Metro is being developed rapidly in second-tier cities. There is a need to understand the impact it brings as it relates to the planning and management of the whole urban transportation system. In this paper, we applied the multilayer complex network theory to study this problem by contrasting the characteristics of transportation networks before and after the metro is built. We focused on transportation networks in second-tier cities and (1) proposed edge functions of the road subnetwork and rail transit subnetwork with impedance as weight; (2) established an interlayer function based on the transfer behavior to couple the above subnetworks into the multilayer weighted transportation network; and (3) redefined statistical parameters, such as node strength, chessboard coefficient, and average least pass cost. At last, Hohhot, China, a typical second-tier city, was taken as a case study. Calculations show that the new-built metro network in the second-tier city increases convenience and reduces travel cost, whereas, the vulnerability of the whole network increases, and the distribution of key nodes in the road network is reconstructed. For the sustainable development of urban transportation, more attention should be paid to the new-built metro in second-tier cities.
Abstract. In order to explore changes in accessibility and connectivity of urban traffic network before and after the construction of subway, traffic networks within the Second Ring road, Hohhot, was analyzed based on complex network theory. Firstly, the urban road traffic network and the urban compound traffic network with the adjunction of the subway to former were mapped. Secondly, the node degree, clustering coefficient, average path length and node strength of the two networks were calculated based on SuperMap. Finally, the eigenvalues obtained above were compared and analyzed. Results show that both of the two traffic networks have some characteristics of small clustering coefficient reflected in random network and scale-free network. The latter, compared to the former, network diameter and average shortest path reduce, the average node degree and average node intensity increase. That is to say, with the adjunction of the subway, the connectivity and the accessibility of the entire network are significantly improved, and its carrying capacity increases remarkably.
Predictive analytics of the traffic flow is paid more attention by the traffic engineering experts and relevant departments. However, how to forecast traffic volume still is an important problem affecting the traffic theoretical and practical analysis. Firstly, this paper set up a three layers BP neural network basing on the actual situation to introduce the modeling process of the neural network in detail, and forecast the short-term traffic volume by the means of rolling forecast. Secondly, taking the Hailar Street in Hohhot for example, two groups of test data from the same time of different days and sequent time of the same day were trained and forecast. in addition, predicting results and actual results were compared, and the correlations between test data and predicting result was analyzed and disclosed. Finally, the conclusion shows the error is acceptable and BP Neural Network constructed is practical when prediction accuracy is not very high.
Abstract. Identifying and protecting traffic hub is vital to keep the stability and reliability of urban road traffic network. In this paper, a comprehensive evaluation method of node importance in urban road traffic network was introduced based on identification theory of key nodes in complex network. Firstly, taking into account the impact of road network topology and traffic flow characteristics on node's capacity, node importance in topological network and betweenness, urban road grade and node traffic flow are selected as the evaluating indexes of node importance, and AHP is used to determine the weight of each index. Secondly, the associated value of the indexes are calculated and obtained based on SuperMap Deskpro and practical investigation, and then, combined with TOPSIS, a sequence of node importance is determined. Finally, we applied the method to part district of Hohhot road traffic network, it can be seen that the key nodes obtained with the method stay in the important position in the the traffic network and have greater traffic flow, the results showed it is effective and practical feasible.
The integration optimization model of VFP&VRP with multi-type vehicles , multi-kinds and small scale goods was established considering limit goods, total cost was maximized which were composed of fixed cost, variable cost and loss cost on the condition of considering vehicle capacity, time windows and goods characteristics in the model. Additionally, PSO-TS hybrid algorithm solving the model was proposed according to the characteristics of ACO and PSO .In the integrated frame of hybrid algorithm, the VFP and VRP were related by translating goods filling scheme into initial-solve of TS and adopting total objective function to evaluate particle. Finally, the model and algorithm were successfully proved by a given instance.
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