Recent advances in vehicle technology offer new opportunities for an electric, automated, modular bus (MB) unit with an adjustable capacity to be applied to transit systems, promising to tackle the resource allocation challenges of traditional buses in coping with uneven travel demand. Drawing on the concept of modular vehicles, this paper introduces a novel scheduling system in which MB units can be combined/separated from fulfilling imbalanced trip demands through capacity adjustments. We develop an optimization model for determining the optimal formation and trip sequence of MB units. In particular, given that the vehicles are electrically powered, battery range limits and charging plans are considered in the system scheduling process. A column-generation-based heuristic algorithm is designed to efficiently solve this model, with constraints related to travel demand and charging station capacity incorporated into the master problem and the trip sequence for modular units with limited energy solved by the subproblem. Taking real data from transit operations for numerical examples, the proposed model performs well in terms of both algorithmic performance and practical applications. The generated optimal MB dispatching scheme can significantly reduce the operating cost from $1534.31 to $1144.26, a decrease of approximately 25% compared to conventional electric buses. The sensitivity analysis on the MB dispatch cost and battery capacity provides some insights for both the scenario configuration and the battery selection for MB system implementation.

The contents of visual working memory (VWM) have been repeatedly found to be linked with attention allocation during visual searching. While the target representation in working memory (target template) was found to affect memory-driven attentional capture in a top-down manner, non-target representation in working memory (non-target template) can also affect attentional selection. The present article reviews existing literature on the modulation of attentional selection by non-target template stored in visual working memory. It is concluded that non-target presentations can not only automatically bias attention to information that matches the non-target template, but also benefit visual search performance by strategically suppressing items that matches the non-target template. The suppression functions of non-target template were affected by several factors including experiment paradigm, task difficulty, characteristics of stimuli and level of cognitive control. Future research should be aimed towards further investigation of its properties and promote both basic and applied research.

a new gray method is provided in this paper for highway lane detection. Firstly, the novel gray method transform an RGB color image to a gray-level image based on a new gray vector. To deal with illumination changes, the new gray vector is updated on real-time.Secondly,the canny edge detector’s threshold values are decided adaptive.Lastly,Hough transform method realizes the detection of lanes. For different time in a day, experiments indicate that the proposed algorithm has good results.

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