Practical Management of Distance Based Toll System for Urban Expressway

According to the extension of ETC （Electronic Toll Collection） System, the distance based toll system has been recently introduced to realize the effective traffic management for urban transport networks. In the study, urban road network in Keihanshin area is analyzed as an empirical study. The traffic assignment technique is modified to estimate the traffic conditions on the network with describing the individual route charging as well as diversion traffic. The impact of implementation of distance based toll onto the real scale transport network can be evaluated to discuss the social benefit of road users. The advanced technique with intelligent information processing can be proposed to determine the optimal combination of parameters in distance based toll function. In the study, the reduction of total travel time of road users is regarded as the index of the social benefit on urban network. Therefore, the estimation model of total travel time is created by neural network without the estimation process for large scale network. After the optimal combination of parameters is determined, practical road pricing policy on the urban network can be analyzed. Finally, the optimal function form of distance based toll is recommended in practical implementation.

Indexing the bit-code and distance for fast KNN search in high-dimensional spaces

Various index structures have recently been proposed to facilitate high-dimensional KNN queries, among which the techniques of approximate vector presentation and one-dimensional (1D) transformation can break the curse of dimensionality. Based on the two techniques above, a novel high-dimensional index is proposed, called Bit-code and Distance based index (BD). BD is based on a special partitioning strategy which is optimized for high-dimensional data. By the definitions of bit code and transformation function, a high-dimensional vector can be first approximately represented and then transformed into a 1D vector, the key managed by a B+-tree. A new KNN search algorithm is also proposed that exploits the bit code and distance to prune the search space more effectively. Results of extensive experiments using both synthetic and real data demonstrated that BD out- performs the existing index structures for KNN search in high-dimensional spaces.

PRODUCT IMAGE RETRIEVAL BASED ON CO-FEATURES OF THE OBJECT

In this paper, we propose a product image retrieval method based on the object contour corners, image texture and color. The product image mainly highlights the object and its background is very simple. According to these characteristics, we represent the object using its contour, and detect the corners of contour to reduce the number of pixels. Every corner is described using its approximate curvature based on distance. In addition, the Block Difference of Inverse Probabilities (BDIP) and Block Variation of Local Correlation (BVLC) texture features and color moment are extracted from image's HIS color space. Finally, dynamic time warping method is used to match features with different length. In order to demonstrate the effect of the proposed method, we carry out experiments in Mi-crosoft product image database, and compare it with other feature descriptors. The retrieval precision and recall curves show that our method is feasible.

基于危险值分布流模型的飞机时间间隔计算方法

前后两架飞机的间隔是影响进近航路容量的关键因素,为了在飞机进近阶段前后两架飞机之间既能保持安全,又能最大程度地缩小两机之间的尾流间隔,提升进近阶段的到达容量,使用一种改进的Lighthill-Whitham-Richards(LWR)的交通流量模型,改进后的LWR模型将进场着陆的飞机发生碰撞冲突的概率视为与飞机数量相关的连续分布,称为危险值分布,通过危险值分布预测发生冲突的概率,使用速度平差法计算不同机型组合的安全间隔。基于危险值分布流模型对进近阶段上不满足间隔的飞机提出速度调整方法,使飞机之间保持所需的最小间隔时间,以便能够最佳利用进场着陆空域的容量。