Joint ego-motion and road geometry estimation

We provide a sensor fusion framework for solving the problem of joint ego-motion and road geometry estimation. More specifically we employ a sensor fusion framework to make systematic use of the measurements from a forward looking radar and camera, steering wheel angle sensor, wheel speed sensors and inertial sensors to compute good estimates of the road geometry and the motion of the ego vehicle on this road. In order to solve this problem we derive dynamical models for the ego vehicle, the road and the leading vehicles. The main difference to existing approaches is that we make use of a new dynamic model for the road. An extended Kalman filter is used to fuse data and to filter measurements from the camera in order to improve the road geometry estimate. The proposed solution has been tested and compared to existing algorithms for this problem, using measurements from authentic traffic environments on public roads in Sweden. The results clearly indicate that the proposed method provides better estimates.     

道路交通网络中的关键节点识别方法研究

在现实世界中，大量复杂系统都可以通过抽象的节点和连边构成的网络来加以刻画。作为城市交通系统的重要组成部分，道路交通网络是一个典型的复杂系统，与人们的生活密切相关。道路交通网络中的关键节点识别问题是复杂网络领域研究中的一个经典难题。传统的度中心性算法和PageRank算法在复杂网络的关键节点的识别中具有较好的应用，考虑到道路交通网络中关键节点的特殊性和彼此关联性，在度中心性算法的基础上引入贪心算法的思想，提出了一个基于贪心策略的度中心性关键节点识别方法；同时，在PageRank算法的基础上引入贪心算法的思想，提出了一种基于贪心策略的PageRank关键节点识别方法，从而使道路交通网络中关键节点识别的结果更合理，在交通道路维护保养、规划设计，以及犯罪分子潜逃阻断等领域都有重要的应用价值。通过公开数据集与经典的关键节点识别方法做比较，验证了算法的有效性。     

Arc routing in a node routing environment

We describe a special variant of the vehicle routing problem (VRP), where there are many customers per road segment. This class of VRPs arises in, e.g. mail delivery, and is a borderline case where both arc routing and node routing techniques may be applied for modeling and solving. In a real-world setting, the problem should be modeled so as to incorporate all important constraining factors. We use a simplified node routing model and aggregate customers into supernodes to reduce problem size. A tabu search metaheuristic for the standard node routing-based VRP is then applied to the aggregated version of the problem. Our method is tested both on test instances from the literature as well as on a portfolio of new test instances especially made to fit the problem at hand. Experimental results are reported, showing that aggregation of customers can lead to substantial improvements both in solution time and solution quality in this setting, especially for larger instances.     

Branch-and-Bound Methods for Euclidean Registration Problems

In this paper, we propose a practical and efficient method for finding the globally optimal solution to the problem of determining the pose of an object. We present a framework that allows us to use point-to-point, point-to-line, and point-to-plane correspondences for solving various types of pose and registration problems involving euclidean (or similarity) transformations. Traditional methods such as the iterative closest point algorithm or bundle adjustment methods for camera pose may get trapped in local minima due to the nonconvexity of the corresponding optimization problem. Our approach of solving the mathematical optimization problems guarantees global optimality. The optimization scheme is based on ideas from global optimization theory, in particular convex underestimators in combination with branch-and-bound methods. We provide a provably optimal algorithm and demonstrate good performance on both synthetic and real data. We also give examples of where traditional methods fail due to the local minima problem.     

Optimally solving Markov decision processes with total expected discounted reward function: Linear programming revisited

We compare the computational performance of linear programming (LP) and the policy iteration algorithm (PIA) for solving discrete-time infinite-horizon Markov decision process (MDP) models with total expected discounted reward. We use randomly generated test problems as well as a real-life health-care problem to empirically show that, unlike previously reported, barrier methods for LP provide a viable tool for optimally solving such MDPs. The dimensions of comparison include transition probability matrix structure, state and action size, and the LP solution method.     

Modelling and Solving Employee Timetabling Problems

Employee timetabling is the operation of assigning employees to tasks in a set of shifts during a fixed period of time, typically a week. We present a general definition of employee timetabling problems (ETPs) that captures many real-world problem formulations and includes complex constraints. The proposed model of ETPs can be represented in a tabular form that is both intuitive and efficient for constraint representation and processing. The constraint networks of ETPs include non-binary constraints and are difficult to formulate in terms of simple constraint solvers. We investigate the use of local search techniques for solving ETPs. In particular, we propose several versions of hill-climbing that make use of a novel search space that includes also partial assignments. We show that, on large and difficult instances of real world ETPs, where systematic search fails, local search methods perform well and solve the hardest instances. According to our experimental results on various techniques, a simple version of hill climbing based on random moves is the best method for solving large ETP instances.     

Fully Computable a Posteriori Error Bounds for Hybridizable Discontinuous Galerkin Finite Element Approximations

We introduce an entirely new class of high-order methods for computational fluid dynamics based on the Gaussian process (GP) family of stochastic functions. Our approach is to use kernel-based GP prediction methods to interpolate/reconstruct high-order approximations for solving hyperbolic PDEs. We present a new high-order formulation to solve (magneto)hydrodynamic equations using the GP approach that furnishes an alternative to conventional polynomial-based approaches.     

