Impact Assessing of Traffic Lights via GPS Vehicle Trajectories

The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic...

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Autores principales:	Zhuhua Liao, Hao Xiao, Silin Liu, Yizhi Liu, Aiping Yi
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	deep learning traffic light detection impact assessment multi-input model Geography (General) G1-922
Acceso en línea:	https://doaj.org/article/cdbb01d4e57e4c369e17491b96e99fa6
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id	oai:doaj.org-article:cdbb01d4e57e4c369e17491b96e99fa6
record_format	dspace
spelling	oai:doaj.org-article:cdbb01d4e57e4c369e17491b96e99fa62021-11-25T17:53:07ZImpact Assessing of Traffic Lights via GPS Vehicle Trajectories10.3390/ijgi101107692220-9964https://doaj.org/article/cdbb01d4e57e4c369e17491b96e99fa62021-11-01T00:00:00Zhttps://www.mdpi.com/2220-9964/10/11/769https://doaj.org/toc/2220-9964The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we propose a low-cost and fast traffic signal detection and impact assessment framework, which detects traffic lights from GPS trajectories and intersection features in a supervised way, and analyzes the impact range and time of traffic lights from intersection track data segments. The experimental results show that our approach gains the best AUC value of 0.95 under the ROC standard classification and indicates that the impact pattern of traffic lights at intersections is high related to the travel rule of traffic participants.Zhuhua LiaoHao XiaoSilin LiuYizhi LiuAiping YiMDPI AGarticledeep learningtraffic light detectionimpact assessmentmulti-input modelGeography (General)G1-922ENISPRS International Journal of Geo-Information, Vol 10, Iss 769, p 769 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	deep learning traffic light detection impact assessment multi-input model Geography (General) G1-922
spellingShingle	deep learning traffic light detection impact assessment multi-input model Geography (General) G1-922 Zhuhua Liao Hao Xiao Silin Liu Yizhi Liu Aiping Yi Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
description	The adaptability of traffic lights in the control of vehicle traffic heavily affects the trafficability of vehicles and the travel efficiency of traffic participants in busy urban areas. Existing studies mainly have focused on the presence of traffic lights, but rarely evaluate the impact of traffic lights by analyzing traffic data, thus there is no solution for practicably and precisely self-regulating traffic lights. To address these issues, we propose a low-cost and fast traffic signal detection and impact assessment framework, which detects traffic lights from GPS trajectories and intersection features in a supervised way, and analyzes the impact range and time of traffic lights from intersection track data segments. The experimental results show that our approach gains the best AUC value of 0.95 under the ROC standard classification and indicates that the impact pattern of traffic lights at intersections is high related to the travel rule of traffic participants.
format	article
author	Zhuhua Liao Hao Xiao Silin Liu Yizhi Liu Aiping Yi
author_facet	Zhuhua Liao Hao Xiao Silin Liu Yizhi Liu Aiping Yi
author_sort	Zhuhua Liao
title	Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
title_short	Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
title_full	Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
title_fullStr	Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
title_full_unstemmed	Impact Assessing of Traffic Lights via GPS Vehicle Trajectories
title_sort	impact assessing of traffic lights via gps vehicle trajectories
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/cdbb01d4e57e4c369e17491b96e99fa6
work_keys_str_mv	AT zhuhualiao impactassessingoftrafficlightsviagpsvehicletrajectories AT haoxiao impactassessingoftrafficlightsviagpsvehicletrajectories AT silinliu impactassessingoftrafficlightsviagpsvehicletrajectories AT yizhiliu impactassessingoftrafficlightsviagpsvehicletrajectories AT aipingyi impactassessingoftrafficlightsviagpsvehicletrajectories
_version_	1718411888478388224

Impact Assessing of Traffic Lights via GPS Vehicle Trajectories

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