Traffic Data On-the-fly PDF Download

Author: Alican Karaer
Publisher:
ISBN:
Category : Civil engineering
Languages : en
Pages : 0

Get Book Here

Book Description
Also, the performance of the model was significantly better on identifying signal crosswalks (92.5%) and uncontrolled major road crossings (96.6%) regardless of zebra or non-zebra pavement markings. The final results revealed that there are 861 mid-block, 30,784 signal, and 29,307 driveway crosswalks on the state roads in Florida. The proposed framework can be adapted in other locations where the appropriate imagery and vector data are available and is expected to contribute on the wider use of machine learning in transport policy. Finally, the fifth case study presented the literature review and the state of the art on drone utilization for traffic monitoring with the desired traffic data while providing the background on computer vision and particularly on the Multi Object Tracking (MOT) methodology with a preliminary case study to perform a real-time object detection on webcam. The provided summary of drone utilization among the U.S. transportation agencies can help stakeholders on how to benefit from UAS technology on their day-to-day work. Moreover, uniform traffic study manuals can be updated with the presented desired data analysis to help practitioners perform drone-based traffic monitoring. Furthermore, the benchmark MOT algorithms along with their data sets and performance metrics were introduced and a case study for real-time object detection was performed to pave the way for real-time naturalistic trajectory extraction and analysis. A small program was developed using python programing language, and the code was shared to apply real-time object detection on the images extracted from users' webcam. Overall findings of this dissertation depict that regardless of the imagery data source or image processing method, a comprehensive pre-processing step should be performed with a focus on the targeted end data. In addition, satellite imagery and remote sensing methods powered by GIS, provide free and exhaustive data that can be used for smarter cities. Deep learning methods have extensive power over image data; in fact, some models for certain tasks have already surpassed human performance. However, it requires serious understanding to convert commonly known neural network models to perform slightly different tasks than what they were initially trained for. Tethered drones have also been promising solutions to collect continuous and automated traffic data. However, there is a trade off since the operation is too sensitive to weather events such as wind.