Applied Mechanics and Materials Vols. 253-255

Abstract: Traffic road network is one of the fundamental components in Intelligent Transportation System (ITS). This paper analyses the requirement for traffic road network in ITS, and constructs a lane-based road network model. The model which describes traffic network from different levels is composed of 5 kinds of elements: link, node, arc, lane and lane connector. In level-1, the basic unit of the model is link or arc, which represents the road section with the constant traffic organization. That means the number of lanes, the attributes of lane and the topological relationship between lanes in link or arc are constant. In level-2, lane and lane connector give the detail information of the network based on arcs. This model can support various research and application fields in ITS. Finally, we take the network modeling in traffic simulation as an example. The simulation traffic network in TransModeler is extracted automatically from the traffic network database that is constructed on the lane-based network model.

Abstract: When there are multiple objectives co-existent in Vehicle routing problem(VRP), it is difficult to achieve optical status simultaneously. To solve this issue, it introduces a method of improved multi-objective Genetic Algorithm (MOGA). It adopts an approach close to heuristic algorithm to cultivate partial viable chromosomes, route decoding to ensure that all individuals meet constraints and uses relatively efficient method of arena contest to construct non-dominated set. Finally programme to fulfill the multi-objective algorithm and then apply it in the standard example of VRP to verity its effectiveness by comparison with the existing optimal results.

Abstract: There will be some emergency needs which will disable the predetermined route during the vehicle scheduling, and affect the whole distribution process. The existing algorithms cannot efficiently and accurately solve these vehicle scheduling problems with the emergency needs. This article improved the C-K algorithm with the time window and the stowage constraint, studied the carriage of goods in Hebei province, and solved the emergency needs of vehicles scheduling problem, and the operation speed will be faster, the algorithm steps will be not complicated. Thus, vehicles scheduling route with burst situation will be redefined efficiently and accurately, and efficiency will be improved, resources inputs will be reduced, so that the cost will be saved, interests will be maximized. This article improved the existing logistics, and played a role in promoting the logistics capabilities and management.

Abstract: With the rapid development of the society, the transportation system has become more complicated and vulnerable. For simulating the real-time traffic condition of the whole city, a wide range of OD matrix data are needed which are hard to collect in whole based on the present conventional methods. The paper raises a feasible design of the traffic simulation platform based on the real-time mobile phone data. The popularity and development of mobile phones make the vast amounts of real-time traffic data can be collected and usable. With the help of the GIS module, dynamic OD traffic generation module and other related modules, the real-time mobile phone data will be converted to the valuable traffic data and applied to the traffic simulation platform.

Abstract: Multi-depots vehicle routing problem (MDVRP) is a kind of NP combination problem which possesses important practical value. In order to overcome PSO’s premature convergence and slow astringe, a Cloud Adaptive Particle Swarm Optimization(CAPSO) is put forward, it uses the randomicity and stable tendentiousness characteristics of cloud model, adopts different inertia weight generating methods in different groups, the searching ability of the algorithm in local and overall situation is balanced effectively. In this paper, the algorithm is used to solve MDVRP, a kind of new particles coding method is constructed and the solution algorithm is developed. The simulation results of example indicate that the algorithm has more search speed and stronger optimization ability than GA and the PSO algorithm.

Abstract: This paper investigates the automatic train braking control problem of ATC (Automatic Train Control) system under uncertain disturbances. An adaptive control algorithm is developed to ensure high precision tracking performance of the acceleration during the braking process, according to a standard reference model which has been widely used in the urban vehicles. The control parameter’s adaptive law is strictly deduced based on the Lyapunov Stability Theory. Rigorous analysis has shown that the train controlled by this method based ATO (Automatic Train Operation) system can effectively track the reference trajectory. Numerical simulation also verifies the effectiveness of this adaptive control algorithm.

Abstract: This paper offers an assessment of flight delays rating, which deals with general concept of risk and safety. With the use of linguistic terms, subjective assessments of qualitative delays rating indexes are represented with fuzzy variable. The relative weights of rating attributes are assessed using a pairwise comparison process. Based on the concept of optimality, Fuzzy simulation approach is employed to dispose of the evaluation model and compute the expected values. Finally, an empirical study about a major domestic airline is conducted to demonstrate the effectiveness of the approach.

Abstract: The base theory of micro-inertial strapdown head and attitude systems is expatiate on, and the calculating processes about the strapdown attitude matrix and the body head and attitude angle were discussed thoroughly，at the same time the method of refreshing strapdown matrix by using the quaternion was introduced emphatically. Finally, the result and its analysis about the simulation experiment are given, and the correctness and the validity are proved, some references for our researchers in this field are provided.

Abstract: The traffic flow at approaches to signalized intersections is determined by a multitude of factors. This results in randomness in the parameters that have to be estimated in order to calculate the signal change intervals. If factors influencing the distribution of these parameters can be identified, less safety margins may be feasible. In this way the approach capacity may be increased without compromising safety at the intersection. In this research, it is considered that the coordination of signals is a determining factor to set the signal change intervals. Thus, this research is an effort to study the effect of signal coordination and the arrival patterns generated from it on the driver’s behavior at the onset of yellow indication. It is hypothesized in this research that the vehicles generally require different signal change intervals in case of coordinated approaches compared to if the approaches were un-coordinated. Field surveys will be conducted in order to study the driver’s behavior under different conditions of coordination. After completing the extraction of data, analysis will be performed on various driver behavior parameters deemed essential for this study in order to establish the difference in the behavior of drivers for the two different cases of coordination and arrival patterns that were under observation. It is expected that the research results will lead to a potential to improve the signal coordination strategies and to achieve safe and efficient design for signal change intervals.

Abstract: Real-time scheduling and signal priority strategies play a critical role in improving the service quality of Bus Rapid Transit (BRT) system. The delays of public passengers and social vehicles are essential factors that should be considered for signal priority control. This paper proposes a signal priority algorithm for BRT based on intersection resource integration from the angle of intersection time and space combinatorial optimization, which combined optimize lane functional partitioning and green ratio allocation. The results of the data validation proves that the optimization model can significantly reduce the BRT vehicle delay at the intersection, while reducing the adverse effects of social vehicles.