Real-Time Dynamic Traffic Control Based on Traffic-State Estimation

The accurate depiction of the existing traffic state on a road network is essential in reducing congestion and delays at signalized intersections. The existing literature in the optimization of signal timings either utilizes prediction of traffic state from traffic flow models or limited real-time measurements available from sensors. Prediction of traffic state based on historic data cannot represent the dynamics of change in traffic demand or network capacity. Similarly, data obtained from limited point sensors in a network provides estimates which contain errors. A reliable estimate of existing traffic state is, therefore, necessary to obtain signal timings which are based on the existing condition of traffic on the network. This research proposes a framework which utilizes estimates of traffic flows and travel times based on real-time estimated traffic state for obtaining optimal signal timings. The prediction of traffic state from the Cell Transmission Model (CTM) and measurements from traffic sensors are combined in the recursive algorithm of Extended Kalman Filter (EKF) to obtain a reliable estimate of existing traffic state. The estimate of traffic state obtained from the CTM-EKF model is utilized in the optimization of signal timings using Genetic Algorithm (GA) in the proposed CTM-EKF-GA framework. The proposed framework is applied to a synthetic signalized intersection and the results are compared with a model-based optimal solution and simulated reality. The optimal delay estimated by CTM-EKF-GA framework is only 0.6% higher than the perfect solution, whereas the delay estimated by CTM-GA model is 12.9% higher than the perfect solution

The impact of sexual harassment on job satisfaction, turnover intentions, and absenteeism: findings from Pakistan compared to the United States

The purpose of this study was to compare and contrast how differences in perceptions of sexual harassment impact productive work environments for employees in Pakistan as compared to the US; in particular, how it affects job satisfaction, turnover, and/or absenteeism. This study analyzed employee responses in Pakistan (n = 146) and the United States (n = 102, 76) using questionnaire data. Significant results indicated that employees who were sexually harassed reported (a) a decrease in job satisfaction (b) greater turnover intentions and (c) a higher rate of absenteeism. Cross-cultural comparisons indicated that (a) Pakistani employees who were sexually harassed had greater job dissatisfaction and higher overall absenteeism than did their US counterparts and (b) Pakistani women were more likely to use indirect strategies to manage sexual harassment than were US targets