Special issue: Smart transportation: Theory and practice

The special issue of Journal of Advanced Transportation is devoted to the dissemination of the state-of-the-art research on the smart transportation topics ranging from theory to practice. Neumann and colleagues addressed the traffic data fusion problem of using multiple data sources to make better estimation of travel times instead of using a single data source. Wen and Yan investigated the problem of predicting work zone traffic capacity for smarter work zone traffic managements. With consideration of capacity variation, they proposed a truncated lognormal model to predict the work zone capacity distribution. Rim and colleagues proposed a filtering-based model to detect and correct the outliers of GPS speed measures. In the proposed model, the locally weighted regression (LWR) filter was adopted. Bie and colleagues proposed an optimization model to improve the coordinated signal settings of hook-turn intersections. The proposed model was formulated as a mixed nonlinear integer problem for minimizing the average vehicle delays in the study network. Kala proposed an agent-based model to investigate the feasibility of developing cooperative transportation systems, which enables a few emergent vehicles to reach their destinations on time with a priority. In the proposed model, cooperative traffic lights were set to give a priority to emergent vehicles at intersections. Tahmasseby and colleagues examined the potential of using a social network based carpooling system for staff and students of University of Calgary.