Computational Intelligence and Neuroscience The latest articles from Hindawi Publishing Corporation © 2014 , Hindawi Publishing Corporation . All rights reserved. Application of Wireless Intelligent Control System for HPS Lamps and LEDs Combined Illumination in Road Tunnel Sun, 21 Dec 2014 00:10:18 +0000 Because of the particularity of the environment in the tunnel, the rational tunnel illumination system should be developed, so as to optimize the tunnel environment. Considering the high cost of traditional tunnel illumination system with high-pressure sodium (HPS) lamps as well as the effect of a single light source on tunnel entrance, the energy-saving illumination system with HPS lamps and LEDs combined illumination in road tunnel, which could make full use of these two kinds of lamps, was proposed. The wireless intelligent control system based on HPS lamps and LEDs combined illumination and microcontrol unit (MCU) Si1000 wireless communication technology was designed. And the remote monitoring, wireless communication, and PWM dimming module of this system were designed emphatically. Intensity detector and vehicle flow detector can be configured in wireless intelligent control system, which gather the information to the master control unit, and then the information is sent to the monitoring center through the Ethernet. The control strategies are got by the monitoring center according to the calculated results, and the control unit wirelessly sends parameters to lamps, which adjust the luminance of each segment of the tunnel and realize the wireless intelligent control of combined illumination in road tunnel. Jinxing Lai, Junling Qiu, Jianxun Chen, Yaqiong Wang, and Haobo Fan Copyright © 2014 Jinxing Lai et al. All rights reserved. Improvement of Adaptive GAs and Back Propagation ANNs Performance in Condition Diagnosis of Multiple Bearing System Using Grey Relational Analysis Thu, 18 Dec 2014 09:23:55 +0000 Condition diagnosis of multiple bearings system is one of the requirements in industry field, because bearings are used in many equipment and their failure can result in total breakdown. Conditions of bearings commonly are reflected by vibration signals data. In multiple bearing condition diagnosis, it will involve many types of vibration signals data; thus, consequently, it will involve many features extraction to obtain precise condition diagnosis. However, large number of features extraction will increase the complexity of the diagnosis system. Therefore, in this paper, we presented a diagnosis method which is hybridization of adaptive genetic algorithms (AGAs), back propagation neural networks (BPNNs), and grey relational analysis (GRA) to diagnose the condition of multiple bearings system. AGAs are used in the diagnosis algorithm to determine the best initial weights of BPNNs in order to improve the diagnosis accuracy. In addition, GRA is applied to determine and select the dominant features from the vibration signal data which will provide good diagnosis of multiple bearings system in less features extraction. The experiments results show that AGAs-BPNNs with GRA approaches can increase the accuracy of diagnosis in shorter processing time, compared with the AGAs-BPNNs without the GRA. Lili A. Wulandhari, Antoni Wibowo, and Mohammad I. Desa Copyright © 2014 Lili A. Wulandhari et al. All rights reserved. Freeway Travel Speed Calculation Model Based on ETC Transaction Data Mon, 15 Dec 2014 00:10:25 +0000 Real-time traffic flow operation condition of freeway gradually becomes the critical information for the freeway users and managers. In fact, electronic toll collection (ETC) transaction data effectively records operational information of vehicles on freeway, which provides a new method to estimate the travel speed of freeway. First, the paper analyzed the structure of ETC transaction data and presented the data preprocess procedure. Then, a dual-level travel speed calculation model was established under different levels of sample sizes. In order to ensure a sufficient sample size, ETC data of different enter-leave toll plazas pairs which contain more than one road segment were used to calculate the travel speed of every road segment. The reduction coefficient α and reliable weight θ for sample vehicle speed were introduced in the model. Finally, the model was verified by the special designed field experiments which were conducted on several freeways in Beijing at different time periods. The experiments results demonstrated that the average relative error was about 6.5% which means that the freeway travel speed could be estimated by the proposed model