Research Objectives

Focus of the research project 

The research objective is to investigate new concepts of EPWT subsystems, primarily involving high-speed rotary machines. These rotary machines may serve as electric motors for propulsion units, electric compressors for fuel cells, cooling systems for electric battery vehicles, or transmission systems for electric vehicles. The scope also includes research into power-density enhancement in electric propulsion units, along with an assessment of the associated impacts. The investigation will focus on the energy efficiency and acoustic emissions of high-speed rotary machines, the flow behavior of operating fluids in gearboxes with consideration of vehicle motion, and concepts for oil-free rotor bearings. The aim is to achieve significant improvements in simulations of coupled thermal-mechanical-fluid-electromagnetic problems as well as in the experimental verification capabilities for these problems. The results will enable enhancements in the technical, technological, and economic characteristics of future EPWT systems.

Research objectives 

• Concept of oil-free bearing for high-speed rotating machines as a subsystem of a power unit with potential application in fuel cells: The aim is to develop new concepts of radial-axial rotor bearings for rotating machines, in which the operating fluid in the lubrication subsystems is not based on lubricating oils. These oil-free concepts will enable the application of such rotating machines in high-performance power units with extremely stringent requirements for the purity of working media. The oil-free bearing concept must ensure guaranteed radial and axial load capacities for very heavy rotors operating under transient conditions, extremely low mechanical losses of the rotating machine, and must naturally suppress undesirable vibrations and the associated noise of the entire subsystem.

• Advanced ability to predict the dynamic behavior of high-speed machines: The research goal is to develop an advanced ability to predict the behavior of high-speed rotating machines, taking into account simultaneously occurring multiphysical phenomena. This ability will enable sensitivity studies, feasibility studies, and ultimately reliable optimization without the costs of manufacturing and testing many considered variants. Interactions between individual subsystem components through fluid and electromagnetic effects are anticipated. This advanced capability must subsequently enable the development of future EPWTs with reduced weight and acoustic emissions by tens of percent compared to the current state.

• Ability to predict oil flow in transmission systems of moving vehicles: The goal is to develope an experimentally verified methodology that will enable the simulation and subsequent evaluation of multiphase operating fluid flow in time and space varying domains corresponding to the internal spaces of transmission mechanisms and will take into account the dynamics of the vehicle during driving maneuvers. Predicting oil flow will enable the design of a new transmission concept with reduced oil volume and high oil fill stability under dynamic operating conditions in the vehicle.

Research activities 

• A1.1 Research on oil-free bearing concepts for rotors of high-speed rotating machines: The activity includes the design and validation of new rotor bearing concepts and the investigation of computational descriptions of operating fluid flow in lubrication and sealing systems, with a focus on specific transient conditions in the subsystems of electric power units. The work is expected to involve analytical tasks, numerical flow simulations, development of specialized numerical models, design of optimization strategy methods, shape and property optimization of lubrication and sealing systems, and analyses of the influence of bearings on energy losses and acoustic emissions of rotating subsystems. Oil-free bearing systems will be designed taking into account future specific applications in fuel cells. The research teams of ÚADI-RS and PBST will participate in the activity.

• A1.2 Research of the behavior of high-speed rotating machines with oil-free rotor bearings under operating conditions: The activity consists of testing oil-free bearing concepts for rotating machines under operating conditions close to real operating conditions. Activities include the development of a specific testing concept, analysis of component interactions through rotor bearings, testing of new bearing concepts, and analysis of experimentally obtained results. The ÚADI-RS research team and the PBSTT team will participate in the activity.

• A1.3 Research on the behavior of high-speed electrical machines with consideration multiphysical phenomena: This activity involves the creation of analytical and numerical computational models that effectively describe mechanical, thermal, fluid, and electromagnetic phenomena and their mutual interactions during the operation of high-speed rotating machines. Theoretical studies, computational numerical analyses, the development of proprietary numerical models, and experimental verification at industrial partners are anticipated. The activities will take into account the specific conditions associated with electric drive units in EPWT for use in motor vehicles. The research teams of ÚADI-RS, ÚAEE, and Garrett will participate in the activity. 