Iterative methods for solving extended general mixed variational inequalities

In this paper, we introduce and consider a new class of mixed variational inequalities involving four operators, which are called extended general mixed variational inequalities. Using the resolvent operator technique, we establish the equivalence between the extended general mixed variational inequalities and fixed point problems as well as resolvent equations. We use this alternative equivalent formulation to suggest and analyze some iterative methods for solving general mixed variational inequalities. We study the convergence criteria for the suggested iterative methods under suitable conditions. Our methods of proof are very simple as compared with other techniques. The results proved in this paper may be viewed as refinements and important generalizations of the previous known results.     

Route‐Aware Edge Bundling for Visualizing Origin‐Destination Trails in Urban Traffic

Origin‐destination (OD) trails describe movements across space. Typical visualizations thereof use either straight lines or plot the actual trajectories. To reduce clutter inherent to visualizing large OD datasets, bundling methods can be used. Yet, bundling OD trails in urban traffic data remains challenging. Two specific reasons hereof are the constraints implied by the underlying road network and the difficulty of finding good bundling settings. To cope with these issues, we propose a new approach called Route Aware Edge Bundling (RAEB). To handle road constraints, we first generate a hierarchical model of the road‐and‐trajectory data. Next, we derive optimal bundling parameters, including kernel size and number of iterations, for a user‐selected level of detail of this model, thereby allowing users to explicitly trade off simplification vs accuracy. We demonstrate the added value of RAEB compared to state‐of‐the‐art trail bundling methods on both synthetic and real‐world traffic data for tasks that include the preservation of road network topology and the support of multiscale exploration.     

Parallel particle filter for tracking road centrelines from high-resolution SAR images using detected road junctions as initial seed points

Acquiring road junction information is helpful for improving the quality of road network extraction. This article presents a new road network extraction method with three stages. First, road junction candidates are extracted by our previously proposed valley-finding algorithm. Second, numerous particle filters running in parallel track road centrelines starting from all of the detected junction candidates. Finally, the road centrelines are approximated by fitting the tracked centrepoints. The main contribution of this article lies in two aspects. First, road centrepoint tracking routes are launched simultaneously by considering the detected road junctions as starting points, which helps overcome the interference of various obstacles. Second, parallel tracking is implemented by a graphics processing unit (GPU) running accelerated particle filters, which significantly improves the execution time of the road network extraction task. The experimental results show that our proposed method not only handles various obstacles that occur on the roads capably, but also, on average, is 10.5 times as fast as previous methods. We compared the proposed method with two other existing methods in the literature using two different synthetic aperture radar (SAR) images to validate the superior performance of our proposed method.     

面向对象有限元并行计算框架PANDA求解器的服务构件化设计与集成

针对很多结构有限元程序需要使用数值方法进行系统方程组求解的共性特点,提出对数值求解部分进行构件化设计,形成求解器服务,用于面向对象有限元并行计算框架PANDA为不同应用类型的有限元程序开发提供数值算法.将美国Livermore国家实验室开发的数值求解器库HYPRE作为数值求解构件集成到PANDA框架中,利用其提供的数值...     

Automatic Guided Vehicles: Robust Controller Design in Image Space

We have been interested in Automatic Guided Vehicles (AGV) for several years. In this paper, we synthesize controllers for AGV applications using monocular vision. In particular, we are interested in road following and direction change tasks, and in analyzing the influence of extrinsic camera parameter perturbations on vehicle behavior. We use the bicycle as the kinematic vehicle model, and we choose the position of the white band on the road as the sensor signal. We define an interaction between the camera, which is mounted inside the vehicle, and the white band detected in the image space. Using this kind of interaction, we present how to use a pole assignment technique to solve the servoing task. We show the simulation and experimental results (1/10 scale demonstrator) with and without perturbations. We then investigate the use of a robust controller to slow down the effect of perturbations on the behavior of the vehicle.     

Continuous range-based skyline queries in road networks

With the ever-growing popularity of smartphone devices in recent years, skyline queries over spatial Web objects in road networks have received increasing attention. In the literature, various techniques have been developed to tackle skyline queries that take both spatial and non-spatial attributes into consideration. However, the existing solutions only focus on solving point-based queries, where the query location is a spatial point. We observe that in many real-life applications, the user location is often represented by a spatial range. Thus, in this paper, we study a new problem of range-based skyline queries (CRSQs) in road networks. Two efficient algorithms named landmark-based (LBA) and index-based (IBA) algorithms are proposed. We also present incremental versions of LBA and IBA to handle continuous range-based skyline queries over moving objects. Extensive experiments using real road network datasets demonstrate the effectiveness and efficiency of our proposed algorithms.     