accurately. The proposed model is helpful to promote the level of the freeway operation monitoring and the freeway management, as well as to provide useful information for the freeway travelers. Jiancheng Weng, Rongliang Yuan, Ru Wang, and Chang Wang Copyright © 2014 Jiancheng Weng et al. All rights reserved. Game Theory Model of Traffic Participants within Amber Time at Signalized Intersection Mon, 15 Dec 2014 00:10:22 +0000 The traffic light scheme is composed of red, green, and amber lights, and it has been defined clearly for the traffic access of red and green lights; however, the definition of that for the amber light is indistinct, which leads to the appearance of uncertainty factors and serious traffic conflicts during the amber light. At present, the traffic administrations are faced with the decision of whether to forbid passing or not during the amber light in the cities of China. On one hand, it will go against the purpose of setting amber lights if forbidding passing; on the other hand, it may lead to a mess of traffic flow running if not. And meanwhile the drivers are faced with the decision of passing the intersection or stopping during the amber light as well. So the decision-making behavior of traffic administrations and drivers can be converted into a double game model. And through quantification of their earnings in different choice conditions, the optimum decision-making plan under specific conditions could be solved via the Nash equilibrium solution concept. Thus the results will provide a basis for the formulation of the traffic management strategy. Weiwei Qi, Huiying Wen, Chuanyun Fu, and Mo Song Copyright © 2014 Weiwei Qi et al. All rights reserved. Risk Evaluation of Bogie System Based on Extension Theory and Entropy Weight Method Wed, 10 Dec 2014 00:10:40 +0000 A bogie system is the key equipment of railway vehicles. Rigorous practical evaluation of bogies is still a challenge. Presently, there is overreliance on part-specific experiments in practice. In the present work, a risk evaluation index system of a bogie system has been established based on the inspection data and experts’ evaluation. Then, considering quantitative and qualitative aspects, the risk state of a bogie system has been evaluated using an extension theory and an entropy weight method. Finally, the method has been used to assess the bogie system of four different samples. Results show that this method can assess the risk state of a bogie system exactly. Yanping Du, Yuan Zhang, Xiaogang Zhao, and Xiaohui Wang Copyright © 2014 Yanping Du et al. All rights reserved. Label Propagation with -Degree Neighborhood Impact for Network Community Detection Wed, 26 Nov 2014 14:25:34 +0000 Community detection is an important task for mining the structure and function of complex networks. In this paper, a novel label propagation approach with -degree neighborhood impact is proposed for efficiently and effectively detecting communities in networks. Firstly, we calculate the neighborhood impact of each node in a network within the scope of its -degree neighborhood network by using an iterative approach. To mitigate the problems of visiting order correlation and convergence difficulty when updating the node labels asynchronously, our method updates the labels in an ascending order on the α-degree neighborhood impact of all the nodes. The -degree neighborhood impact is also taken as the updating weight value, where the parameter impact scope α can be set to a positive integer. Experimental results from several real-world and synthetic networks show that our method can reveal the community structure in networks rapidly and accurately. The performance of our method is better than other label propagation based methods. Heli Sun, Jianbin Huang, Xiang Zhong, Ke Liu, Jianhua Zou, and Qinbao Song Copyright © 2014 Heli Sun et al. All rights reserved. A Novel Adjustment Method for Shearer Traction Speed through Integration of T-S Cloud Inference Network and Improved PSO Sun, 23 Nov 2014 13:18:25 +0000 In order to efficiently and accurately adjust the shearer traction speed, a novel approach based on Takagi-Sugeno (T-S) cloud inference network (CIN) and improved particle swarm optimization (IPSO) is proposed. The T-S CIN is built through the combination of cloud model and T-S fuzzy neural network. Moreover, the IPSO algorithm employs parameter automation adjustment strategy and velocity resetting to significantly improve the performance of basic PSO algorithm in global search and fine-tuning of the solutions, and the flowchart of proposed approach is designed. Furthermore, some simulation examples are carried