A method to estimate traffic penetration rates of commercial floating car data using speed information

Download

index.pdf

Date

2022-08-05

Author

Altintasi, Oruc
Tüydeş Yaman, Hediye
Tuncay, Kağan

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

112
views

39
downloads

Floating Car Data (FCD) are being increasingly used as an alternative traffic data source due to its lower cost and high coverage area. FCD can be obtained by tracking vehicle trajectories individually or by processing multiple tracks anonymously to produce average speed information commercially. For commercial FCD, the spatio-temporal distribution of these vehicles in actual traffic, traffic Penetration Rate (PR) is the most important factor affecting the accuracy of speed estimations, despite the high number of registered vehicles feeding to an FCD provider, denoting the market PR. This study proposes a method for assessing the traffic PR of commercial FCD by evaluating its speed estimation quality compared to Ground Truth (GT) data. GT speed data were employed to generate different levels of traffic PR using Monte Carlo (MC) simulations, which resulted in the development of Quality-PR (Q-PR) relations for Mean Absolute Percentage Error (MAPE) and Root Mean Square Error (RMSE) as selected Measures of Effectiveness (MoE). Simulation-based FCD results at an urban road segment in Ankara (Turkey) showed that a quality of FCD with traffic PR of 15% or more would improve significantly. Use of the developed Q-PR relations suggested an approximately 5% traffic PR for the commercial FCD speeds at the location.

Subject Keywords

commercial floating car data, floating car data quality, penetration rate, probe vehicle, Monte Carlo simulations, TRAVEL-TIME ESTIMATION, VEHICLES, NUMBER, SIZE, commercial floating car data, floating car data quality, Monte Carlo simulatio, penetration rate, probe vehicle

URI

https://hdl.handle.net/11511/99655

Journal

Transport

DOI

https://doi.org/10.3846/transport.2022.17069

Collections

Department of Civil Engineering, Article

Suggestions

OpenMETU
Core

Monitoring urban traffic from floating car data (fcd): using speed or a los-based state measure Altıntaşı, Oruç; Tüydeş Yaman, Hediye; Tuncay, Kağan (Springer, Cham, 2019-01-01) Floating Car Data (FCD) has an important traffic data source due to its lower cost and higher coverage despite its reliability problems. FCD obtained from GPS equipped vehicles can provide speed data for many segments in real-time, as provided by Be-Mobile for urban regions in Turkey. Though only providing speed per consecutive road segments, FCD is a great data source to visualize urban traffic state, in the absence of any other traffic data source, which is the focus of this study. After evaluation of var...
Quality of floating car data (FCD) as a surrogate measure for urban arterial speed Altintasi, Oruc; Tüydeş Yaman, Hediye; Tuncay, Kağan (Canadian Science Publishing, 2019-12-01) Commercial floating car data (FCD) is being increasingly used as a traffic data source due to its lower cost despite concerns about its reliability. This paper focuses on the evaluation of FCD speed quality as a surrogate measure for arterial speed from different aspects. First, FCD speed is compared to video-based traffic data, collected from a specific urban road segment and assumed as ground truth in (a) descriptive evaluations, (b) speed estimation, and (c) level of service estimation. Regression analys...
On Strategies Improving Accuracy of Speed Prediction from Floating Car Data (FCD) Tüydeş Yaman, Hediye; Kocamaz, Korhan; Tuncay, Kağan (2021-09-08) For smart mobility, speed data extracted from Floating Car Data (FCD) plays an important role in speed predictionaccuracy. However, there are reliability issues for commercial FCD due to processing of individual vehicletracking data, and imposed temporal averaging to compress data size. Furthermore, spatial discretizationsignificantly affects the accuracy of the prediction due to uneven segment lengths and highly variable dataavailability in the network. In this study, these issues are examined in detail, a...
A new algorithm for automatic road network extraction in multispectral satellite images Karaman, Ersin; Çınar, Umut; Gedik, Ekin; Çetin, Yasemin; Halıcı, Uğur (2012-05-09) The aim of this study is to develop automatic road extraction algorithm in satellite images. As roads have different width and surface material characteristics in urban and rural areas, a modular approach for road extraction algorithm is desired. In this study, edge detection, segmentation, clustering and vegetation and land cover analyses are used. In order to combine the results of different methods, a score map based on segmentation analysis is constructed. Quantitative and visual results show that this ...
An integrated incident detection methodology with gps-equipped vehicles Demiroluk, Sami; Tüydeş Yaman, Hediye; Department of Civil Engineering (2007) Recurrent congestion in urban traffic networks, especially on arterials, is a growing problem. Non-recurrent congestion, mainly due to incidents, only aggravates the problem. Any solution requires monitoring of the network, for which many developing countries, such as Turkey, do not have the traditional surveillance systems on arterials mainly due to high costs. An alternative solution is the utilization of Global Positioning System (GPS) technology, which is increasingly used in traffic monitoring. It is e...

Citation Formats

O. Altintasi, H. Tüydeş Yaman, and K. Tuncay, “A method to estimate traffic penetration rates of commercial floating car data using speed information,” Transport, vol. 37, no. 3, pp. 161–176, 2022, Accessed: 00, 2022. [Online]. Available: https://hdl.handle.net/11511/99655.