Project

BME Automated Drive Lab

Goal: The project aims:
- to develop Scenario-in-the-Loop (SciL) simulation (mixed reality) framework for testing and proving of autonomous vehicles;
- to support and provide R&D at ZalaZone automotive proving ground.

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Project log

Tamas Tettamanti
added a research item
Vehicle dynamics models are widely used in many areas of the automotive industry. The usability of each model depends on how well it is able to mimic the behavior of the real vehicle. Each simulation model must go through a thorough investigation process first, which is called model validation. Although, vehicle dynamics simulation models and methodology for computational model validation are well established fields, to the best of the authors' knowledge a general framework for vehicle dynamics model validation is still lacking. The research aims to develop a comprehensive methodological framework for vehicle dynamics model validation. In this paper the aim is to present the high level layout of the proposed framework, introducing the main blocks and the tasks related, also addressing some critical issues regarding vehicle dynamics model validation such as validation metrics and vehicle parameter measurement and estimation. An important part of the proposed methodology is a sophisticated vehicle dynamics measurement system, which gives the opportunity to estimate a bunch of vehicle parameters during dynamic testing, which can be useful for several reasons, e.g. fine-tuning the parameters of the Pacejka Magic formula. As a case study some vehicle dynamics test based parameter estimations are shown to justify the raison d'être and investigate possible applications. INDEX TERMS Vehicle model validation, vehicle dynamics, vehicle parameter identification, methodological framework.
Henrietta Lengyel
added a research item
The emergence of new autonomous driving systems and functions - in particular, systems that base their decisions on the output of machine learning subsystems responsible for environment perception { brings a significant change in the risks to the safety and security of transportation. These kinds of Advanced Driver Assistance Systems are vulnerable to new types of malicious attacks, and their properties are often not well understood. This paper demonstrates the theoretical and practical possibility of deliberate physical adversarial attacks against deep learning perception systems in general, with a focus on safety-critical driver assistance applications such as traffic sign classification in particular. Our newly developed traffic sign stickers are different from other similar methods insofar that they require no special knowledge or precision in their creation and deployment, thus they present a realistic and severe threat to traffic safety and security. In this paper we preemptively point out the dangers and easily exploitable weaknesses that current and future systems are bound to face.
Tamas Tettamanti
added an update
BME Automated Drive Lab shares a free HD map and valuable models in different file formats for simulation software tools: IPG CarMaker, PreScan, VTD Vires, SUMO, Unity 3D and Unreal. If you or your organization wishes to use the models and the HD map of the ZalaZONE Automotive Proving Ground, check our new blogpost below for more information.
 
Henrietta Lengyel
added an update
BME Automated Drive Lab shares HD map and valuable models in different file formats for simulation software tools (IPG CarMaker, PreScan, VTD Vires, SUMO, Unity 3D, Unreal) for free.
If you or your company/organization wishes to use the models and the HD map of the ZalaZONE Automotive Proving Ground, check our new blogpost below for more information.
 
Tamas Tettamanti
added a research item
Developing a vehicle is always a long and complex task. This is especially true for autonomous cars. Tasks performed by the driver are taken over by the vehicle and must be performed with maximum reliability. Developing these systems is a difficult task, especially due to limited testing capabilities. Testing a vehicle in a closed environment is safe and controlled, but the variety of test scenarios is limited. By using mixed reality environments, one can create a diverse environment around a real test vehicle, with traffic, obstacles, and unexpected situations. The real movement of the test vehicle allows testing decision and motion planning level vehicular functions. Information from the virtual world can be considered as input to the vehicle sensor. Mixed reality or digital twin simulation environments can greatly assist the autonomous vehicle development process and also serve as a basis for validation procedures for such systems. This article introduces a mixed reality simulation environment that integrates a real test vehicle into a virtual environment, can handle other real and virtual obstacles, contains traffic simulations, and visualizes all of these.
Tamas Tettamanti
added an update
We are happy to announce that our new Website is now published! If you are also excited about self-driving vehicles, it worth to bookmark this site, because we update it with the latest news and innovations regulary!
See you there!
 
Tamas Tettamanti
added a research item
Vissim is a microscopic road traffic simulator based on the individual behavior of vehicles. The goal of the microscopic modeling approach is the accurate description of the traffic dynamics. Thus, the simulated traffic network may be analyzed in detail. The simulator uses the so-called psycho-physical driver behavior model developed originally by Wiedemann (1974). Vissim is widely used for diverse problems by traffic engineers in practice as well as by researchers for developments related to road traffic. Vissim offers a user friendly graphical interface (GUI) through of which one can design the geometry of any type of road networks and set up simulations in a simple way. However, for several problems the GUI is not satisfying. This is the case, for example, when the user aims to access and manipulate Vissim objects during the simulation dynamically. For this end, an additional interface is offered based on the COM which is a technology to enable interprocess communication between software. The Vissim-COM interface defines a hierarchical model in which the functions and parameters of the simulator originally provided by the GUI can be manipulated by programming. It can be programmed in any type of languages which is able to handle COM objects (e.g. C++, Visual Basic, Java, etc.). Through Vissim-COM the user is able to manipulate the attributes of most of the internal objects dynamically.
Ádám Nyerges
added a research item
Today's road vehicles already have several driver assistant systems and in the near future connected and highly automated vehicles will also appear in road transport. Higher automation levels rely on revolutionary technologies that cannot be tested and approved in the former way. To be able to achieve better efficiency, comfort and to guarantee future road safety new testing and validation methods are required. The complexity of the systems and the stochasticity of the potential traffic situations demand new approaches with different testing levels and approval layers. This paper will discuss the preliminary steps for a proposed new approach for connected and automated vehicle testing methodology.
Zsolt Szalay
added a research item
Technologies are already available using which road vehicles are able to operate in a completely autonomous way under certain circumstances. These technologies and current developments make it likely that within a few decades fully autonomous vehicles will spread in road traffic. This is expected to greatly increase traffic safety, provide mobility to groups currently excluded from transport, make transport more economical and reduce pollution. In parallel these, however, it can be stated that - despite the fact that in the case of conventional vehicles the driver is the most safety-critical element of the system, - autonomous vehicles will also be involved in traffic accidents, which will require the legal assessment of liability and the determination of the level of compensation. In this paper, we present how current regulations and practices can be applied to accidents affecting autonomous vehicles and we propose a methodolody for the liability distribution that was formerly developed for a mobile robots.
Tamas Tettamanti
added an update
Road models of ZalaZONE Automotive Proving Ground are available in different simulation software:
OpenDrive, IPG CarMaker, PreScan, VTD Vires, Unity 3D, SUMO!
The models are ready to use for software based testing of various AD/ADAS applications in a realistic environment.
Feel free to use under MIT license:
 
