A conflict–congestion model for pedestrian–vehicle mixed evacuation based on discrete particle swarm optimization algorithm

A simulation model based on temporal–spatial conflict and congestion for pedestrian–vehicle mixed evacuation has been investigated. Assuming certain spatial behaviors of individuals during emergency evacuation, a discrete particle swarm optimization with neighborhood learning factor algorithm has been proposed to solve this problem. The proposed algorithm introduces a neighborhood learning factor to simulate the sub-group phenomenon among evacuees and to accelerate the evacuation process. The approach proposed here is compared with methods from the literatures, and simulation results indicate that the proposed algorithm achieves better evacuation efficiency while maintaining lower pedestrian–vehicle conflict levels.     

Singularity-free dynamic equations of vehicle–manipulator systems

In this paper we derive the singularity-free dynamic equations of vehicle–manipulator systems using a minimal representation. These systems are normally modeled using Euler angles, which leads to singularities, or Euler parameters, which is not a minimal representation and thus not suited for Lagrange’s equations. We circumvent these issues by introducing quasi-coordinates which allows us to derive the dynamics using minimal and globally valid non-Euclidean configuration coordinates. This is a great advantage as the configuration space of the vehicle in general is non-Euclidean. We thus obtain a computationally efficient and singularity-free formulation of the dynamic equations with the same complexity as the conventional Lagrangian approach. The closed form formulation makes the proposed approach well suited for system analysis and model-based control. This paper focuses on the dynamic properties of vehicle–manipulator systems and we present the explicit matrices needed for implementation together with several mathematical relations that can be used to speed up the algorithms. We also show how to calculate the inertia and Coriolis matrices and present these for several different vehicle–manipulator systems in such a way that this can be implemented for simulation and control purposes without extensive knowledge of the mathematical background. By presenting the explicit equations needed for implementation, the approach presented becomes more accessible and should reach a wider audience, including engineers and programmers.     

Modeling pedestrians’ interest in locations: A concept to improve simulations of pedestrian destination choice

Large environments that are designed for travel, leisure, and for everyday life – such as transport hubs, amusement parks, and shopping centers – feature different locations that are frequently visited by pedestrians. Each visit is evoked by one’s motivation to engage in some kind of activity at a certain location. By means of modeling the pedestrians’ interests in locations with the aid of computer simulations, it is possible to forecast the occupancy at locations by utilizing sophisticated pedestrian destination choice models. In the field of pedestrian dynamics research, location preference modeling is not common, but it is all the more rare to include a psychological grounding into such choice models. Here we show that our psychologically inspired and mathematically defined model to describe pedestrians’ interests in locations is able to improve the exactness of pedestrian destination choice models. The interest function model is based on the psychological concept of goal-related memory accessibility and on fundamental coherences found in pedestrian-related data that is measurable at locations. We validated the interest function model and our results provide evidence that our approach improves the simulation fidelity regarding occupancy forecasting. Because the interest concept is designed as a framework that can be coupled to existing microscopic pedestrian simulators, it can be used in most pedestrian destination choice models to describe pedestrian visiting preferences. Consequently, the reliability of the occupancy predictions of pedestrian simulations can be enhanced by integrating the interest function model into choices models.     

Atomistic Modeling of pure Mg and Mg–Al systems

Interatomic potentials for pure Mg and the Mg–Al binary system have been developed based on the modified embedded-atom method (MEAM) potential formalism. The potentials can describe various fundamental physical properties of pure Mg (bulk, point defect, planar defect and thermal properties) and alloy behaviors (thermodynamic, structural and elastic properties) in reasonable agreement with experimental data or higher-level calculations. The applicability of the potential to atomistic investigations on the deformation behavior of pure Mg and the effect of alloying element Al on it is discussed.     