out and comparison results indicate that the proposed method is feasible, efficient, and is outperforming others. Finally, an industrial application example of coal mining face is demonstrated to specify the effect of proposed system. Lei Si, Zhongbin Wang, Xinhua Liu, Yinwei Yang, and Lin Zhang Copyright © 2014 Lei Si et al. All rights reserved. An Improved Fuzzy c-Means Clustering Algorithm Based on Shadowed Sets and PSO Wed, 12 Nov 2014 00:00:00 +0000 To organize the wide variety of data sets automatically and acquire accurate classification, this paper presents a modified fuzzy -means algorithm (SP-FCM) based on particle swarm optimization (PSO) and shadowed sets to perform feature clustering. SP-FCM introduces the global search property of PSO to deal with the problem of premature convergence of conventional fuzzy clustering, utilizes vagueness balance property of shadowed sets to handle overlapping among clusters, and models uncertainty in class boundaries. This new method uses Xie-Beni index as cluster validity and automatically finds the optimal cluster number within a specific range with cluster partitions that provide compact and well-separated clusters. Experiments show that the proposed approach significantly improves the clustering effect. Jian Zhang and Ling Shen Copyright © 2014 Jian Zhang and Ling Shen. All rights reserved. Numerical Simulation of Nonperiodic Rail Operation Diagram Characteristics Tue, 11 Nov 2014 06:24:49 +0000 This paper succeeded in utilizing cellular automata (CA) model to simulate the process of the train operation under the four-aspect color light system and getting the nonperiodic diagram of the mixed passenger and freight tracks. Generally speaking, the concerned models could simulate well the situation of wagon in preventing trains from colliding when parking and restarting and of the real-time changes the situation of train speeds and displacement and get hold of the current train states in their departures and arrivals. Finally the model gets the train diagram that simulates the train operation in different ratios of the van and analyzes some parameter characters in the process of train running, such as time, speed, through capacity, interval departing time, and departing numbers. Yongsheng Qian, Bingbing Wang, Junwei Zeng, and Xin Wang Copyright © 2014 Yongsheng Qian et al. All rights reserved. High Speed Railway Environment Safety Evaluation Based on Measurement Attribute Recognition Model Sun, 09 Nov 2014 13:29:55 +0000 In order to rationally evaluate the high speed railway operation safety level, the environmental safety evaluation index system of high speed railway should be well established by means of analyzing the impact mechanism of severe weather such as raining, thundering, lightning, earthquake, winding, and snowing. In addition to that, the attribute recognition will be identified to determine the similarity between samples and their corresponding attribute classes on the multidimensional space, which is on the basis of the Mahalanobis distance measurement function in terms of Mahalanobis distance with the characteristics of noncorrelation and nondimensionless influence. On top of the assumption, the high speed railway of China environment safety situation will be well elaborated by the suggested methods. The results from the detailed analysis show that the evaluation is basically matched up with the actual situation and could lay a scientific foundation for the high speed railway operation safety. Qizhou Hu, Ningbo Gao, and Bing Zhang Copyright © 2014 Qizhou Hu et al. All rights reserved. Estimation of Critical Gap Based on Raff’s Definition Sun, 09 Nov 2014 06:38:37 +0000 Critical gap is an important parameter used to calculate the capacity and delay of minor road in gap acceptance theory of unsignalized intersections. At an unsignalized intersection with two one-way traffic flows, it is assumed that two events are independent between vehicles’ arrival of major stream and vehicles’ arrival of minor stream. The headways of major stream follow M3 distribution. Based on Raff’s definition of critical gap, two calculation models are derived, which are named M3 definition model and revised Raff’s model. Both models use total rejected coefficient. Different calculation models are compared by simulation and new models are found to be valid. The conclusion reveals that M3 definition model is simple and valid. Revised Raff’s model strictly obeys the definition of Raff’s critical gap and its application field is more extensive than Raff’s model. It can get a more accurate result than the former Raff’s model. The M3 