Bálint Tóth
added 2 research items
The paper presents a novel simulation concept for autonomous and highly automated road vehicles, called Scenario-in-the-Loop (SciL) testing. SciL can contribute to a more efficient development, testing and validation of driverless cars, which is a pressing question of our days. SciL based testing introduces a new approach capable to simulate and control realistic traffic scenarios around the autonomous vehicle under test realizing a Digital Twin technology for testing. For realistic traffic generation a high fidelity microscopic traffic simulator (SUMO) and for visualization the Unity 3D game engine are involved. The proposed testing methodology was proved with a real world autonomous car. As a test environment for SciL demonstration ZalaZONE Smart City Zone was used. Two different traffic scenarios (platooning and valet parking with pedestrian dummy) have been successfully tested and demonstrated.
Tamas Tettamanti
added an update
Co-simulation example for using Sumo and Unity 3D in a synchronized manner. An example code is provided via GitHub:
This demonstrates real-time communication between the microscopic traffic simulator SUMO and the 3D game engine Unity 3D with Python 3.7 based TCP/IP server.
 
Tamas Tettamanti
added 3 research items
As highly automated and autonomous vehicles (AVs) become more and more widespread, inducing the change of traffic dynamics, significant changes occur in traditional traffic control. So far, automotive testing has been done mostly in real-world or pure virtual simulation environment. However, this practice is quite obsolete as testing in real traffic conditions can be quite costly, moreover purely simulation based testing might be inadequate for specific goals. Accordingly, a hybrid concept of the Vehicle-inthe-Loop (ViL) was born recently, in accordance with the Hardware-in-the-Loop concept, i.e. in the ViL concept the vehicle is the 'hardware' within the simulation loop. Furthermore, due to the development of software capabilities, a novel approach, the Scenarioin-the-Loop (SciL) concept evolves based on the ViL approach. The paper defines the main purposes and conditions related to implementing ViL and SciL concepts from the perspective of traffic simulation and traffic control.
The era of autonomous vehicles infer new challenges in several fields. When autonomous vehicles take over the road in a large volume, consumer preferences around car-ownership will transform, traffic modeling and control will need correction, and moreover hackers will appear. These are just a few impacts which are expectable in the near future. Accordingly, the paper's aim is to enlighten trends and upcoming challenges of driverless vehicles and automated transportation system from a transportation engineering perspective.
The Research Center for Autonomous Road Vehicles (RECAR) was founded in 2015 upon the initiative of the Faculty of Transportation Engineering and Vehicle Engineering of Budapest University of Technology and Economics. The research center is supported by industrial partners and other academic partners targeting research and educational purposes. In complement to this project, the construction of a new automotive test track is also under development especially for autonomous road vehicle testing serving as automotive proving ground in Zalaegerszeg, Hungary. Accordingly, an intensive research has been started in RECAR center in the field of autonomous vehicle technology. The paper’s goal is to share the main practical and methodological experiences with the scientific audience as well as the industrial sector. Based on the initial research actions we intend to enlighten the upcoming research challenges of driverless vehicles and automated intelligent transport system. Basically, three main topics are concerned. Firstly, the main issues concerning autonomous vehicle research are summarized. Secondly, the requirements for autonomous test track design are concluded. Thirdly, the legal questions that emerge with the appearance of driverless vehicles are investigated, especially concerning liability.
Bálint Tóth
added a project reference
Tamas Tettamanti
added a research item
As autonomous and driver assistance functions become more and more complex, novel testing method-ologies are required. Introduction of highly automated and autonomous vehicles on public roads alters traffic flow dynamics. Therefore, it is not enough to test only the single vehicle itself, but it will also be required to test its interaction with the environment and other vehicles of traffic. In this context, a practical goal is to test independently of real traffic as much as possible. The Vehicle-in-the-Loop method (i.e. where the vehicle is the 'hardware') is already used for testing vehicles. In this configuration the vehicle is directly forced to do specific manoeuvres, but the sensors of the vehicle are not used and the vehicle does not have to make decisions. The concept of the Scenario-in-the-Loop introduces a testing method where the physical attributes as well as the sensors of vehicles are tested via a virtual twin. In the paper we present the main principles of the Scenario-in-the-Loop concept and outline the requirements of such a test environment from the perspective of traffic control.
Tamas Tettamanti
added an update
Tamas Tettamanti
added a project goal
The project aims:
- to develop Scenario-in-the-Loop (SciL) simulation (mixed reality) framework for testing and proving of autonomous vehicles;
- to support and provide R&D at ZalaZone automotive proving ground.