An algorithm to study non-stationary random vibrations of vehicle–bridge systems

An efficient algorithm is proposed for non-stationary random vibration of vehicle–bridge systems. The pseudo excitation method (PEM) is extended to handle the random analysis of time-dependent vehicle–bridge systems, for which the statistical characteristics of dynamic responses are computed. A vehicle–bridge interaction element is adopted to reduce the computational effort. In the numerical examples, the proposed method is justified by comparing with Monte Carlo simulation results. Also, a method to estimate maximum responses is suggested. Examples include a train moving across both simply supported and three-span continuous bridges and some observed phenomena are discussed.     

Studies on improving vehicle handling and lane keeping performance of closed-loop driver–vehicle system with integrated chassis control

This study proposes a new integrated robust model matching chassis controller to improve vehicle handling performance and lane keep ability. The design framework of the H_∞ controller is based on linear matrix inequalities (LMIs), which integrates active rear wheel steering control, longitudinal force compensation and active yaw moment control. To comprehensively evaluate the performance of the integrated chassis control system, a closed-loop driver–vehicle system is used. The effectiveness of the integrated controller on handling performance improvement is tested by a vehicle without driver model under a crosswind disturbance. At the same time, both the handling and lane keeping improving performance of the closed-loop driver–vehicle system is evaluated by tracking an S shape winding road. The simulation results reveal that the integrated chassis controller not only achieves preferable handling performance and stability, but also improves the vehicle lane keep ability significantly, and can alleviate the working load of the driver.     

2D–3D-based on-board pedestrian detection system

During the next decade, on-board pedestrian detection systems will play a key role in the challenge of increasing traffic safety. The main target of these systems, to detect pedestrians in urban scenarios, implies overcoming difficulties like processing outdoor scenes from a mobile platform and searching for aspect-changing objects in cluttered environments. This makes such systems combine techniques in the state-of-the-art Computer Vision. In this paper we present a three module system based on both 2D and 3D cues. The first module uses 3D information to estimate the road plane parameters and thus select a coherent set of regions of interest (ROIs) to be further analyzed. The second module uses Real AdaBoost and a combined set of Haar wavelets and edge orientation histograms to classify the incoming ROIs as pedestrian or non-pedestrian. The final module loops again with the 3D cue in order to verify the classified ROIs and with the 2D in order to refine the final results. According to the results, the integration of the proposed techniques gives rise to a promising system.     

Transmission of nanoscale information-based neural communication-aware ligand–receptor interactions

Neural Computing and Applications - In this paper, we develop an analytical framework for modeling the transmission of nanoscale information in nanonetwork-based molecular communication and aware...     

Modeling of the molar volume of the solution phases in the Al–Cu–Mg system

The temperature and pressure dependences of molar volume of the solution phases in the Al–Cu–Mg system have been modeled by using the CALPHAD approach. Molar volumes of pure elements were critical assessed according to the experimental data from the literature. Subsequently, volumetric properties of the Al–Cu, Al–Mg and Cu–Mg binary systems were assessed and compared with the corresponding experimental data. The results are compatible with the assessed data.     

Sensitivity analysis and optimization of vehicle–bridge systems based on combined PEM–PIM strategy

This paper presents a new optimization method for coupled vehicle–bridge systems subjected to uneven road surface excitation. The vehicle system is simplified as a multiple rigid-body model and the single-span bridge is modeled as a simply supported Bernoulli–Euler beam. The pseudo-excitation method transforms the random surface roughness into the superposition of a series of deterministic pseudo-harmonic excitations, which enables convenient and accurate computation of first and second order sensitivity information. The precise integration method is used to compute the vertical random vibrations for both the vehicle and the bridge. The sensitivities are used to find the optimal solution, with vehicle ride comfort taken as the objective function. Optimization efficiency and computational accuracy are demonstrated numerically.     

Single–camera vehicle speed measurement using the geometry of the imaging system

Multimedia Tools and Applications - In recent years, measuring the speed of vehicles by a single camera has been done using several methods including the road geometric information, the difference...     

