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This research aims at establishing an integrated urban public transport system with a subway route supplemented by conventional bus lines, in order to enable residents’ “door-to-door” travel. This paper first analyzed the attraction area of the subway, and then used the GIS tools to calculate and analyze residents’ accessibility to adjacent bus stops. Moreover, it created a preliminary layout of bus stops for residential areas with extremely low accessibility using an improved potential model. From the perspective of minimizing residents’ travel costs and bus stop infrastructure deployment costs, a bus stop site selection optimization model was developed. According to the characteristics of the model, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to solve the optimal bus stop locations. In addition, the entropy weight technique for order of preference by similarity to ideal solution (TOPSIS) evaluation model was used to evaluate and sort candidate schemes, accordingly, and thus the optimal site selection scheme was identified. Finally, a before-after comparative analysis on residents’ travel accessibility was conducted. Results show that the proposed method can effectively improve residents’ accessibility to bus stops, which facilitates residents to transfer from conventional bus to subway. Furthermore, it provides a basis for the follow-up optimization of the connection between subway and conventional bus lines.

Cylindrical shell subjected to axial compression is very sensitive to the initial geometric imperfection. Even very small initial imperfection would significantly reduce the critical load. In this paper, the post-buckling behaviors of functionally graded (FG) porous magneto-electro-elastic (MEE) cylindrical shell with initial geometric imperfection is investigated by using the high-order shear deformation theory. The post-buckling equilibrium paths for different imperfection amplitudes are obtained by Galerkin’s method. Several numerical examples are presented to demonstrate the accuracy of the proposed model and reveal the effects of geometrical parameters, material properties, external magneto-electric loads on the post-buckling equilibrium path. In addition, the imperfection sensitivity of FG porous MEE cylindrical shells is also discussed.

Travel trajectories of individuals, collected by smartphone sensors, carry substantial trip chain information on advanced urban transportation operation. Automatic information extraction plays a cr...

This paper proposes an approach combining historical data and real-time situation information to forecast the bus arrival time. The approach includes two phases. Firstly, Radial Basis Function Neural Networks (RBFNN) model is used to learn and approximate the nonlinear relationship in historical data in the first phase. Then, in the second phase, an online oriented method is introduced to adjust to the actual situation, which means to use the practical information to modify the predicted result of RBFNN in the first phase. Afterwards, the system designing outline is given to summarize the structure and components of the system. We did an experimental study on bus route No.21 in Dalian by deploying this system to demonstrate the validity and effectiveness of this approach. In addition, Multiple Linear Regression model, BP Neural Networks and RBFNN without online adjustment are used in contrast. Results show that the approach with RBFNN and online adjustment has a better predicting performance.

In order to analyze the existing problems of temporary reversible lane, traffic conflict characteristic at the period of direction changing was analyzed. Taking Huangpu Road as the investigation object, the data of traffic conflict before and after direction changing were investigated respectively. By the method of mathematical statistics, the traffic conflict characteristic before and after direction changing were compared and analyzed. Using the method of regression analysis, the prediction model of traffic conflict was constructed. This paper also discussed the problem of utilization ratio of this kind of lane. The research showed that, in terms of traffic conflict of temporary reversible lane, there are obvious and regular differences between before and after direction changing. There is a certain relationship among the quantity of traffic conflict, flow and density. The problem of lower lane utilization ratio of temporary reversible lane usually exists.

Trajectory information recognition is an efficient and convenient approach for trip information obtaining. The trajectory segmentation is a pivotal step to group data into travel parts and activity parts. This paper presents a study on a novel fast search clustering method generalized into the trajectory segmentation. The clustering algorithm was extended and the selection of the cut-off distance was discussed. A comparison among four segmentation methods including two empirical and two clustering methods were conducted to examine the effect of them. The result shows that the two clustering methods achieve lower segment error rate, point error rate, and miss rate than the empirical methods. The fast search algorithm works with the three error rates below 0.03, which can provide reliable samples for information recognition.

In order to reveal the traffic characteristics at signalized intersections with road-side bus lane, the analysis methods of capacity and delay at entrance lane were studied. Selecting a signalized intersection with road-side bus lane as investigation location, several traffic parameters were surveyed. Considering the traffic conflict between right-turn vehicles and through buses in this kind of entrance lane and based on the Gap Acceptance Theory, the calculation model of saturation flow rate, which is a key parameter both in the formulas of capacity and delay at signalized intersection mentioned in HCM2000, was improved. Using the investigation data, the calculation results of the traditional model and improved model were compared and analyzed. The research indicated that, comparing with common entrance lane, the capacity of right-turn lane at the entrance lane with bus lane should be reduced, and the travelling delay of bus lane and its inside adjacent lane should be increased. The degree of these effects is related to bus volume, right-turn volume and headway between buses.

Production function is the econometric model used to study the business relationship between input and output. In this paper, it uses Cobb-Douglas (C-D) production function as based model, and it uses regression analysis and Solow residual as the theoretical support. It simulates the production function model of railway transportation. Through the empirical study and quantify the railway transport enterprise production function analysis, the authors reveal factors affecting investment in the railway transport enterprise output volume. This research is helpful for future.