definition model and revised Raff’s model can derive accordant result. Rui-jun Guo, Xiao-jing Wang, and Wan-xiang Wang Copyright © 2014 Rui-jun Guo et al. All rights reserved. Modeling Design Iteration in Product Design and Development and Its Solution by a Novel Artificial Bee Colony Algorithm Thu, 06 Nov 2014 13:42:00 +0000 Due to fierce market competition, how to improve product quality and reduce development cost determines the core competitiveness of enterprises. However, design iteration generally causes increases of product cost and delays of development time as well, so how to identify and model couplings among tasks in product design and development has become an important issue for enterprises to settle. In this paper, the shortcomings existing in WTM model are discussed and tearing approach as well as inner iteration method is used to complement the classic WTM model. In addition, the ABC algorithm is also introduced to find out the optimal decoupling schemes. In this paper, firstly, tearing approach and inner iteration method are analyzed for solving coupled sets. Secondly, a hybrid iteration model combining these two technologies is set up. Thirdly, a high-performance swarm intelligence algorithm, artificial bee colony, is adopted to realize problem-solving. Finally, an engineering design of a chemical processing system is given in order to verify its reasonability and effectiveness. Tinggui Chen and Renbin Xiao Copyright © 2014 Tinggui Chen and Renbin Xiao. All rights reserved. Modeling Mode Choice Behavior Incorporating Household and Individual Sociodemographics and Travel Attributes Based on Rough Sets Theory Thu, 06 Nov 2014 13:36:09 +0000 Most traditional mode choice models are based on the principle of random utility maximization derived from econometric theory. Alternatively, mode choice modeling can be regarded as a pattern recognition problem reflected from the explanatory variables of determining the choices between alternatives. The paper applies the knowledge discovery technique of rough sets theory to model travel mode choices incorporating household and individual sociodemographics and travel information, and to identify the significance of each attribute. The study uses the detailed travel diary survey data of Changxing county which contains information on both household and individual travel behaviors for model estimation and evaluation. The knowledge is presented in the form of easily understood IF-THEN statements or rules which reveal how each attribute influences mode choice behavior. These rules are then used to predict travel mode choices from information held about previously unseen individuals and the classification performance is assessed. The rough sets model shows high robustness and good predictive ability. The most significant condition attributes identified to determine travel mode choices are gender, distance, household annual income, and occupation. Comparative evaluation with the MNL model also proves that the rough sets model gives superior prediction accuracy and coverage on travel mode choice modeling. Long Cheng, Xuewu Chen, Ming Wei, Jingxian Wu, and Xianyao Hou Copyright © 2014 Long Cheng et al. All rights reserved. Fuzzy Temporal Logic Based Railway Passenger Flow Forecast Model Wed, 05 Nov 2014 11:31:10 +0000 Passenger flow forecast is of essential importance to the organization of railway transportation and is one of the most important basics for the decision-making on transportation pattern and train operation planning. Passenger flow of high-speed railway features the quasi-periodic variations in a short time and complex nonlinear fluctuation because of existence of many influencing factors. In this study, a fuzzy temporal logic based passenger flow forecast model (FTLPFFM) is presented based on fuzzy logic relationship recognition techniques that predicts the short-term passenger flow for high-speed railway, and the forecast accuracy is also significantly improved. An applied case that uses the real-world data illustrates the precision and accuracy of FTLPFFM. For this applied case, the proposed model performs better than the k-nearest neighbor (KNN) and autoregressive integrated moving average (ARIMA) models. Fei Dou, Limin Jia, Li Wang, Jie Xu, and Yakun Huang Copyright © 2014 Fei Dou et al. All rights reserved. Analysis of Vehicle-Following Heterogeneity Using Self-Organizing Feature Maps Wed, 05 Nov 2014 00:00:00 +0000 A self-organizing feature map (SOM) was used to represent vehicle-following and to analyze the heterogeneities in vehicle-following behavior. The SOM was constructed in such a way that the