SUMMARY: 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.

Recently, a dynamic traffic control system designated as dynamic intersection signal control optimization (DISCO) has been developed. DISCO considers the entire fundamental diagram of traffic flow, which is essential for controlling congested and transient traffic. As a dynamic model, DISCO works with time-variant traffic patterns and derives dynamic timing plans. In this study, we applied DISCO to a congested network in Hong Kong and studied the various control strategies enabled by DISCO. The results showed that DISCO outperformed the existing plans by 30–40% in overall delay reductions. DISCO performed best under the most flexible control scheme of variable-green no-cycle strategy, given a good initial solution for the algorithm. Nevertheless, even good fixed-time plans can produce remarkable results.