Using Google Maps Data for Low-Cost Traffic Speed Monitoring

Abstract: Every year, millions of lives are lost around the world as a result of violations of traffic laws, especially excessive speeding, which continues to be a considerable issue in road safety management. When assessing the efficacy of a road network, vehicular speed is a critical metric. Inconsistencies and abrupt fluctuations in traffic speed typically indicate the presence of congestion, collisions, or other disruptive occurrences. This study utilizes a Python script in Visual Studio Code, employing web scraping techniques with Selenium to gather and analyse data on vehicle speeds and travel times. A comparison of the traffic patterns on weekdays and weekends was made, with particular attention paid to the variations that occurred at peak, lunchtime, and evening hours. The findings suggest significant differences in speed, with weekdays experiencing considerably lower speeds during morning and evening rush hours, while weekends maintain higher and more consistent speeds throughout the day. These insights can provide strategies for the optimization of traffic flow, the improvement of road safety, and the guidance of metropolitan development plans.