prototype vectors represented vehicle-following stimuli (the follower’s velocity, relative velocity, and gap) while the output signals represented the response (the follower’s acceleration). Vehicle trajectories collected at a northbound segment of Interstate 80 Freeway at Emeryville, CA, were used to train the SOM. The trajectory information of two selected pairs of passenger cars was then fed into the trained SOM to identify similar stimuli experienced by the followers. The observed responses, when the stimuli were classified by the SOM into the same category, were compared to discover the interdriver heterogeneity. The acceleration profile of another passenger car was analyzed in the same fashion to observe the interdriver heterogeneity. The distribution of responses derived from data sets of car-following-car and car-following-truck, respectively, was compared to ascertain inter-vehicle-type heterogeneity. Jie Yang, Ruey Long Cheu, Xiucheng Guo, and Alicia Romo Copyright © 2014 Jie Yang et al. All rights reserved. Safety Assessment of Dangerous Goods Transport Enterprise Based on the Relative Entropy Aggregation in Group Decision Making Model Wed, 05 Nov 2014 00:00:00 +0000 Safety of dangerous goods transport is directly related to the operation safety of dangerous goods transport enterprise. Aiming at the problem of the high accident rate and large harm in dangerous goods logistics transportation, this paper took the group decision making problem based on integration and coordination thought into a multiagent multiobjective group decision making problem; a secondary decision model was established and applied to the safety assessment of dangerous goods transport enterprise. First of all, we used dynamic multivalue background and entropy theory building the first level multiobjective decision model. Secondly, experts were to empower according to the principle of clustering analysis, and combining with the relative entropy theory to establish a secondary rally optimization model based on relative entropy in group decision making, and discuss the solution of the model. Then, after investigation and analysis, we establish the dangerous goods transport enterprise safety evaluation index system. Finally, case analysis to five dangerous goods transport enterprises in the Inner Mongolia Autonomous Region validates the feasibility and effectiveness of this model for dangerous goods transport enterprise recognition, which provides vital decision making basis for recognizing the dangerous goods transport enterprises. Jun Wu, Chengbing Li, and Yueying Huo Copyright © 2014 Jun Wu et al. All rights reserved. A New Cellular Automaton Model for Urban Two-Way Road Networks Tue, 04 Nov 2014 12:31:18 +0000 A new cellular automaton (CA) model is proposed to simulate traffic dynamics in urban two-way road network systems. The NaSch rule is adopted to represent vehicle movements on road sections. Two novel rules are proposed to move the vehicles in intersection areas, and an additional rule is developed to avoid the “gridlock” phenomenon. Simulation results show that the network fundamental diagram is very similar to that of road traffic flow. We found that the randomization probability and the maximum vehicle speed have significant impact on network traffic mobility for free-flow state. Their effect may be weak when the network is congested. Junqing Shi, Lin Cheng, Jiancheng Long, and Yuanlin Liu Copyright © 2014 Junqing Shi et al. All rights reserved. A Red-Light Running Prevention System Based on Artificial Neural Network and Vehicle Trajectory Data Tue, 04 Nov 2014 12:16:44 +0000 The high frequency of red-light running and complex driving behaviors at the yellow onset at intersections cannot be explained solely by the dilemma zone and vehicle kinematics. In this paper, the author presented a red-light running prevention system which was based on artificial neural networks (ANNs) to approximate the complex driver behaviors during yellow and all-red clearance and serve as the basis of an innovative red-light running prevention system. The artificial neural network and vehicle trajectory are applied to identify the potential red-light runners. The ANN training time was also acceptable and its predicting accurate rate was over 80%. Lastly, a prototype red-light running prevention system with the trained ANN model was described. This new system can be directly retrofitted into the existing traffic signal systems. Pengfei Li, Yan Li, and Xiucheng Guo Copyright © 2014 Pengfei Li et al. All rights reserved. A Framework for Spatial Interaction Analysis Based on Large-Scale Mobile Phone Data