Sign in to use this feature.

Years

Between: -

Subjects

remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline
remove_circle_outline

Journals

remove_circle_outline

Article Types

Countries / Regions

remove_circle_outline

Search Results (1)

Search Parameters:
Keywords = Red Light Runner (RLR)

Order results
Result details
Results per page
Select all
Export citation of selected articles as:
18 pages, 889 KiB  
Article
Dynamic All-Red Signal Control Based on Deep Neural Network Considering Red Light Runner Characteristics
by Seong Kyung Kwon, Hojin Jung and Kyoung-Dae Kim
Appl. Sci. 2020, 10(17), 6050; https://doi.org/10.3390/app10176050 - 1 Sep 2020
Cited by 2 | Viewed by 2813
Abstract
Despite recent advances in technologies for intelligent transportation systems, the safety of intersection traffic is still threatened by traffic signal violation, called the Red Light Runner (RLR). The conventional approach to ensure the intersection safety under the threat of an RLR is to [...] Read more.
Despite recent advances in technologies for intelligent transportation systems, the safety of intersection traffic is still threatened by traffic signal violation, called the Red Light Runner (RLR). The conventional approach to ensure the intersection safety under the threat of an RLR is to extend the length of the all-red signal when an RLR is detected. Therefore, the selection of all-red signal length is an important factor for intersection safety as well as traffic efficiency. In this paper, for better safety and efficiency of intersection traffic, we propose a framework for dynamic all-red signal control that adjusts the length of all-red signal time according to the driving characteristics of the detected RLR. In this work, we define RLRs into four different classes based on the clustering results using the Dynamic Time Wrapping (DTW) and the Hierarchical Clustering Analysis (HCA). The proposed system uses a Multi-Channel Deep Convolutional Neural Network (MC-DCNN) for online detection of RLR and also classification of RLR class. For dynamic all-red signal control, the proposed system uses a multi-level regression model to estimate the necessary all-red signal extension time more accurately and hence improves the overall intersection traffic safety as well as efficiency. Full article
(This article belongs to the Special Issue Trustworthiness in Mobile Cyber Physical Systems)
Show Figures

Figure 1

Back to TopTop