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Usage of simulation techniques like Vehicle-in-the-Loop, Scenario-in-the-Loop, and other mixed-reality systems are becoming inevitable in autonomous vehicle development, particularly in testing and validation. These methods rely on using digital twins, realistic representations of real vehicles, and traffic in a carefully rebuilt virtual world. Recreating them precisely in a virtual ecosystem requires many parameters of real vehicles to follow their properties in a simulation. This is especially true for vehicle dynamics, where these parameters have high impact on the simulation results. The paper's objective is to provide a method that can help reverse engineering a real car's suspension characteristics with the help of a genetic algorithm. A detailed description of the method is presented, guiding the reader through the whole process, including the meta-heuristic function's settings and how it interfaces with IPG Carmaker. The paper also presents multiple measurements, which can be effortlessly recreated without expensive devices or the need to disassemble any vehicle parts. Measurements are reproduced in two separate simulation tools with special scenarios providing an efficient way to analyze and verify the results. The provided method creates vehicle suspension characteristics with adequate quality, opening up the possibility to use them in the creation of digital twins or creating virtual traffic with realistic vehicle dynamics for high-quality visualization. Results show satisfying accuracy when tested with OpenCRG.

Digital twin simulation has many applications, but one of the most important applications is in automotive industry. It helps in fleet management, cost management and most importantly increases the operational efficiency of the physical asset. The data from the previous asset’s life cycle is also important for the current asset to be efficient. There are many challenges faced by the automotive industry for which digital twinning might be a solution.

能源互联网是以电力系统为核心，利用可再生能源发电技术、信息技术，融合电力网络、天然气网络、供热/冷网络等多能源网以及电气交通网形成的能源互联共享网络。能源互联网是促进可再生能源消纳，提高能源使用效率的重要途径。因构成网络多，特性差异大，能源互联网的规划、运行和控制面临大量难题。数字孪生是融合物联网技术、通信技术、大数据分析技术和高性能计算技术的先进仿真分析技术，有助于解决当前能源互联网发展面临的技术问题。首先介绍了数字孪生的基本概念，给出了能源互联网数字孪生的构建方式与可能应用；然后以能源互联网规划为例，详述了数字孪生技术解决的关键问题；最后，介绍了基于数字孪生的能源互联网规划平台—CloudIEPS，通过能源互联网规划案例进一步证明了数字孪生技术的重要作用。

交叉路口经常发生碰撞事故，通常是因为此处有两条或多条道路相互交错。诸如左转、穿过路口、右转之类的驾驶行为都可能引发冲突，从而导致碰撞事故。具体而言，美国国家公路交通安全管理局（NHTSA）发现，左转是最主要的碰撞前会发生的危险事件，其发生概率为22.2%（基于所有碰撞事故总数）。此外，在交叉路口转弯或穿过路口时发生的碰撞事故中，大约有61%涉及到左转。

Crashes often occur at intersections because these are the locations where two or more roads cross each other. Activities such as turning left, crossing over, and turning right have the potential for conflicts resulting in crashes. Specifically, the US National Highway Traffic Safety Association (NHTSA) found that turning left is a leading critical pre-crash event and occurs in 22.2 percent of all crashes. Further, approximately 61 percent of crashes that take place while turning or rossing an intersection involve a left-hand turn.1

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