A comparative study of partitioning methods for crowd simulations

The simulation of large crowds of autonomous agents with realistic behavior is still a challenge for several computer research communities. In order to handle large crowds, some scalable architectures have been proposed. Nevertheless, the effective use of distributed systems requires the use of partitioning methods that can properly distribute the workload generated by agents among the existing distributed resources.In this paper, we analyze the use of irregular shape regions (convex hulls) for solving the partitioning problem. We have compared a partitioning method based on convex hulls with two techniques that use rectangular regions. The performance evaluation results show that the convex hull method outperforms the rest of the considered methods in terms of both fitness function values and execution times, regardless of the movement pattern followed by the agents. These results show that the shape of the regions in the partition can improve the performance of the partitioning method, rather than the heuristic method used.     

Accelerated iterative methods for finding solutions of nonlinear equations and their dynamical behavior

In this paper, we present a family of optimal, in the sense of Kung–Traub’s conjecture, iterative methods for solving nonlinear equations with eighth-order convergence. Our methods are based on Chun’s fourth-order method. We use the Ostrowski’s efficiency index and several numerical tests in order to compare the new methods with other known eighth-order ones. We also extend this comparison to the dynamical study of the different methods.     

基于道路网络的对象聚类

大多数的空间聚类算法主要针对欧几何空间中的数据对象.然而在大多真实的应用中,空间对象的访问主要受限于空间网络(如道路网络),因此,对道路网络中的对象进行聚类分析更具有现实意义.道路网络中对象之间的距离度量需要通过基于网络的最短路径距离来重新定义,其计算代价高,这使得已有的基于欧几何距离的聚类算法不能直接运用到这种环境中.因此,通过开发道路网络的特征提出了两种新的聚类算法.算法使用网络中的边和结点信息来缩减搜索空间,避免了一些不必要的距离计算.实验结果表明,算法对于真实道路网络中的对象聚类是高效的.     

Problem solving learning environments and assessment: A knowledge space theory approach

This paper explores the relation between problem solving learning environments (PSLEs) and assessment concepts. The general framework of evidence-centered assessment design is used to describe PSLEs in terms of assessment concepts, and to identify similarities between the process of assessment design and of PSLE design. We use a recently developed PSLE, the ProNIFA system, to illustrate the concepts of student model, evidence model, and task model, concepts that provide for a close link between problem solving teaching software and assessment concepts. We also introduce ProNIFA because it uses a mathematical method developed in psychometric test theory—Competency-based Knowledge Space Theory (CbKST)—for building a student model based on observations on students' problem solving performance. The experiences made with methods such as CbKST lead us to the conclusion that the time has come to more frequently integrate assessment components into PSLEs, and to use problem solving and simulation environments as part of assessment environments. This will contribute to making assessment more authentic and less obtrusive, and making PSLEs more relevant in formal educational settings.     

An efficient path computation model for hierarchically structured topographical road maps

In this paper, we have developed a HiTi (Hierarchical MulTi) graph model for structuring large topographical road maps to speed up the minimum cost route computation. The HiTi graph model provides a novel approach to abstracting and structuring a topographical road map in a hierarchical fashion. We propose a new shortest path algorithm named SPAH, which utilizes HiTi graph model of a topographical road map for its computation. We give the proof for the optimality of SPAH. Our performance analysis of SPAH on grid graphs showed that it significantly reduces the search space over existing methods. We also present an in-depth experimental analysis of HiTi graph method by comparing it with other similar works on grid graphs. Within the HiTi graph framework, we also propose a parallel shortest path algorithm named ISPAH. Experimental results show that inter query shortest path problem provides more opportunity for scalable parallelism than the intra query shortest path problem.     

A New Weighting Approach Based on Rough Set Theory and Granular Computing for Road Safety Indicator Analysis

The steadily increasing volume of road traffic has resulted in many safety problems. Road safety performance indicators may contribute to better understand current safety conditions and monitor the effect of policy interventions. A composite road safety performance indicator is desired to reduce the dimensions of selected risk factors. The essential step for constructing such a composite indicator is to assign a suitable weight to each indicator. However, no agreement on weighting and aggregation in the composite indicator literature has been reached so far. Granular computing is an emerging computing paradigm of information processing that makes use of granules in problem solving. Rough set theory is considered as one of the leading special cases of granular computing approaches. In this article, a new weighting approach based on rough set theory and granular computing is introduced for road safety indicator analysis. The proposed method is applied to a real case study of 21 European countries of which only the class information (not the real values) on all indicators is used to calculate the weights. Experimental evaluation shows that it is an efficient approach to combine individual road safety performance indicators into a composite one.     

Calculating road input data for vehicle simulation

Multibody system simulation is an important tool in the development process in vehicle engineering. Without much effort, different vehicle variants and designs can be simulated, analyzed, and optimized. This is of particular relevance in an early stage of development, when no physical prototypes are available yet. In order to simulate the vehicle models under realistic conditions, suitable input data is needed for the simulation. We present an approach to derive a virtual road profile based on a tire-surrogate model, measured spindle forces, and a multibody system model of the measurement vehicle. In contrast to the measured spindle forces, the road profile together with the tire-surrogate model can be used to simulate other vehicle variants, for which no measurements are available. The road profile is derived by solving an inverse control problem. We formulate this inverse problem in the context of system simulation and provide a short mathematical analysis. Additionally, we discuss a solution approach, the method of control-constraints, which is also applied in a numerical simulation study to compute a virtual road profile.