Scipediacontent: Scipediacontent moved page Draft Content 193028163 to Zhang Fu 2020a

2021-02-15T11:20:33Z

Scipediacontent moved page Draft Content 193028163 to Zhang Fu 2020a

Scipediacontent: Created page with " == Abstract == At an intersection with complex traffic flow, the early detection of the intention of drivers in surrounding vehicles can enable advanced driver assistance sy..."

2021-02-15T11:20:30Z

Created page with " == Abstract == At an intersection with complex traffic flow, the early detection of the intention of drivers in surrounding vehicles can enable advanced driver assistance sy..."

New page

== Abstract ==

At an intersection with complex traffic flow, the early detection of the intention of drivers in surrounding vehicles can enable advanced driver assistance systems (ADAS) to warn the driver in advance or prompt its subsystems to assess the risk and intervene early. Although different drivers show various driving characteristics, the kinematic parameters of human-driven vehicles can be used as a predictor for predicting the driver’s intention within a short time. In this paper, we propose a new hybrid approach for vehicle behavior recognition at intersections based on time series prediction and deep learning networks. First, the lateral position, longitudinal position, speed, and acceleration of the vehicle are predicted using the online autoregressive integrated moving average (ARIMA) algorithm. Next, a variant of the long short-term memory network, called the bidirectional long short-term memory (Bi-LSTM) network, is used to detect the vehicle’s turning behavior using the predicted parameters, as well as the derived parameters, i.e., the lateral velocity, lateral acceleration, and heading angle. The validity of the proposed method is verified at real intersections using the public driving data of the next generation simulation (NGSIM) project. The results of the turning behavior detection show that the proposed hybrid approach exhibits significant improvement over a conventional algorithm; the average recognition rates are 94.2% and 93.5% at 2 s and 1 s, respectively, before initiating the turning maneuver.

Document type: Article

== Full document ==
<pdf>Media:Draft_Content_193028163-beopen959-7683-document.pdf</pdf>

== Original document ==

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

* [http://europepmc.org/articles/PMC7506877 http://europepmc.org/articles/PMC7506877] under the license https://creativecommons.org/licenses/by

* [https://www.mdpi.com/1424-8220/20/17/4887/pdf https://www.mdpi.com/1424-8220/20/17/4887/pdf]

* [https://dblp.uni-trier.de/db/journals/sensors/sensors20.html#ZhangF20a https://dblp.uni-trier.de/db/journals/sensors/sensors20.html#ZhangF20a],
: [https://www.mdpi.com/1424-8220/20/17/4887 https://www.mdpi.com/1424-8220/20/17/4887],
: [https://www.mdpi.com/1424-8220/20/17/4887/pdf https://www.mdpi.com/1424-8220/20/17/4887/pdf],
: [https://academic.microsoft.com/#/detail/3082841044 https://academic.microsoft.com/#/detail/3082841044] under the license cc-by

* [https://www.mdpi.com/1424-8220/20/17/4887 https://www.mdpi.com/1424-8220/20/17/4887],
: [https://doaj.org/toc/1424-8220 https://doaj.org/toc/1424-8220]

* [https://www.mdpi.com/1424-8220/20/17/4887/pdf https://www.mdpi.com/1424-8220/20/17/4887/pdf],
: [http://dx.doi.org/10.3390/s20174887 http://dx.doi.org/10.3390/s20174887]

under the license https://creativecommons.org/licenses/by/4.0/

← Older revision	Revision as of 11:20, 15 February 2021
(No difference)

Zhang Fu 2020a - Revision history

Scipediacontent: Scipediacontent moved page Draft Content 193028163 to Zhang Fu 2020a

Scipediacontent: Created page with " == Abstract == At an intersection with complex traffic flow, the early detection of the intention of drivers in surrounding vehicles can enable advanced driver assistance sy..."