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Articles

by Junyi Han
35 Views, 0 PDF Downloads

The definition of degree in complex network is extended based on the lane attributes (number, width and direction) of urban road network. The connection characteristics of intersections and road elements in urban road network under primitive and dual methods are studied respectively. Considering the cognitive characteristics of actual road network and residents’ travel, intersections are defined as nodes, based on named road method. With Stroke-like analysis, road elements are defined from the perspective of residents’ cognition, and the concept of primitive degree is improved by combining the number of motor lanes. Under the new definition of road network elements, the average nearest neighbor degree method based on improved measure is used to analyze the connection characteristics between intersections and roads, and considering the shortcomings of existing methods, the paper puts forward a new concept of primitive degree. The concept of connection coefficient is better defined, and the analysis method is validated by taking the main urban area of Xiamen as an example, and the characteristics of road network connection in the main urban area are analyzed. The results show that the urban intersection element network and road element network are scale-free networks with power exponents of 1.69 and 2.70, respectively. The connection of road network elements takes a critical node as a segment characteristic, and the value of the adjacent points of connection coefficient based on improvement degree is 3.40 and 8, respectively. From this point of view, the urban road network is not a simple homogeneous or heterogeneous network; the proposed method for analyzing the connectivity characteristics of road network elements is used to understand the topological characteristics of urban road network and the evolution model of road network. The construction is of great significance. 

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Articles

by Nan Song
49 Views, 0 PDF Downloads

Accurate analysis of traffic congestion propagation characteristics is a prerequisite for predicting traffic congestion status and solving congestion problems. First of all, combining with the actual traffic conditions, the speed extension discrimination index (ESDI) is proposed, and the road congestion state is divided into 5 levels, and the threshold values of each level are defined, thus constructing a congestion mosaic Shi Kongtu. Propose the rectangle method to draw rules, establish the propagation model analysis method of traffic congestion evolution, study the propagation rules and characteristics of congestion and dissipation, and effectively calculate the propagation speed. Finally, taking Yellow Garden Bridge as an example, the research shows that the road traffic state discrimination method based on ESDI can correctly divide the congestion state of road sections, and the traffic congestion propagation model based on rectangular method can effectively obtain the evolution characteristics of road congestion, including frequent or sporadic congestion, starting and ending time of dissipation, propagation speed and occurrence reasons, etc.

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Articles

by Bin Sun
31 Views, 0 PDF Downloads

Essentials, JTG B01-2014 Technical Standard for Highway Engineering No longer specifies the recommended value for width of highway central separation band , but emphasizes that should be determined according to the function of central separation band This increases the design flexibility while also increasing the difficulty of width selection of central separation band. Through the analysis of relevant specifications, combined with relevant engineering practice, proposed the minimum width recommended value .Under the condition of meeting the basic function of the central separation belt.

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Articles

by Ziming Wang
43 Views, 0 PDF Downloads

The generalized travel cost of cars considering energy consumption and congestion charge and the generalized travel cost of buses considering comfort consumption are established respectively, and the total energy consumption function of transportation system is constructed. Considering the influence of energy consumption on travelers' path selection behavior, a bi-level programming model with minimum travel time as upper objective function is established. The lower model satisfies the stochastic user balance of the dual-mode traffic network, and is solved by genetic algorithm and Frank-Wolfe algorithm. Through an example, the road congestion charging and energy-saving targets are abstracted into the model, and the change of traffic energy consumption before and after road charging and the energy-saving effect of road congestion charging under different energy-saving targets are discussed. The calculation results show that when the traffic demand is large, the implementation of road congestion charging is beneficial to reduce the traffic energy consumption, and when the energy-saving target is less than 25% and road charging is adopted at the same time, the road network travel time will be correspondingly reduced.

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Articles

by Wenxing Xia
30 Views, 0 PDF Downloads

Existing geometric feature-based target detection and tracking methods have high false detection rate, and missed detection in target tracking process easily leads to false target correlation. To solve these problems, this paper proposes vehicle target detection and tracking method based on LiDAR depth data. According to lidar depth data characteristics, a grid-based parameter automatic clustering (PAG) algorithm is used to process the original data. In addition, target segments are extracted from each cluster to obtain target features. On this basis, vehicle targets are identified and position information of the targets is calculated. Kalman filter algorithm is adopted to formulate filter management strategy to complete target association and state estimation. Finally, an experimental vehicle equipped with forward laser radar is used to verify the proposed method. Experimental results show that the proposed method can accurately identify and track multiple vehicle targets and avoid erroneous target association.

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