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

Current trends in the mining sector and specifically tailings storage facilities have seen a significant increase in monitoring frequency, instrumentation installed on site and field tests conducted. Monitoring methodologies are also shifting away from analog and towards digital electronic systems. These instruments are also being integrated with online dashboards. Owing to all these factors, the instrument that is now most commonly being installed to meet these requirements are VWP’s (Vibrating Wire Piezometers). However interpreting VWP results and deriving the phreatic surface from these are not as straight forward as initially assumed, it requires engineering judgement and a methodology to determine and verify optimum pairing of VWP clusters. Obtaining the correct phreatic surface from VWP’s is critical as this will have a direct impact on the trigger levels and TARP’s of the online dashboard. Inaccuracies in calculating the phreatic surface can lead to the triggering of incorrect levels, which may result in flawed assessments of stability. The primary approach relied on phreatic surface and hydraulic gradients from CPTu testing being compared to the phreatic surface and hydraulic gradient determined from various combinations of VWP’s in a cluster at the time of CPTu testing. In cases where no historical VWP data is available at the time of CPTu testing, a methodology was also investigated using standpipe piezometers only. Piezometric head was converted to pressure and linear regression used to determine the phreatic surface. Results from the primary approach showed that certain pairs of VWP’s yield phreatic surfaces and hydraulic gradients that match the CPTu findings. Standpipe interpretation provided a good starting point and correlates with primary identified pairs. This methodology provides a verification tool to provide confidence when selecting VWP combinations for dashboard reporting.

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