Tue, 04 Nov 2014 09:34:15 +0000 The overall understanding of spatial interaction and the exact knowledge of its dynamic evolution are required in the urban planning and transportation planning. This study aimed to analyze the spatial interaction based on the large-scale mobile phone data. The newly arisen mass dataset required a new methodology which was compatible with its peculiar characteristics. A three-stage framework was proposed in this paper, including data preprocessing, critical activity identification, and spatial interaction measurement. The proposed framework introduced the frequent pattern mining and measured the spatial interaction by the obtained association. A case study of three communities in Shanghai was carried out as verification of proposed method and demonstration of its practical application. The spatial interaction patterns and the representative features proved the rationality of the proposed framework. Weifeng Li, Xiaoyun Cheng, Zhengyu Duan, Dongyuan Yang, and Gaohua Guo Copyright © 2014 Weifeng Li et al. All rights reserved. Robust Optimization Model and Algorithm for Railway Freight Center Location Problem in Uncertain Environment Tue, 04 Nov 2014 09:16:28 +0000 Railway freight center location problem is an important issue in railway freight transport programming. This paper focuses on the railway freight center location problem in uncertain environment. Seeing that the expected value model ignores the negative influence of disadvantageous scenarios, a robust optimization model was proposed. The robust optimization model takes expected cost and deviation value of the scenarios as the objective. A cloud adaptive clonal selection algorithm (C-ACSA) was presented. It combines adaptive clonal selection algorithm with Cloud Model which can improve the convergence rate. Design of the code and progress of the algorithm were proposed. Result of the example demonstrates the model and algorithm are effective. Compared with the expected value cases, the amount of disadvantageous scenarios in robust model reduces from 163 to 21, which prove the result of robust model is more reliable. Xing-cai Liu, Shi-wei He, Rui Song, Yang Sun, and Hao-dong Li Copyright © 2014 Xing-cai Liu et al. All rights reserved. Modeling the Commuting Travel Activities within Historic Districts in Chinese Cities Tue, 04 Nov 2014 09:15:47 +0000 The primary objective of this study is to analyze the characteristics of commuting activities within the historical districts in cities of China. The impacts of various explanatory variables on commuters’ travels are evaluated using the structural equation modeling (SEM) approach. The household survey was conducted in the historical districts in Yangzhou, China. Based on the data, various individual and household attributes were considered exogenous variables, while the subsistence activity characteristics, travel times, numbers of three typical home-based trip chains, trip chains, and travel mode were considered as the endogenous variables. Commuters in our study were classified into two main groups according to their working location, which were the commuters in the historic district and those out of the district. The modeling results show that several individual and household attributes of commuters in historic district have significant impacts on the characteristics of travel activities. Additionally, the characteristics of travel activities within the two groups are quite different, and the contributing factors related to commuting travels are different as well. Mao Ye, Miao Yu, Zhibin Li, Fengjun Yin, and Qizhou Hu Copyright © 2014 Mao Ye et al. All rights reserved. A Novel Artificial Immune Algorithm for Spatial Clustering with Obstacle Constraint and Its Applications Tue, 04 Nov 2014 09:14:54 +0000 An important component of a spatial clustering algorithm is the distance measure between sample points in object space. In this paper, the traditional Euclidean distance measure is replaced with innovative obstacle distance measure for spatial clustering under obstacle constraints. Firstly, we present a path searching algorithm to approximate the obstacle distance between two points for dealing with obstacles and facilitators. Taking obstacle distance as similarity metric, we subsequently propose the artificial immune clustering with obstacle entity (AICOE) algorithm for clustering spatial point data in the presence of obstacles and facilitators. Finally, the paper presents a comparative analysis of AICOE algorithm and the classical clustering algorithms. Our clustering model based on artificial immune system is also applied to the