Probabilistic estimation of temporary lanes at road work zones

Graf, Regine; Wimmer, Andreas; Dietmayer, Klaus

doi:10.1109/itsc.2012.6338764

Cited by 3 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Graf et al ( 20 ) investigate a more limited example in which temporary lane markers assist drivers through a work zone. This method monitors the lanes even if both temporary and original lane markers are present.…”

Section: Literature Reviewmentioning

confidence: 99%

Vision-Based Work Zone Safety Alert System in a Connected Vehicle Environment

Cui

Hou

Zhang

et al. 2023

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Work zones, being a critical component of roadway transportation systems, can benefit greatly from computer vision-enabled roadway infrastructures, specifically in connected vehicle (CV) environments. Connected infrastructures, such as roadside units (RSU) and on-board units (OBU), can greatly improve the environmental awareness and safety of CVs driving through a work zone. The contribution of this paper lies in developing a vision-based approach to generate work zone safety messages in real time, utilizing video streams from roadside monocular traffic cameras that can be used by CV work zone safety apps on mobile devices to reliably navigate through a work zone. A monocular traffic camera calibration method is proposed to establish the accurate mapping between the image plane and Global Position System (GPS) space. Real test scenarios show that our algorithm can precisely and effectively locate work zone boundaries from a monocular traffic camera in real time. We demonstrate the capabilities and features of our system through real-world experiments where the driver cannot see the work zone. End-to-end latency analysis reveals that the vision-based work zone safety warning system satisfies the active safety latency requirements. This vision-based work zone safety alert system ensures the safety of both the worker and the driver in a CV environment.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

Vision-Based Work Zone Safety Alert System in a Connected Vehicle Environment

Cui

Hou

Zhang

et al. 2023

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

show abstract

“…Point-based event detection can be summarized as the process of confirming the existence of the event, which is also a necessary step in the route-based event detection. Figure 1b shows the process of route-based event detection which involves the ''event initialization'' (event estimation) and ''event cancellation'' (11). The location information in the detection result is a set of points instead of one point of interest.…”

Section: Existing Workmentioning

confidence: 99%

Traffic Event Detection from Consumer Vehicle Sensor Data: An Autonomous Vehicle Study

Zhang¹

2022

Transportation Research Record: Journal of the Transportation R

View full text Add to dashboard Cite

Traffic event detection from vehicles’ on-board sensors can detect the road information and improve traffic management and safety. Current sensor-based traffic event detection is mainly based on probe vehicles, test vehicles, or other designated vehicles, which is costly and cannot be deployed on a large scale. With the fast development of on-board equipment, data collection from consumer vehicle sensors is becoming popular and can cover a large geographic scale with almost no equipment or labor cost. However, there are very few studies of the data features and potential for application. This paper presents a pipeline for employing consumer vehicle sensors to detect roadworks. The unique data features and deficiencies of the consumer vehicle sensor are discussed and summarized. A clustering method is employed to distinguish the roadwork sites. A route builder method is proposed to reconstruct the routes of the roadworks and to extract the corresponding start and end locations. Compared with ground truth, roadworks detection from consumer vehicle sensors can cover up to 86% of the roadworks on freeways and over 40% of the roadworks on non-freeway roads. The average offset errors are 4.7% on freeways, and 24.9% on non-freeway roads. Compared with point-based roadworks detection from “ViaMichelin Traffic information,” the results from consumer vehicle sensors achieved a matching ratio of nearly 90% and were advantageous in extracting the roadworks route information. This study proves the possibility of employing consumer vehicle sensors for route-based traffic event detection and provides insights for countering uneven distribution and trajectory truncation issues related to privacy protection.

show abstract

Work Zone Detection For Autonomous Vehicles

Shi

Rajkumar

2021

2021 IEEE International Intelligent Transportation Systems Conference (ITSC)

View full text Add to dashboard Cite

Probabilistic estimation of temporary lanes at road work zones

Cited by 3 publications

References 10 publications

Vision-Based Work Zone Safety Alert System in a Connected Vehicle Environment

Vision-Based Work Zone Safety Alert System in a Connected Vehicle Environment

Traffic Event Detection from Consumer Vehicle Sensor Data: An Autonomous Vehicle Study

Work Zone Detection For Autonomous Vehicles

Contact Info

Product

Resources

About