• A1.4 Development and validation of methods for fluid–structure interaction analysis in gear systems: This activity involves numerical simulations of multiphase fluid flow and its interaction with moving components. New methods for solving fluid flow, such as Lagrangean meshless methods of the SPH (smoothed particle hydrodynamics) type, will be analyzed and developed. Numerical simulations will be verified experimentally using optical methods and methods of subsequent analysis after sampling operating fluids. The methodology will enable the determination of the quantity and specification of the oil filling required for a given transmission across operating conditions. The research teams of ÚADI-RS, SVS FEM, and WIKOV will participate in the activity. 

• A1.5 Research on interactions between moving components and fluids in gear systems considering vehicle dynamics: The activity involves the use of SPH numerical simulations to model the influence of vehicle dynamics on the motion of the oil charge within a gearbox. The work will involve theoretical studies, numerical computational analyses, design and production of a functional test bench prototype and its software control to account for vehicle dynamics, and experimental validation in cooperation with industrial partners. The activities will consider specific conditions of gearboxes in EPWTs during vehicle driving maneuvers (acceleration, deceleration, and cornering). The research teams of ÚADI-RS, SVS FEM, and WIKOV will participate in the activity.

Research activity milestones 

• M1.1 Verified computational model of an air bearing for supporting the rotor of a high-speed rotating machine.

• M1.2 Validated Capability to Simulate the Dynamics of a High-Speed Machine with Oil-Free Bearings under Operating Conditions

• M1.3 New Concept of Rotor Support for an Electric Compressor Using Oil-Free Bearings.

• M1.4 Validated Capability to Simulate the Dynamics of an Electric Power Unit with Consideration of Multiphysical Interactions.

• M1.5 Validated Capability to Simulate the Coupled Multiphysical Behavior of an Electric Power Unit.

• M1.6 Validated Capability to Simulate Fluid–Structure Interactions in a Gearbox under Real Operating Conditions, Accounting for the Effects of Complex Internal Geometry.

• M1.7. Validated Methodology for Analyzing Interactions between Key Components and Fluids in Gear Systems.

• M1.8 Capability for Experimental Characterization of Oil Behavior in a Gearbox under Real Operating Conditions Considering Vehicle Driving Maneuvers.

• M1.9 Validated Methodology for Describing Oil Behavior in a Gearbox under Real Operating Conditions, Simulating Automotive Driving Maneuvers such as Acceleration, Deceleration, and Cornering.

Research outcomes 

The outcomes of the research activities will be new capabilities applicable to the development of subsystems for future EPWTs. Research results such as patents (G), software (SW), and functional prototypes (G) will enable to describe, analyse, and validate the research objectives. The research outcomes will be openly disseminated through publications in peer-reviewed scientific journals (Jimp) and presentations at international conferences (D), ensuring a broad impact on the development of low-emission mobility. The planned outcomes include:

• Patent defining a new type of axial-radial rotor mounting.

• Software for analyzing force loads of rotors in high-speed rotating machines. 

• Software for controlling test procedures on a test rig using data from a virtual environment that reflects the physical model of a car.

• Functional Prototype of a Test Rig for Testing Rotating Machines.

• Functional prototype of a test rig for investigating oil behavior in a gearbox under operating conditions corresponding to vehicle driving maneuvers.

• Article in an impacted journal focused on rotor bearing systems of high-speed machines.

• Two articles in impacted journals focused on the multiphysical description of rotating machines.

• Article in an impacted journal focused on the interaction between moving gearbox components and fluids.

• Article in an impacted journal focused on oil flow in a gearbox during vehicle motion.

• Conference proceedings articles presenting research activities and significant results achieved within the project.