case of public facility location problem in order to establish the practical applicability of our approach. By using the clone selection principle and updating the cluster centers based on the elite antibodies, the AICOE algorithm is able to achieve the global optimum and better clustering effect. Liping Sun, Yonglong Luo, Xintao Ding, and Ji Zhang Copyright © 2014 Liping Sun et al. All rights reserved. Understanding Attitudes towards Proenvironmental Travel: An Empirical Study from Tangshan City in China Tue, 04 Nov 2014 08:58:24 +0000 Understanding people’s attitudes towards proenvironmental travel will help to encourage people to adopt proenvironmental travel behavior. Revealed preference theory assumes that the consumption preference of consumers can be revealed by their consumption behavior. In order to investigate the influences on citizens’ travel decision and analyze the difficulties of promoting proenvironmental travel behavior in medium-sized cities in China, based on revealed preference theory, this paper uses the RP survey method and disaggregate model to analyze how individual characteristics, situational factors, and trip features influence the travel mode choice. The field investigation was conducted in Tangshan City to obtain the RP data. An MNL model was built to deal with the travel mode choice. SPSS software was used to calibrate the model parameters. The goodness-of-fit tests and the predicted outcome demonstrate the validation of the parameter setting. The results show that gender, occupation, trip purpose, and distance have an obvious influence on the travel mode choice. In particular, the male gender, high income, and business travel show a high correlation with carbon-intensive travel, while the female gender and a medium income scored higher in terms of proenvironmental travel modes, such as walking, cycling, and public transport. Xiaoping Fang, Yajing Xu, and Weiya Chen Copyright © 2014 Xiaoping Fang et al. All rights reserved. Study of Track Irregularity Time Series Calibration and Variation Pattern at Unit Section Tue, 04 Nov 2014 08:40:46 +0000 Focusing on problems existing in track irregularity time series data quality, this paper first presents abnormal data identification, data offset correction algorithm, local outlier data identification, and noise cancellation algorithms. And then proposes track irregularity time series decomposition and reconstruction through the wavelet decomposition and reconstruction approach. Finally, the patterns and features of track irregularity standard deviation data sequence in unit sections are studied, and the changing trend of track irregularity time series is discovered and described. Chaolong Jia, Lili Wei, Hanning Wang, and Jiulin Yang Copyright © 2014 Chaolong Jia et al. All rights reserved. Research on Assessment Methods for Urban Public Transport Development in China Tue, 04 Nov 2014 08:25:01 +0000 In recent years, with the rapid increase in urban population, the urban travel demands in Chinese cities have been increasing dramatically. As a result, developing comprehensive urban transport systems becomes an inevitable choice to meet the growing urban travel demands. In urban transport systems, public transport plays the leading role to promote sustainable urban development. This paper aims to establish an assessment index system for the development level of urban public transport consisting of a target layer, a criterion layer, and an index layer. Review on existing literature shows that methods used in evaluating urban public transport structure are dominantly qualitative. To overcome this shortcoming, fuzzy mathematics method is used for describing qualitative issues quantitatively, and AHP (analytic hierarchy process) is used to quantify expert’s subjective judgment. The assessment model is established based on the fuzzy AHP. The weight of each index is determined through the AHP and the degree of membership of each index through the fuzzy assessment method to obtain the fuzzy synthetic assessment matrix. Finally, a case study is conducted to verify the rationality and practicability of the assessment system and the proposed assessment method. Linghong Zou, Hongna Dai, Enjian Yao, Tian Jiang, and Hongwei Guo Copyright © 2014 Linghong Zou et al. All rights reserved. Rail Mounted Gantry Crane Scheduling Optimization in Railway Container Terminal Based on Hybrid Handling Mode Tue, 04 Nov 2014 08:23:39 +0000 Rail mounted gantry crane (RMGC) scheduling is important in reducing makespan of handling operation and improving container handling efficiency. In this paper, we present an RMGC scheduling