Abstract

This study uses regression analysis to evaluate long-run traffic management system performance. Three important traffic management systems in the Twin Cities metro area - Ramp Metering, Variable Message Signs (VMS), and Freeway Service Patrol (the Highway Helper Program) were evaluated with multiple regression models to predict link speed and incident rate. We find that ramp meters increase freeway link speed and reduce incident rate. Freeway Service Patrols increase link speed when incidents are present. The results for variable message signs are ambiguous. Document type: Part of book or chapter of book

Abstract

This paper presents an empirical assessment of urban traffic congestion in Central London, UK. Compared with freeways or motorways, urban networks are relatively less studied because of its complexity and availability of required traffic data. This paper introduces the use of automatic number plate recognition technology to analyze the characteristic of urban traffic congestion in Central London. We also present the use of linear regression to diagnose the observed congestion and attribute them to different causes. In particular, we distinguish the observed congestion into two main components: one due to recurrent factors and the other due to nonrecurrent factors. The methodologies are illustrated through a case study of Central London Area. It is found that about 15% of the observed congestion in the region is due to nonrecurrent factors such as accidents, roadwork, special events, and strikes. Given the significance of London, the study will be valuable for transport policy evaluation and appraisal in other global cities. Copyright © 2013 John Wiley & Sons, Ltd. Language: en