公路线形设计中缓和曲线选用的探讨

本主要介绍缓和曲线在公路平面线形设计中的应用及计算方法，缓和曲线的应用增加了路线设计的自由度，使线形更优美流畅。     

公路平面线形交互设计系统的研究

模拟纸上定线，提出了在图形屏幕上直接构造（设计）路线平面线形的连接、插入、延伸等方法，改进了传统的先给出参数后在计算机屏幕上才有线位的方法。同时建立了基于线元的动态调整线形线拉的交互设计计算模型，提出了对所交互线元约束的处理方法，解决了基于一般计算模型较难处理复杂平面线形组合的交互设计问题。     

山区公路平面线形曲线型设计方法综述

指出曲线型设计方法能够增进道路线形本身的美观,增强线形与环境方面的协调性,同时有利于交通事故的减少,介绍了山区公路平面线形曲线型设计方法与传统直线型设计方法的不同,对十种不同曲线型设计方法的适用条件和特点进行了分析,从而提高山区公路平面选线质量。     

山区高速公路线形设计

结合京承高速公路（苇子峪-京冀界段）工程的线形设计,从线形设计方法、平面线形设计、纵面线形设计、平纵线形组合设计和线形与环境的协调五个方面,就如何改进山区高速公路线形设计进行了分析研究,以期指导实践。     

互通式立交匝道线形安全设计研究

互通式立交匝道线形设计是互通式立交总体设计、总体布局的关键,对减少交通事故的发生有很大的影响。互通式立交匝道线形设计中的平面线形、纵断面线形、变速车道线形、视距等对车辆是否能够安全驶出和驶入公路的影响尤为重要,优化互通式立交匝道线形设计是提高互通式立交的安全性及行车舒适性的基本保障。     

改扩建道路工程线型拟合设计

对高等级道路的改扩建工程平面拟合设计之“综合法”和不对称竖曲线的设计作了简要探讨,并举例说明公路改建工程平面线形拟合设计计算结果。     

刍议公路几何设计中的相关问题

公路线形是道路的骨架,也是命脉,因此线形几何设计是公路最为关键的组成部分,其不仅是包含平面线形、纵断面线形和横断面的三维立体线形设计,也是包含行车速度或时间在内的四维线形设计。此文从与道路几何线形设计相关的汽车运动学、行驶时间阀值和驾驶员心理学等问题进行了深入的分析研究,并对回旋线参数取值和S型曲线超高值计算问题进行了剖析,为公路设计者提供参考。     

道路线形优化设计分析

道路是一种长条状的带状三维结构物。其立体线形的确定依据是平面线形的设计、纵断面线形设计以及横断面的布置。比较这三种设计工作，最难的是平面线形的设计，其次是纵断面线形的设计。平面线形的确定要同时满足适应城市地理位置，工程量最小，行车稳定，平顺，舒适，线形连续协调并要满足视觉和乘员心理的安全感。     

短线法施工桥梁安装线形和制造线形计算

介绍了短线匹配法预制梁施工方法及特点,论述了短线法施工桥梁安装线形与制造线形的区别及相关计算方法.通过对厦门集美大桥的计算表明:结构的安装线形与制造线形相差较大,选择合适计算方法对桥梁的安装线形和制造线形计算是保证桥梁在施工过程中达到设计线形的关键之一.     

基于舒适安全因素的道路线形设计探讨

道路线形设计是否合理是决定驾驶员及乘客能否快速、舒适和安全行驶的最主要的原因。本文围绕舒适和安全这两个决定性因素,研究分析道路平面线形、纵断面线形以及平纵组合线形的影响并提出相应的建议;并采用横向加速度和横向加速度变化率等指标评价道路线形,采用可能速度等指标、新型缓和曲线等线形对道路设计进行优化。     

Mountain railway alignment optimization integrating layouts of large-scale auxiliary construction projects