optimization model, whose objective is to determine an optimization handling sequence in order to minimize RMGC idle load time in handling tasks. An ant colony optimization is proposed to obtain near optimal solutions. Computational experiments on a specific railway container terminal are conducted to illustrate the proposed model and solution algorithm. The results show that the proposed method is effective in reducing the idle load time of RMGC. Li Wang and Xiaoning Zhu Copyright © 2014 Li Wang and Xiaoning Zhu. All rights reserved. Optimization of the Design of Pre-Signal System Using Improved Cellular Automaton Tue, 04 Nov 2014 08:19:13 +0000 The pre-signal system can improve the efficiency of intersection approach under rational design. One of the main obstacles in optimizing the design of pre-signal system is that driving behaviors in the sorting area cannot be well evaluated. The NaSch model was modified by considering slow probability, turning-deceleration rules, and lane changing rules. It was calibrated with field observed data to explore the interactions among design parameters. The simulation results of the proposed model indicate that the length of sorting area, traffic demand, signal timing, and lane allocation are the most important influence factors. The recommendations of these design parameters are demonstrated. The findings of this paper can be foundations for the design of pre-signal system and show promising improvement in traffic mobility. Yan Li, Ke Li, Siran Tao, Xia Wan, and Kuanmin Chen Copyright © 2014 Yan Li et al. All rights reserved. Analysis of the Contribution of the Road Traffic Industry to the PM2.5 Emission for Different Land-Use Types Tue, 04 Nov 2014 08:14:41 +0000 Road dust and vehicle exhaust are the main sources of air pollution in cities, especially in recent years with the quantity of vehicles and transportation construction continuously soaring; the hazy weather has been a dominant urban pollution form which is widely concerned by the Chinese society. By establishing a relationship model between traffic and land use, then applying analytic hierarchy process on the data from air quality monitoring station, this paper concludes the influence of different traffic behavior on air pollution which provides support to abate urban air pollution caused by traffic reasons through taking measures to control traffic. Peng Xu, Wei Wang, Jiawei Ji, and Shunyu Yao Copyright © 2014 Peng Xu et al. All rights reserved. Study of the Bus Dynamic Coscheduling Optimization Method under Urban Rail Transit Line Emergency Tue, 04 Nov 2014 08:03:24 +0000 As one of the most important urban commuter transportation modes, urban rail transit (URT) has been acting as a key solution for supporting mobility needs in high-density urban areas. However, in recent years, high frequency of unexpected events has caused serious service disruptions in URT system, greatly harming passenger safety and resulting in severe traffic delays. Therefore, there is an urgent need to study emergency evacuation problem in URT. In this paper, a method of bus dynamic coscheduling is proposed and two models are built based on different evacuation destinations including URT stations and surrounding bus parking spots. A dynamic coscheduling scheme for buses can be obtained by the models. In the model solution process, a new concept—the equivalent parking spot—is proposed to transform the nonlinear model into an integer linear programming (ILP) problem. A case study is conducted to verify the feasibility of models. Also, sensitivity analysis of two vital factors is carried out to analyze their effects on the total evacuation time. The results reveal that the designed capacity of buses has a negative influence on the total evacuation time, while an increase in the number of passengers has a positive effect. Finally, some significant optimizing strategies are proposed. Yun Wang, Xuedong Yan, Yu Zhou, Jiaxi Wang, and Shasha Chen Copyright © 2014 Yun Wang et al. All rights reserved. Incident Duration Modeling Using Flexible Parametric Hazard-Based Models Tue, 04 Nov 2014 08:02:36 +0000 Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers. This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model. Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008. Results show that different factors significantly affect different incident time phases, whose best distributions were diverse. Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents. The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time. Ruimin Li and Pan Shang Copyright © 2014 Ruimin Li and Pan Shang. All rights reserved.