Construction Site Entrance Vehicle Queue Length Prediction Video Dataset

#Image Recognition #Vehicle Detection #Queue Length Prediction #Construction Site Vehicle Scheduling #Congestion Management #Site Monitoring
  • 500 records
  • 1.2G
  • MP4
  • CC-BY-NC-SA 4.0
  • MOBIUSI INCMOBIUSI INC
Updated:2026-02-04

AI Analysis & Value Prop

Construction sites often face frequent vehicle movements and congestion, leading to inefficient resource allocation. Existing solutions mostly rely on manual management or fixed camera monitoring, which suffer from poor real-time capabilities and low detection accuracy. This dataset aims to address the issue of accurately predicting vehicle queue lengths at construction site entrances to optimize site vehicle scheduling. Video data is collected through high-definition cameras installed at the site entrance, with the collection process conducted in both clear and rainy weather, and over multiple periods to cover various scenarios. Videos are manually screened to ensure their typicality and representativeness. During annotation, videos undergo multiple rounds of review and consistency checks to ensure data consistency and accuracy. The annotation team consists of experts with over 5 years of video analysis experience. Preprocessing steps include video clipping, denoising, and keyframe extraction, with all data being structurally stored in MP4 format.

Technical Specifications

FieldTypeDescription
file_namestringFile name
durationstringDuration
qualitystringResolution
vehicle_countintThe total number of vehicles queued in the video.
queue_lengthfloatThe total length of the vehicle queue on the driveway, measured in meters.
average_vehicle_speedfloatThe average speed of vehicles in the queue, measured in meters per second.
weather_conditionstringThe weather condition during the video recording, such as sunny, rainy, etc.
time_of_daystringThe time period during video recording, such as morning, afternoon, evening.
vehicle_type_distributionjsonThe distribution of different vehicle types in the video, such as cars, trucks, construction vehicles, etc.
traffic_light_statusstringThe status of the traffic light in the video, such as red, green.

Compliance Statement

Authorization TypeCC-BY-NC-SA 4.0 (Attribution–NonCommercial–ShareAlike)
Commercial UseRequires exclusive subscription or authorization contract (monthly or per-invocation charging)
Privacy and AnonymizationNo PII, no real company names, simulated scenarios follow industry standards
Compliance SystemCompliant with China's Data Security Law / EU GDPR / supports enterprise data access logs

Frequently Asked Questions

What problem can this dataset help solve?
This dataset can be used to predict the queue length of vehicles at construction site entrances, assisting in on-site scheduling and management.
How is the video data in the dataset collected?
The video data is usually collected by installing cameras at the construction site entrance, which record the vehicle queuing conditions in real time.
What impact does the dataset have on the construction industry?
The dataset can enhance the efficiency of construction sites, reduce vehicle wait times, and improve traffic flow, playing a positive role in the daily operations of construction sites.
What kind of research or projects is this dataset suitable for?
This dataset is suitable for projects related to traffic management systems research, site planning, resource allocation optimization, and smart construction site development.
How can this dataset be used to improve construction site operations efficiency?
By predicting queue lengths, managers can better schedule vehicle entry and exit times, thereby reducing congestion and improving overall site operational efficiency.

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Cite this Work

@dataset{Mobiusi2026,
  title={Construction Site Entrance Vehicle Queue Length Prediction Video Dataset},
  author={MOBIUSI INC},
  year={2026},
  url={https://www.mobiusi.com/datasets/b3eca0e723b06c5b5b85ebbf7fd8eecc},
  urldate={2026-02-04},
  keywords={Vehicle Queue Prediction, Construction Site Video Analysis, Construction Site Vehicle Management, Queue Length Measurement},
  version={1.0}
}

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