Vehicle-to-Infrastructure-Based Traffic Signal Optimization for Isolated Intersection

Traffic signal control is critical for traffic efficiency optimization but is usually constrained by traffic detection methods. The emerging V2I (Vehicle to Infrastructure) technology is capable of providing rich information for traffic detection, thus becoming promising for traffic signal control. Based on parallel simulation, this paper presents a new traffic signal optimization method in a V2I environment. In the proposed method, a predictive optimization problem is formulated, and a cellular automata model is employed as traffic flow model. By using genetic algorithm, the predictive optimization problem is solved online to implement receding horizon control. Simulation results show that the proposed method can improve traffic efficiency in the sense of reducing average delay and number of stops. Meanwhile, simulation also shows that greater communication range brings better performance for reducing the average number of stops. Simulation results show that the proposed V2I-based signal control method can improve traffic efficiency, especially when the traffic volume is relatively high. The proposed algorithm can be applied to traffic signal control to improve traffic efficiency

The influence of amino and hydroxyl of chitosan on hydroxyl radical scavenging activity

In order to determine the effect of the amido and hydroxyl of chitosan on antioxidant activity, a series of N-deacetylated chitosan with a degree of deacetylation (D.D.) ranging from 45% to 95% were prepared using region selective N-acetylation of chitosan. Their carboxymethyl derivatives (CMC) were also synthesized according to previous method. The antioxidant activity was evaluated on the basis of their abilities to scavenge hydroxyl radical. The results indicated that the hydroxyl radical scavenging ability depended on the degree of deacetylation and concentration. It also showed that the 2-NH 2 had a closer relation than 6-OH in hydroxyl radical scavenging activities. ©2009 Crown