Impact of Crowdsourced Speed Check Data on Traffic Speed: A Case Study of the Netherlands

作     者：Liu, Yutian Bahrami, Sina Feng, Tao de Vries, Jorn 

作者机构：Department of Built Environment Eindhoven University of Technology Eindhoven Netherlands Urban and Data Science Lab Graduate School of Advanced Science and Engineering Hiroshima University Japan Flitsmeister Veenendaal Netherlands 

出 版 物：《SSRN》 

年 卷 期：2022年

核心收录：

主　　题：Navigation 

摘      要：The proliferation of smartphones and internet connectivity has provided the opportunity of using crowdsourced data in traffic management. Nowadays, many people use navigation apps such as Google Maps, Waze, and Flitsmeister to obtain real-time travel information and provide feedback on road conditions such as reporting police speed checks. As an accurate traffic speed prediction is of great significance for road users and traffic managers, different models have been proposed and widely used to predict traffic speed considering spatio-temporal dependence of traffic data and external factors such as weather, accident and point of interest. This study investigates the impact of crowdsourced data about police enforcement from navigation apps on traffic speed. In addition, we examine whether the police enforcement report affects the accuracy of the deep learning prediction model. We extract crowdsourced police enforcement information from navigation apps, collect the corresponding historical traffic speed data, and predict traffic speed in several corridors in the Netherlands using a GCN-GRU traffic speed prediction model. The results show that the crowdsourced data for police enforcement causes the average vehicle speed to drop between 1 [km/h] to 3 [km/h] when passing the road segments marked with police activity. Moreover, the prediction performance of the GCN-GRU model during the periods without police enforcement is better than the periods with reported police activity showing that police speed check reports can decrease the accuracy of speed prediction models. © 2022, The Authors. All rights reserved.