This study focuses on recognizing the travel modes and activity types in personal travel trajectory. Firstly the paper proposes a concept of trip-activity chain pattern to describe the general form of travel trajectory, and analyzes the structure and features of this pattern and its sub-patterns: trip sub-pattern and activity sub-pattern. Then normalized Euclidean distance measurement method is adopted to decompose the travel trajectory into trip and activity parts. Finally the authors apply RBFNN to solve the pattern recognition problem, which obtains an accuracy of 88.5% of travel mode recognition and 74.4% of activity type recognition.

With the acceleration of urbanization process, the problem of urban traffic is increasingly prominent. In particular, there is a dispute about whether to cancel the existing conventional rail transit buses after the rail transit goes into operation. This paper comes up with back propagation (BP) neural network model basing on the principle of complementarities, by analyzing the relationship between running rail and conventional public transport, and solves the problem of the adjustment of regular bus lines under the operations of both collinear.

In order to prevent social instability of rail transit construction projects effectively, 15 factors caused rail transit social risk were extracted. Using the integration of decision-making trial and evaluation laboratory (DEMATEL) and the interpretive structure model(ISM), a structural model of risk cause system was established. The causes were divided into 4 categories: root causes, controllable causes, key causes, direct causes. The results show that safeguarding the fundamental interests of the masses is the key to control the social risk of the rail transit construction.

It is important to evaluate bus system development level for public transportation system operations management. In his paper, 22 indicators are selected to establish the evaluation target system of the bus system development level. A new combined evaluation method based on structure entropy weight- matter element analysis is proposed. In this method, structure entropy method can make the weight calculation more objective, matter element analysis can ensure the integrity of the qualitative and quantitative information and easier to operate. Finally, case study of Dalian, after analyzing the particularity of bus system in Dalian, it specifically evaluates the development level of the bus system in Dalian used structure entropy weight - matter element analysis method, and gets the level is “medium”, among all of the indicators, the rating of peak hour load factor is “pass”, then it proposes some reference countermeasures to improve the development level of bus system in Dalian for the evaluation results.

The study focuses on the travel time costs of public traffic, calculates them under different conditions in order to analyze the coordination of them. It’s finished by two stages. At the first stage, using generalized travel cost share rate forecasting model to forecast the share rates of different income groups using different travel modes. At the second stage, the share rate is used to determines the travel time cost function. Selecting distance and time as characteristic variables of the function, studying the change of it. Finally, taking Guangzhou as an example to analyze the coordination of the urban rail transit. The results indicate that it’s necessary to control the length of the line coincides between the subway and bus within 4km. It improves the accuracy and practicality of the model with consideration of more factors affecting the resident travel mode choice.

In order to adapt to traffic operation situation of over-saturated signalized intersection, the setting methods of optimal cycle and green split of every phase are studied. Selecting Xinan Rd. and Wuyi Rd. intersection as study object, traffic investigation was carried out. Considering the two factors of the average delay and capacity at over- saturated intersection comprehensively, the optimization method of signal cycle length was proposed. Considering the traffic volume and queue length, setting method of the green splits of every phase was also proposed. Using the measured traffic data, signal timing scheme of the investigated intersection was not only designed, but also compared with the existing situation. The research indicates that, using this method, the average delay will be increased at over- saturated intersection, and the capacity can also be increased. This method is beneficial to reduce vehicles queuing at this kind of intersection.

This paper focuses on travel mode recognition based on Radial Basis Function (RBF) Neural Networks using the characters extracted from travel trace information collected by smartphone. First, the authors analyzed the characters of travel mode to find out what the key parameters are to divide the two kinds of travel mode by using the F-score method in order to make up the character vectors to recognize different travel modes. Eventually, a classifier of the RBF-based Neural Network can be established. This Neural Network is trained by travel mode samples extracted from travel trace data in Dalian. For comparison, BP Neural Networks are used. The result shows that the recognition accuracy rate of RBF Neural Network is better than BP Neural Network, and suggests that the RBF Neural Network has a better recognition performance.

The system, facing to passengers, aim to releasing the information of bus arrival time prediction, sends messages to mobile phone directly, saves the travel time and decreases the waiting times and also increases the efficiency. The system runs with the information of bus real-time GPS data, using the computer languages and technologies of Java EE, JSP, MySQL database and Android. The author uses FSM (finite state machine) which is part of servers to handle the bus real-time data, develops a synthetic system centralized, enterprise-level, mobile phone platform and based on requests and responses.

Rational transportation structure is very important to economic rapid development with decreased transport cost. On the basis of system analysis, an applied analytical SWOT model was used to investigate the method and theory that are in accordance with nationality, and an is constructed to address ways to improve the transportation structure in Dalian region. Establishing the index system of evaluation, the authors applied the gray correlation method of Dalian City transportation system for quantitative analysis. The analysis of the transportation structure could set up a system of transportation which could improve the economy in Dalian, and promote the transportation in Dalian.