A comparison of various algorithms to extract Magic Formula tyre model coefficients for vehicle dynamics simulations

Tyre models are a prerequisite for any vehicle dynamics simulation. Tyre models range from the simplest mathematical models that consider only the cornering stiffness to a complex set of formulae. Among all the steady-state tyre models that are in use today, the Magic Formula tyre model is unique and most popular. Though the Magic Formula tyre model is widely used, obtaining the model coefficients from either the experimental or the simulation data is not straightforward due to its nonlinear nature and the presence of a large number of coefficients. A common procedure used for this extraction is the least-squares minimisation that requires considerable experience for initial guesses. Various researchers have tried different algorithms, namely, gradient and Newton-based methods, differential evolution, artificial neural networks, etc. The issues involved in all these algorithms are setting bounds or constraints, sensitivity of the parameters, the features of the input data such as the number of points, noisy data, experimental procedure used such as slip angle sweep or tyre measurement (TIME) procedure, etc. The extracted Magic Formula coefficients are affected by these variants. This paper highlights the issues that are commonly encountered in obtaining these coefficients with different algorithms, namely, least-squares minimisation using trust region algorithms, Nelder–Mead simplex, pattern search, differential evolution, particle swarm optimisation, cuckoo search, etc. A key observation is that not all the algorithms give the same Magic Formula coefficients for a given data. The nature of the input data and the type of the algorithm decide the set of the Magic Formula tyre model coefficients.     

On the performance of rheological shock absorber models in full vehicle simulation

A comparative study of the performance of three rheological automotive shock absorber models as well as of an extended force–velocity relation in full vehicle simulation is performed. Simulation results for both the shock absorber test rig and a full vehicle crossing a single obstacle are compared with measured data. While the gain of accuracy by the extended force–velocity relation is marginal, the rheological models in general yield a noticeable improvement, which, however, in full vehicle simulation is less significant than in test rig simulation. Among the rheological models studied here, the one consisting of a nonlinear spring–dashpot element with an element modelling friction by a continuous transition from the compression to the extension range in parallel and a quadratic approximation of the static gas force exhibits the best global performance.     

Locating fixed roadside units in a bus transport network for maximum communications probability

A key issue in solving the difficult bus-bunching problem is being able to have reliable information about the location of the buses in the network. Most advanced public transport systems have buses with GPS devices, but the problem remains of how to send reliable information from the buses to the control unit, particularly when the density of buses is low, but there are high communications reliability requirements. As a solution, we study locating roadside units (RSUs) along the route. The buses, together with the RSUs, form a linear vehicular ad-hoc network (VANET). The RSUs are deployed so to maximize the probability of a vehicle communicating with an RSU in at most two hops. Previous studies on RSU location never took into account two hops, a conceptually different type of network. Rather, they consider that a vehicle is able to communicate only directly to an RSU (one hop), which is a well-known Maximum Covering Problem, in which one of the parties is always immobile, similar to a mobile phone network. Oppositely, our method solves the problem in which two of the intervening parties are mobile and communicate with each other, not possible to solve as a Maximum Covering Problem. We estimate the probability of a vehicle accessing successfully an RSU either directly or through the relay of another vehicle. This probability is later embedded in an integer programming formulation that optimizes the RSU locations for maximum communications likelihood.Numerical examples show that the connection probability is strongly dependent on the coverage ratio of the transmitters and receivers and relatively independent on the vehicle density on the network, when densities are low. Results also show that it is possible to find some cost-efficient solutions which result in a smaller number of RSUs located while assuring a connection probability of 0.9 or higher.     

Minimizing lifetime structural costs: Optimizing for production and maintenance under service life uncertainty

Current naval shipowners are being forced to extend the service lives of their aging vessels from budgetary and political constraints. This is causing them to incur significant costs due to maintaining the structure of these older ships to keep the ships in operation. These increasing costs make it desirable to design new naval structures with their minimization in mind, as well as ensuring that such vessels are robust to changes in expected service life with respect to their total lifetime cost. However, such structures will necessarily have higher production costs, therefore, an optimization framework is presented to estimate both production and maintenance costs for a naval vessel's internal structure and develop trade-spaces between these two competing objectives in order to find designs that represent a balance of both.     

Exploring the feasibility of classification trees versus ordinal discrete choice models for analyzing crash severity

A cross-median crash (CMC) is one of the most severe types of crashes in which a vehicle crosses the median and sometimes collides with opposing traffic. A study of severity of CMCs in the state of Wisconsin was conducted by Lu et al. in 2010. Discrete choice models, namely ordinal logit and probit models were used to analyze factors related to the severity of CMCs. Separate models were developed for single and multi-vehicle CMCs. Although 25 different crash, roadway, and geometric variables were used, only 3 variables were found to be statistically significant which were alcohol usage, posted speed, and road conditions. The objective of this research was to explore the feasibility of GUIDE Classification Tree method to analyze the severity of CMCs to discover if any additional information could be revealed.A dataset of CMCs in the state of Wisconsin between 2001 and 2007, used in the study by Lu et al. was used to develop three different GUIDE Classification Trees. Additionally, the effects of variable types (continuous or discrete), misclassification costs, and tree pruning characteristics on models results were also explored. The results were directly compared with discrete choice models developed in the study by Lu et al. showing that the GUIDE Classification Trees revealed new variables (median width and traffic volume) that affect CMC severity and provided useful insight on the data. The results of this research suggest that the use of Classification Tree analysis should at least be considered in conjunction with regression-based crash models to better understand factors affecting crashes. Classification Tree models were able to reveal additional information about the dependent variable and offer advantages with respect to multicollinearity and variable redundancy issues.     

