基于神经网络的铅酸蓄电池模型研究

根据某型潜艇蓄电池充放电的特点,设计了充放电装备用以进行模型试验,提出了充放电电流、蓄电池附属系统及参数测量实验的技术方案,以实验数据为基础,结合神经网络技术,建立了比较准确的蓄电池模型。     

城市商业广场地下停车场交通设计若干理念

通过调查,分析了大型商业广场地下停车场的主要特征与使用特点.结合实例,从商业广场地下停车场内外部交通组织、车库内部分区、出口引导标识和人性化交通设施设计等方面出发,论述了大型商业广场地下停车场交通设计的若干理念与具体实现形式,为城市大型商业建筑地下停车场交通设计提供了必要的理念支撑.     

基于MATLAB的高速公路计重收费基本费率确定方法

随着高速公路计重收费的实施,如何合理确定计重收费的基本费率也成为重点研究的问题。通过采集样本数据,提出基于MATLAB的三次样条插值确定计重收费基本费率的方法,并建立确定基本费率的计算模型,以供同行参考和借鉴。     

高速公路运营收入预测软件的开发

高速公路运营收入预测是高速公路企业进行财务评价的基础,根据交通量和收费标准相结合的预测方法,用V isual Basic编制的小程序实现高速公路基年和未来年运营收入的快速预测,从而结束了手工计算的估算方式,大大提高了工作效率。     

基于混合A*和可变半径RS曲线的自动泊车路径优化方法

路径规划是自动泊车系统的重要组成部分,是确保泊车运动安全、缩短行车距离、提高乘坐舒适性的关键。而当前自动泊车规划系统往往面临行驶空间狭小、障碍物多、路径搜索难度大等技术挑战,同时搜索曲线半径固定容易导致路径接点处曲率不连续,增大了路径跟随控制难度和轮胎磨损程度,这些都提升了泊车路径规划的研究难度。针对以上问题,设计可变半径的Reeds-Shepp曲线,提出基于混合A^*和该曲线的自动泊车路径规划方法,通过调整曲线半径,提升其在复杂场景下路径的搜索能力和灵活性。随后,设计基于分段贝塞尔曲线和梯度下降的路径优化方法,利用其多阶导数连续的优势优化已搜索的路径曲率,并采用梯度下降来保证路径曲率大小和对障碍的规避,解决直线与圆弧相接等位置曲率变化不连续的难题。结合路径搜索与路径优化的泊车规划方法能够切实满足复杂场景下的泊车需要。最后,基于团队自主研发的PanoSim虚拟系统与MATLAB搭建联合仿真环境,针对多种自动泊车工况测试验证提出的方法。研究结果表明：调整Reeds-Shepp曲线的搜索半径进行全局路径搜索,可获得更短和更易跟随的路径,具有良好的灵活性;基于贝塞尔曲线和梯度下降法的路径优化可有效消除曲率突变点、约束路径曲率并保证对障碍的无碰撞要求。     

石太客运专线列车开行方式改变降低电费方案

根据石太客运专线列车开行方案变化,引起牵引变压器容量需求减小情况,提出几种降低电费的方案,可供相关线路参考借鉴。     

基于智能体模拟的浮动式停车价格实施效果研究

在城市机动车保有量快速增长的背景下，制定合理的停车价格对缓解停车难问题具有重要的作用. 基于多智能体的建模方法，结合典型城市商业区停车调查数据搭建仿真环境，通过编程实现停车过程中的行为决策规则，建立浮动式停车价格下的路内停车模拟平台，并对浮动式停车价格的实施效果进行研究. 模拟结果表明，浮动式停车价格策略的实施不仅使路内停车资源的利用更为均衡，区域内车位紧张状况有所缓解，停车寻泊时间有所减少，还提高了周边道路上车辆运行速度. 本研究可以为提高停车效率、缓解区域道路交通拥堵提供一定决策建议.     

Dynamic demand estimation and microscopic traffic simulation of a university campus transportation network

Abstract

This article documents the authors' experience with the modeling, simulation, and analysis of a university transportation system, using the TRansportation ANalysis and SIMulation System (TRANSIMS). The processes of data preparation and network coding are described, followed by the algorithm developed to estimate the dynamic 24-hour demand, which includes a procedure for estimating the ‘desirability’ of the different parking lots from readily available data. The dynamic demand estimation algorithm is validated by comparing estimated and observed parking lot occupancies, where it is shown that the algorithm is capable of replicating observed results. Finally, an example is included to demonstrate how the developed model can be used in campus transportation planning. Besides serving as a first case study for using TRANSIMS to model a university campus, the study's contributions include the development of a procedure for parking lot desirability ranking and a practical procedure for estimating dynamic demand on university campuses.     

电梯用电计量原理与分摊方法

根据电梯工作原理和工作过程,通过设置与电梯工作状态相关的计量及其控制器件,对楼宇交通状况分析和做相关实验,将电梯实际用电情况用数学方法进行计算,合理地将楼宇电梯用电费分摊至电梯使用住户。     

A study on smart parking guidance algorithm

Parking problem becomes one of major issues in the city transportation management since the spatial resource of a city is limited and the parking cost is expensive. Lots of cars on the road should spend unnecessary time and consume energy during searching for parking due to limited parking space. To cope with these limitations and give more intelligent solutions to drivers in the selection of parking facility, this study proposes a smart parking guidance algorithm. The proposed algorithm supports drivers to find the most appropriate parking facility considering real-time status of parking facilities in a city. To suggest the most suitable parking facility, several factors such as driving distance to the guided parking facility, walking distance from the guided parking facility to destination, expected parking cost, and traffic congestion due to parking guidance, are considered in the proposed algorithm. To evaluate the effectiveness of the proposed algorithm, simulation tests have been carried out. The proposed algorithm helps to maximize the utilization of space resources of a city, and reduce unnecessary energy consumption and CO₂ emission of wandering cars since it is designed to control the utilization of parking facility efficiently and reduce traffic congestion due to parking space search.