Mountain railway alignment design is an important but complex civil engineering problem. To overcome the drastically undulating terrain, long tunnels and high bridges are major structures used along a mountain railway, which poses great challenges for railway design and construction. Unfortunately, despite being studied for many years, the crucial construction factors of complex structures have received slight attention in alignment optimization. In this paper, for the first time, the layout of large-scale auxiliary construction projects (LACPs), including tunnel shafts and access roads, is incorporated into the alignment design process in order to consider construction practicability and economy. Primarily, an alignment–LACPs concurrent optimization model is built. After defining the comprehensive design variables, the alignment–LACPs total construction cost is formulated as the objective function. Besides, the separate constraints for designing the alignment and LACPs are considered. Also, a construction duration computation is proposed for constraining the alignment–LACPs integration. To solve the model, a four-step hybrid solution method is developed. Specifically, the alignment is first generated with a particle swarm optimization (PSO). Afterward, a new divide and conquer approach is devised to search for shaft alternatives along the alignment. Then, a customized Dijkstra algorithm is developed to search for complex access roads. Finally, a novel polynomial mechanism for time-varying acceleration coefficients (TVAC) is designed for PSO to evolve the alignment–LACPs solutions. The above model and methods have been applied to two complex actual mountain railway examples. Their effectiveness is demonstrated through detailed analysis of resulting railway solutions and control experiments with contemporary TVAC-based methods.     

A Customized Particle Swarm Method to Solve Highway Alignment Optimization Problem

Abstract: Optimizing highway alignment requires a versatile set of cost functions and an efficient search method to achieve the best design. Because of numerous highway design considerations, this issue is classified as a constrained problem. Moreover, because of the infinite number of possible solutions for the problem and the continuous search space, highway alignment optimization is a complex problem. In this study, a customized particle swarm optimization algorithm was used to search for a near‐optimal highway alignment, which is a compound of several tangents, consisting of circular (for horizontal design) and parabolic (for vertical alignment) curves. The selected highway alignment should meet the constraints of highway design while minimizing total cost as the objective function. The model uses geographical information system (GIS) maps as an efficient and fast way to calculate right‐of‐way costs, earthwork costs, and any other spatial information and constraints that should be implemented in the design process. The efficiency of the algorithm was verified through a case study using an artificial map as the study region. Finally, we applied the algorithm to a real‐world example and the results were compared with the alignment found by traditional methods.     

A sequential exploration algorithm for the design optimization of horizontal road alignment

Most computer-aided optimization procedures for horizontal alignment optimization of roads require the use of information such as horizontal points of intersection (PIs) to determine an alignment. In these methods, to obtain parameters such as the radius of the curve corresponding to a specific PI, the previous and next PIs must be known. In this paper, a sequential exploration algorithm (SEA) is proposed, and the algorithm continuously explores the entire optimization space through certain steps. Only the parameters of the previous node are required to determine the current node's parameters during the exploration process, avoiding the tight coupling between PIs in traditional optimization algorithms. Furthermore, the proposed SEA does not require assumptions about the positions and numbers of the PIs, and it can design near-optimal road alignments that match geometric restrictions and automatically take transition curves into account. Another feature of the proposed algorithm is that it directly optimizes the geometric element parameters based on the actual milepost, and it is a fully collaborative optimization approach that does not require secondary optimization nesting during the optimization process. Analyses comparing the optimization effects of different algorithms are performed on a numerical case, that is, a problem of avoiding obstacles, and two actual cases from the literature, that is, a new road design problem and an existing road reconstruction problem. It is discovered that the proposed SEA results in an approximately 3% to 10% improvement in optimization effects when compared to two current cutting-edge optimization algorithms. This work offers a new perspective on road alignment optimization by merging discrete and continuous optimizations, with a discrete component handling optimization accuracy and a continuous component handling real optimization.     

Mountain railway alignment optimization based on landform recognition and presetting of dominating structures

Mountain railway alignment optimization has always been a challenge for designers and researchers in this field. It is extremely difficult for existing methods that optimize alignments before major structures to generate a better alignment than the best one provided by human designers when the terrain is drastically undulating between the start and endpoints. To fill this gap, a “structures before alignments” design process is proposed in this paper. Primarily, a landform recognition method is devised for recognizing dominating landforms. Then, a bi-level alignment optimization model is proposed, with the upper level dedicated to characterizing dominating structures and the lower level focusing on optimizing the entire alignments. To solve this bi-level model, a three-stage optimization method is designed. At the first stage, a scanning process and screening operators are devised for generating all the possible locations of dominating structures. At the second stage, a hierarchical multi-criteria decision-making procedure is applied for selecting the optimized dominating structure layouts. At the third stage, alignments are optimized based on the determined structure layouts using a bi-objective optimization method, which minimizes construction cost and geo-hazard risk simultaneously. The proposed model and solution method are applied to two real-world cases whose results verify their capabilities in producing alignment alternatives with better combinations of construction cost and geo-hazard risk than manually designed alternatives.     