Visibility mapping in New York's coastal zone: A case study of alternative methods

Abstract

Most scenery evaluation methodologies incorporate visibility extent. In New York's coastal zone, visibility mapping for planning and project studies is complicated by low topographic relief, and diverse configurations of water edge and upland surface character. A generalized visibility model has been developed, including macrolandscape, observer, and sight‐line recording. Based on a prior shorescape study of New York's coast, the Lake Ontario Port Bay site was selected to test alternative visibility methods. Within the study site, four “landscape control points”; were chosen which provided extensive views of representative land and water forms, and surface types. For each control point, four families of visibility mapping approaches were applied: primary (field observation); secondary (topographic maps and vertical air photo analysis); tertiary (physical topographic model); and quaternary (digital terrain computer model). Major study conclusions are: the methods require different resources; all methods readily produced visibility maps; all methods, except secondary, could be used to produce perspective scenes for subsequent content evaluation; all methods except primary omitted one or more elements of the general visibility model; all methods should incorporate field work due to critical viewer environment conditions; sensitivity analysis in each method produced ambiguous zones; each view map was different, particularly in the background. An integrated, multi‐approach strategy would appear desirable for most planning and project applications.     

Using survival models to estimate bus travel times and associated uncertainties

Transit agencies often provide travelers with point estimates of bus travel times to downstream stops to improve the perceived reliability of bus transit systems. Prediction models that can estimate both point estimates and the level of uncertainty associated with these estimates (e.g., travel time variance) might help to further improve reliability by tempering user expectations. In this paper, accelerated failure time survival models are proposed to provide such simultaneous predictions. Data from a headway-based bus route serving the Pennsylvania State University-University Park campus were used to estimate bus travel times using the proposed survival model and traditional linear regression frameworks for comparison. Overall, the accuracy of point estimates from the two approaches, measured using the root-mean-squared errors (RMSEs) and mean absolute errors (MAEs), was similar. This suggests that both methods predict travel times equally well. However, the survival models were found to more accurately describe the uncertainty associated with the predictions. Furthermore, survival model estimates were found to have smaller uncertainties on average, especially when predicted travel times were small. Tests for transferability over time suggested that the models did not over-fit the dataset and validated the predictive ability of models established with historical data. Overall, the survival model approach appears to be a promising method to predict both expected bus travel times and the uncertainty associated with these travel times.     

基于HCSR的热点应力插值方法研究

针对《散货船、油船协调共同规范》（HCSR）中的疲劳热点应力插值方法,总结7种不同的插值方式,通过对简化的实体单元和壳体单元模型的分析以及实船模型新旧规范的对比,验证了HCSR中插值方法的合理性,并对两个版本的HCSR方法进行比较.     

新型轨检小车整体车架结构设计与分析

基于传统T型轨检小车车架存在着装配繁琐、稳定性不足、刚度差的缺点,设计一种新的Y型车架结构,该车架的主体结构采用一体成型技术,整体重心降低45mm,提高装配效率与使用寿命的同时使轨检小车在推行过程中稳定性更好。通过对新Y型车架横梁连接螺栓的强度校核,验证其螺栓连接的可靠性,并根据新Y型与传统T型车架的ANSYS Workbench有限元分析结果得出,新Y型车架刚度显著提高。     

High-resolution numerical relaxation approximations to second-order macroscopic traffic flow models

A novel numerical approach for the approximation of several, widely applied, macroscopic traffic flow models is presented. A relaxation-type approximation of second-order non-equilibrium models, written in conservation or balance law form, is considered. Using the relaxation approximation, the nonlinear equations are transformed to a semi-linear diagonilizable problem with linear characteristic variables and stiff source terms. To discretize the resulting relaxation system, low- and high-resolution reconstructions in space and implicit–explicit Runge–Kutta time integration schemes are considered. The family of spatial discretizations includes a second-order MUSCL scheme and a fifth-order WENO scheme, and a detailed formulation of the scheme is presented. Emphasis is given on the WENO scheme and its performance for solving the different traffic models. To demonstrate the effectiveness of the proposed approach, extensive numerical tests are performed for the different models. The computations reported here demonstrate the simplicity and versatility of relaxation schemes as solvers for macroscopic traffic flow models.