The supply of highway facilities in urban and suburban areas across South Korea has not kept pace with automobile growth, resulting in traffic congestion, and congested roads have contributed to worsen operation and safety problems with high fuel consumption. Traffic agencies and engineers in South Korea have focused on mitigating congestions through Intelligent Transportation Systems (ITS), demand managements, and other conventional measures. Unfortunately, these conventional countermeasures were exhausted in Korea to mitigate traffic congestion. From the viewpoint of efficiency and safety, a superstreet might be one of the alternatives to be considered for solving traffic problems. A superstreet is an unconventional intersection which redirects left turn and through movements from side streets. The design concept leads to increase safety by reducing conflict points at a major crossing point and operating like a pair of one-way streets which signals independently control from the both directions. Prior research have reviewed the performance of the implemented superstreets in North Carolina, U.S and showed a significant improvement in operation and safety compared to existing conventional intersection designs. The purpose of this paper is to provide insight on the potential to implement a superstreet as a promising solution for improving mobility and safety in the South Korea. This paper evaluated how a superstreet design effectively and safely handles with given traffic circumstances compared to an existing design. The VISSIM Model was selected to simulate the operations of subject intersections and Surrogate Safety Assessment Model (SSAM), developed by Federal Highway Administration (FHWA), which performs conflict analysis by processing vehicles trajectory data extracted from micro-simulations, was adopted to evaluate safety estimations. The results showed that the corridor with superstreets have the most effective progression of traffic along the entire road section with the fewest stops and lowest delays. Also it indicated that superstreets would contribute to have a decrease in collisions. The results would suffice to provide traffic agencies and engineers with an effective alternative to improve safety while reducing congestion.

Accurate detection of road surface conditions in adverse winter weather is essential for traffic safety. To promote safe driving and efficient road management, this study presents an accurate and generalizable data-driven learning model for the estimation of road surface conditions. The machine model was a support vector machine (SVM), which has been successfully applied in diverse fields, and kernel functions (linear, Gaussian, second-order polynomial) with a soft margin classification technique were also adopted. Two learner designs (one-vs-one, one-vs-all) extended their application to multi-class classification. In addition to this non-probabilistic classifier, this study calculated the posterior probability of belonging to each group by applying the sigmoid function to the classification scores obtained by the trained SVM. The results indicate that the classification errors of all the classifiers, excluding the one-vs-all linear learners, were below 3%, thereby accurately classifying road surface conditions, and that the generalization performance of all the one-vs-one learners was within an error rate of 4%. The results also showed that the posterior probabilities can analyze certain atmospheric and road surface conditions that correspond to a high probability of hazardous road surface conditions. Therefore, this study demonstrates the potential of data-driven learning models in classifying road surface conditions accurately.

In the dense cities of developing countries, freeway designers need to provide large capacities in small areas. The nano-interchange, a new system interchange, attempts to address this challenge. The authors designed each alternative at 35, 45, and 55 mph ramp design speeds. The designs revealed that the nano-interchange saves space for any given ramp speed, and the construction plus right-of-way costs may not be much higher than the four-level. Operation estimations showed small travel time savings for the four-level interchange at any particular design speed. Safety evaluations indicated that the nano-interchange will likely cause more reported collisions at ramp junctions. Overall, designers should consider the nano-interchange when they want to keep ramp design speeds higher, but designers willing to reduce ramp design speeds will find the four-level a tough competitor.