Vertical alignment optimization of mountain railways with terrain-driven greedy algorithm improved by Monte Carlo tree search

Vertical alignment design is an important process for railway construction which fundamentally affects the infrastructure investment cost. Determining an optimized vertical alignment is a challenging task since the objective function is non-linear, non-differentiable, and quite unsmooth. Great efforts have been invested in solving the vertical alignment optimization problem and many methods have been proposed. However, for vertical alignment designs in complex mountainous regions, the terrain conditions impose great difficulties and, hence, many bridges and tunnels are generally required. Thus, reasonably locating bridges and tunnels along the entire alignment (EA) is a major concern that deserves further investigations. To solve this problem, this study develops a terrain-driven greedy algorithm improved by Monte Carlo tree search (T-GRA-MCTS). A terrain-driven method is proposed to determine the number and longitudinal distribution of vertical points of intersection (VPIs). In order to trade off the local section of an alignment versus the EA when optimizing each VPI along the alignment to locate bridges and tunnels reasonably, an MCTS is employed and integrated with a GRA. The basic MCTS is modified for vertical alignment optimization with a novel equation for computing the upper confidence bounds for trees and a customized termination criterion is provided. A real-world railway case is used to demonstrate the effectiveness of the proposed method. The results show that the T-GRA-MCTS performs better than a greedy search method without MCTS or a widely used nature-inspired algorithm (i.e., a particle swarm optimization). Moreover, it can find a less expensive solution than the one designed by experienced human engineers.     

A deep reinforcement learning approach to mountain railway alignment optimization

The design and planning of railway alignments is the dominant task in railway construction. However, it is difficult to achieve self-learning and learning from human experience with manual as well as automated design methods. Also, many existing approaches require predefined numbers of horizontal points of intersection or vertical points of intersection as input. To address these issues, this study employs deep reinforcement learning (DRL) to optimize mountainous railway alignments with the goal of minimizing construction costs. First, in the DRL model, the state of the railway alignment optimization environment is determined, and the action and reward function of the optimization agent are defined along with the corresponding alignment constraints. Second, we integrate a recent DRL algorithm called the deep deterministic policy gradient with optional human experience to obtain the final optimized railway alignment, and the influence of human experience is demonstrated through a sensitivity analysis. Finally, this methodology is applied to a real-world case study in a mountainous region, and the results verify that the DRL approach used here can automatically explore and optimize the railway alignment, decreasing the construction cost by 17.65% and 7.98%, compared with the manual alignment and with the results of a method based on the distance transform, respectively, while satisfying various alignment constraints.     

Intersection Modeling for Highway Alignment Optimization

Abstract:   When optimizing a highway alignment, it is desirable to consider new and modified intersections along it. This article develops methods for locally optimizing intersections within highway alignment optimization processes. Design and operational characteristics for intersections are reviewed from the literature. The formulation considers the major costs that are sensitive to intersection characteristics. Genetic algorithms are used for optimal search. The proposed methods are implemented on an artificial study area and on a real one through the use of geographic information systems. The results show how the methods work for local optimization of intersections as well as for optimizing entire alignments. These methods can be used for improving search flexibility, thus allowing more effective intersections. They also provide a basis for extending the alignment optimization from single highways to networks .     

基于ADAMS的前轮外倾及前束优化分析

分析了前轮外倾和前束两者的关系及两者对车轮磨损的影响,通过建立的前悬架模型仿真了原有的车轮定位参数在实际运动中的变化,对模型车的前轮定位参数进行了优化设计,给出了一种更方便和直接的确定前轮定位参数最优值的方法。     

定线成果数据库的建立

描述了定线成果数据库的设计思想,详细阐述了纸质数据库和电子数据库的实施方法,并对定线成果数据库的更新和维护措施进行了研究,实现了定线成果资料标准化、数字化、自动化的信息管理。     

Spiral Spline Curves for Highway Design

Techniques for automating the design of highways are examined. It is accepted design practice to reduce the straight-line parts of the horizontal alignment of a designed center line as much as possible. This can be accomplished manually by using clothoid templates. This article describes the use of spiral splines that behave in a manner such that the horizontal alignment may be automatically designed as a composition of clothoid segments. The resulting methods are suitable for microcomputer implementation.