Evaluation of Coordinated Ramp Metering (CRM) Implemented By Caltrans

Coordinated ramp metering (CRM) is a critical component of smart freeway corridors that rely on real-time traffic data from ramps and freeway mainline to improve decision-making by the motorists and Traffic Management Center (TMC) personnel. CRM uses an algorithm that considers real-time traffic volumes on freeway mainline and ramps and then adjusts the metering rates on the ramps accordingly for optimal flow along the entire corridor. Improving capacity through smart corridors is less costly and easier to deploy than freeway widening due to high costs associated with right-of-way acquisition and construction. Nevertheless, conversion to smart corridors still represents a sizable investment for public agencies. However, in the U.S. there have been limited evaluations of smart corridors in general, and CRM in particular, based on real operational data. This project examined the recent Smart Corridor implementation on Interstate 80 (I-80) in the Bay Area and State Route 99 (SR-99, SR99) in Sacramento based on travel time reliability measures, efficiency measures, and before-and-after safety evaluation using the Empirical Bayes (EB) approach. As such, this evaluation represents the most complete before-and-after evaluation of such systems. The reliability measures include buffer index, planning time, and measures from the literature that account for both the skew and width of the travel time distribution. For efficiency, the study estimates the ratio of vehicle miles traveled vs. vehicle hour traveled. The research contextualizes before-and-after comparisons for efficiency and reliability measures through similar measures from another corridor (i.e., the control corridor of I-280 in District 4 and I-5 in District 3) from the same region, which did not have CRM implemented. The results show there has been an improvement in freeway operation based on efficiency data. Post-CRM implementation, travel time reliability measures do not show a similar improvement. The report also provides a counterfactual estimate of expected crashes in the post-implementation period, which can be compared with the actual number of crashes in the “after” period to evaluate effectiveness

Why do citizens use e-tax system? Extending the technology continuance theory

Among the various online services provided by the government, e-tax system is one of the commonly used e-government platforms, which offers significant benefits to government and citizens by reducing costs, eliminate human errors, and reduce the turnaround time for processing income tax returns. Despite these plausible benefits, some reservations have been articulated regarding the continuance usage intention of e-tax system. Thus, we investigate the most critical factors of e-tax continuance usage in this paper. We developed an integrated theoretical model based on the technology continuance theory (TCT) extended with social influence and perceived risk. The proposed conceptual model was empirically validated with data collected from a sample of 345 e-tax service users in Bangladesh. Partial least squares structural equation modeling (PLS-SEM) was employed to analyze the collected data. The study findings suggest that user satisfaction, perceived usefulness, and attitude have a direct impact on continuance usage intention where confirmation, ease of use and social influence have indirect influence on continuance usage intention of e-tax system. This paper discusses some contributions to theory and practice based on our finding