Modeling of the viscosity in the AL–Cu–Mg–Si system: Database construction

The viscosity database for the Al–Cu–Mg–Si system was constructed using the CALPHAD (CALculation of PHAse Diagram)-type formalism. Viscosities of pure elements were described with the Arrhenius formula based on the experimental data. Subsequently, viscosities of the Al–Cu, Al–Si, Al–Mg and Cu–Si binary systems were assessed via CALPHAD technique and compared with the corresponding experimental data. Due to the lack of experimental data, viscosities in the Mg–Si and Cu–Mg systems were estimated by means of the Hirai's equation. The viscosities of the ternary Al–Cu–Si system were then predicted based on the binary parameters and compared with the experimental results. Using the established viscosity database for the quaternary Al–Cu–Mg–Si system, the viscosities of some commercial aluminum alloys were predicted. The reasonable agreement between calculations and experiments in Al-rich corner indicates that the CALPHAD-type database for the viscosity is valid and the database is suitable for predicting the viscosity of the commercial Al–Cu–Mg–Si based alloys.     

Modeling of Ni–Cr–Mo based alloys: Part II — Kinetics

The CALPHAD approach is applied to kinetic studies of phase transformations and to aging of prototypes of Ni–Cr–Mo-based alloys selected for waste disposal canisters in the Yucca Mountain Project (YMP). Based on a previous study on alloy stability for several candidate alloys, the thermodynamic driving forces, together with a newly developed mobility database, have been used to analyze diffusion-controlled transformations in these Ni-based alloys. Results on precipitation of the Ni₂Cr-ordered phase in Ni–Cr and Ni–Cr–Mo alloys, and of the complex P and σ$\sigma$ phases in a surrogate of Alloy 22 are presented, and the output from the modeling are compared with experimental data on aging.     

The Issues of Information Modeling

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User Modeling in Human–Computer Interaction

A fundamental objective of human–computer interaction research is to make systems more usable, more useful, and to provide users with experiences fitting their specific background knowledge and objectives. The challenge in an information-rich world is not only to make information available to people at any time, at any place, and in any form, but specifically to say the right thing at the right time in the right way. Designers of collaborative human–computer systems face the formidable task of writing software for millions of users (at design time) while making it work as if it were designed for each individual user (only known at use time). User modeling research has attempted to address these issues. In this article, I will first review the objectives, progress, and unfulfilled hopes that have occurred over the last ten years, and illustrate them with some interesting computational environments and their underlying conceptual frameworks. A special emphasis is given to high-functionality applications and the impact of user modeling to make them more usable, useful, and learnable. Finally, an assessment of the current state of the art followed by some future challenges is given.     

Modeling Multileader–Follower Noncooperative Stackelberg Games

This paper presents a Stackelberg–Nash game for modeling multiple leaders and followers. The model involves two Nash games restricted by a Stackelberg game. We propose a computational approach to find the equilibrium point based on the extraproximal method for ergodic controlled finite Markov chains. The extraproximal method consists of a two-step iterated procedure: the first step is a prediction and the second is a basic adjustment of the previous step. We formulate the game as coupled nonlinear programming problems using the Lagrange principle. The Tikhonov’s regularization method is used to guarantee the convergence to a unique equilibrium point. Validity of the method is demonstrated applying this framework to model an oligopoly competition.     

Adaptive rollover prevention controller for driver–vehicle systems

In the paper, we propose an adaptive rollover prevention controller for heavy vehicles. At first, a design method for an ideal vehicle model is proposed. The designed ideal vehicle model has the property that good rollover prevention performance can be assured even if the driver steering characteristics vary. If the behavior of the actual heavy vehicle tracks that of the designed ideal vehicle model, rollover prevention can be achieved. Therefore, next, to realize good rollover prevention, we propose an adaptive steering controller. In the heavy vehicle system using the controller, the actual heavy vehicle can track the ideal vehicle model. Then, rollover prevention can be achieved. Finally, to demonstrate the usefulness of the proposed controller, numerical simulations are carried out.