Correlation Analysis of Internet Car and Urban Traffic Congestion Based on Logistics Regression Congestion

Internet car travel has become one of the commonly used modes of travel. The order and trajectory data of the internet car provides a new data source for studying urban traffic congestion. Therefore, based on the data of Beijing internet car on weekdays and weekends, this paper calculates the average travel speed by using the order interval time and trajectory data, and cluster analysis of the overall sample. Logistics regression analysis is used to quantify the relationship between order data and travel speed from the perspective of time. Combined with the data analysis results, the traffic operation state is divided. The multi-scenario analysis method is used to analyze the impact of different average travel speed on urban traffic congestion. This paper analyzes the correlation between internet car and traffic congestion, and can provide reference for traffic congestion management in the future.