Scipediacontent: Scipediacontent moved page Draft Content 274189534 to Gu et al 2019a

2021-02-12T12:27:59Z

Scipediacontent moved page Draft Content 274189534 to Gu et al 2019a

Scipediacontent: Created page with " == Abstract == Floating car data are beneficial in estimating traffic conditions in wide areas and are playing an increasing role in traffic surveillance. However, widesprea..."

2021-02-12T12:27:56Z

Created page with " == Abstract == Floating car data are beneficial in estimating traffic conditions in wide areas and are playing an increasing role in traffic surveillance. However, widesprea..."

New page

== Abstract ==

Floating car data are beneficial in estimating traffic conditions in wide areas and are playing an increasing role in traffic surveillance. However, widespread application is limited by low-sample frequency which makes it hard to get a complete picture of a vehicle’s motion. An accurate and reliable reconstruction of a vehicle’s trajectory could effectively result in a higher sampling frequency enabling a more accurate estimation of road traffic parameters. Existing methods require additional information such as nearby vehicles, signal timing strategies, and queue patterns which are not always available. To address this problem, this paper presents a method used with low-sample frequency data to reconstruct vehicle trajectories through intersections, without the need for extra information. Furthermore, the additional parameters for the speed-time curve distributions for deceleration rate and acceleration rate are generated. A piecewise deceleration and acceleration model is developed to calculate the acceleration rate for different travel modes in the trajectory. The distribution parameters of the acceleration data for each travel mode are then estimated using a new Expectation Maximization (EM) algorithm. The acceleration statistics are then used to reconstruct the corresponding parts of the trajectory. Compared to the reference trajectories (truth), the test results show that the method developed in this paper achieves improvement in accuracy ranging from 16 to 67% over the commonly used linear interpolation method. In addition, the proposed method is not very sensitive to the sampling interval of the floating car data, unlike the linear interpolation method where the error grows rapidly with increasing sampling interval.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_274189534-beopen164-1881-document.pdf</pdf>

== Original document ==

The different versions of the original document can be found in:

* [http://downloads.hindawi.com/journals/jat/2019/9417471.pdf http://downloads.hindawi.com/journals/jat/2019/9417471.pdf] under the license https://creativecommons.org/licenses/by

* [http://dx.doi.org/10.1155/2019/9417471 http://dx.doi.org/10.1155/2019/9417471] under the license cc-by

* [http://downloads.hindawi.com/journals/jat/2019/9417471.pdf http://downloads.hindawi.com/journals/jat/2019/9417471.pdf],
: [http://downloads.hindawi.com/journals/jat/2019/9417471.xml http://downloads.hindawi.com/journals/jat/2019/9417471.xml],
: [http://dx.doi.org/10.1155/2019/9417471 http://dx.doi.org/10.1155/2019/9417471] under the license http://creativecommons.org/licenses/by/4.0

* [http://dx.doi.org/10.1155/2019/9417471 http://dx.doi.org/10.1155/2019/9417471],
: [https://doaj.org/toc/0197-6729 https://doaj.org/toc/0197-6729],
: [https://doaj.org/toc/2042-3195 https://doaj.org/toc/2042-3195] under the license http://creativecommons.org/licenses/by/4.0/

* [https://www.hindawi.com/journals/jat/2019/9417471 https://www.hindawi.com/journals/jat/2019/9417471],
: [http://downloads.hindawi.com/journals/jat/2019/9417471.pdf http://downloads.hindawi.com/journals/jat/2019/9417471.pdf],
: [https://academic.microsoft.com/#/detail/2946736663 https://academic.microsoft.com/#/detail/2946736663]

← Older revision	Revision as of 12:27, 12 February 2021
(No difference)

Gu et al 2019a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 274189534 to Gu et al 2019a

Scipediacontent: Created page with " == Abstract == Floating car data are beneficial in estimating traffic conditions in wide areas and are playing an increasing role in traffic surveillance. However, widesprea..."