charging system: Impact assessment on Portugal’s shadow-Toll Highways
    2019
    Co-Authors: Figueiras Paulo, Gonçalves Diogo, Costa Ruben, Guerreiro Guilherme, Georgakis Panos, Jardim-gonçalves Ricardo
    Abstract:

    Traffic congestion is a huge problem in many countries. It affects not only the inner workings of cities but also the quality of life of the people that endure it. In Portugal, traffic congestion happens mainly on national/urban roads, and this phenomenon has increased since the introduction of the so called shadow-Toll systems in Highways that were free to use. This work proposes a Toll charging system that relies on a novel dynamic congestion charging scheme, supported by state of the art Big Data technologies, in order to shift traffic from national/urban roads to Tolled Highways, taking into account not only the Quality of Service of the Highways and national roads, but also the competitiveness of Toll prices for users. This Intelligent Transportation System was tested and validated in a real-world scenario with one of the biggest freight logistics companies in Portugal and with the Portuguese public road infrastructure operator.This work was performed under the scope of the OPTIMUM Project - Multi-source Big Data Fusion Driven Proactivity for Intelligent Mobility, grant agreement number 636160-2, funded by the European Union's Horizon 2020 research and innovation programme.Accepted versio

Dulce Rosas - One of the best experts on this subject based on the ideXlab platform.

  • Travel Time Estimation Travel Time Estimation from Multiple Data Sources
    2016
    Co-Authors: Francesc Soriguera, Dulce Rosas, D. Abeijon, L. Thorson, Francesc Robuste
    Abstract:

    Travel time is the best indicator of the level of service in a road link, and perhaps the most important variable for measuring congestion. This paper presents a method for estimating accurate travel times in Toll Highways using data from multiple sources, as loop detectors and Toll tickets. The proposed methodology consists of a data fusion technique using different travel time estimations in order to obtain a more accurate fused value with less error than individual estimations by itself. Finally results obtained in the application of the methodology to the AP-7 highway, near Barcelona in Spain, are presented

  • travel time measurement in closed Toll Highways
    2010
    Co-Authors: Francesc Soriguera, Dulce Rosas, Francesc Robuste
    Abstract:

    Travel time for a road trip is a drivers' most appreciated traffic information. Measuring travel times on a real time basis is also a perfect indicator of the level of service in a road link, and therefore is a useful measurement for traffic managers in order to improve traffic operations on the network. In conclusion, accurate travel time measurement is one of the key factors in traffic management systems. This paper presents a new approach for measuring travel times on closed Toll Highways using the existing surveillance infrastructure. In a closed Toll system, where Toll plazas are located on the on/off-ramps and each vehicle is charged a particular fee depending on its origin and destination, the data used for Toll collection can also be valuable for measuring mainline travel times on the highway. The proposed method allows estimating mainline travel times on single sections of highway (defined as a section between two neighboring ramps) using itineraries covering different origin-destinations. The method provides trip time estimations without investing in any kind of infrastructure or technology. This overcomes some of the limitations of other methods, like the information delay and the excess in the travel time estimation due to the accumulation of exit times (i.e. the time required to travel along the exit link plus the time required to pay the fee at the Toll gate). The results obtained in a pilot test on the AP-7 Toll highway, near Barcelona in Spain, show that the developed methodology is sound.