Research focus 

The research objective includes several research aims and activities. Due to the nature and scope of the investigated issues, computer simulations will be used as the primary research tool. The simulation models will be developed by the project team. Input data for the models will be obtained primarily from literature sources, including available statistical data. The scenarios under investigation will take into account constraints arising from the geographical location of the Czech Republic (landlocked country with limited potential for increasing electricity production from hydropower). The first research activity (A1) focuses on the impact (benefit) of renewable energy sources on reducing greenhouse gas emissions in road transport. Attention will be primarily given to energy used for vehicle propulsion, but energy demands associated with the development of the necessary energy infrastructure will also be considered. Currently, the use of electricity from RES for powering BEVs is well established, and pilot operations have verified the feasibility of producing hydrogen using RES. In the short term, electrical energy can be stored in battery storage systems, but long-term (seasonal) electricity storage has not yet been resolved. For long-term storage, various energy carriers may be considered. However, with each energy conversion, the overall efficiency of the energy chain decreases. The issue of converting renewable energy into different energy carriers will be addressed in the second research activity (A2). Following the energy conversion topic, activity A3 will focus on sizing energy storage for clean mobility, addressing the required storage capacity with regard to different energy carriers and the possibilities of their storage and transportation. Since BEVs are currently the most widespread vehicles that do not produce greenhouse gas emissions during operation, the storage of electrical energy will be addressed in a separate research activity (A4), which will be investigated in a greater detail.

Research objectives 

• Analyze the potential use of renewable energy sources in road transport.

• Determine the contribution of renewable energy sources to reduce greenhouse gas emissions in road transport in the Czech Republic.

• Develop software for assessing the impact of renewable energy sources to reduce greenhouse gas emissions in road transport in the Czech Republic.

• Assess various energy carriers in terms of their suitability (safety, transport, storability) to use in road transport in the Czech Republic.

• Determine well-to-wheel conversion efficiencies from renewable energy production to the use of energy carriers in vehicles.

• Develop a methodological procedure for assessing the efficiency of the renewable energy-based supply chain in road transport.

• Analyze the demand for various energy carriers produced from renewable sources in road transport in the Czech Republic.

• Analyze the need for energy storage systems for different carriers in road transport in the Czech Republic.

• Develop a methodological procedure for sizing battery storage systems for road transport under conditions in the Czech Republic.

• Analyze the need for battery storage systems in road transport in the Czech Republic.

• Develop a procedure for sizing battery storage systems for road transport under conditions in Czech Republic.

• Develop software for sizing battery storage systems.

Research activies

A2.1 Impact of renewable energy sources on reducing greenhouse gas emissions in road transport: Within this research activity, attention will be focused on the possibilities and methods of using renewable energy sources (RES) in road transport. The main objective will be to determine the contribution of RES to reduce greenhouse gas emissions in road transport. The goal of the research activity is to develop a supporting simulation tool for analysis and decision-making related to the implementation of RES in road transport. The outcome of the research activity will be software for analyzing the impact of RES (and derived energy carriers) on the reduction of greenhouse gas emissions from road transport.

A2.2 Conversion of renewable energy into various energy carriers: Research activity A2.2 is closely related to research activity A2.1. The conversion of one form of energy into another (e.g., conversion of electrical energy into other energy carriers) leads to a reduction in the efficiency of the entire energy chain. The conversion of electricity generated from renewable energy sources into other energy carriers will be necessary in the field of clean mobility, as electrical energy cannot be economically stored for long periods (on the order of months). For long-term storage purposes, other energy carriers will therefore be required. The objective of this research activity is to analyze the conversion of renewable energy into other energy carriers under the conditions of the Czech Republic. The outcome of the activity will be a methodology for assessing the efficiency of the energy chain in clean mobility using various energy carriers.

A2.3 Dimensioning of energy storage facilities for clean mobility: The efficient use of renewable energy sources depends on the ability to store energy. In the future, primary energy from renewable sources is expected to be predominantly in the form of electrical energy, which cannot be directly stored for long periods. Other energy carriers will therefore be required for long-term energy storage. These energy carriers (such as hydrogen, methane, ammonia, etc.) can subsequently be used directly to power vehicles in road transport. The objective of this research activity is to develop a methodology for sizing storage systems for the above-mentioned energy carriers, taking into account the requirements for their use in road transport.

A2.4 Battery energy storage in road transport: The research activity is mainly focused on the storage of electrical energy for road transport. Battery electric vehicles (BEVs) currently represent the largest share of zero tailpipe greenhouse gas emission vehicles in the EU (and also in the Czech Republic). In 2022, BEVs accounted for 1.19% of the passenger car fleet in the EU, while the share of fuel-cell vehicles (hydrogen-powered) was negligible (fewer than 10,000 fuel-cell vehicles were in operation across the entire EU in 2022). Based on current trends, it is highly likely that BEVs will constitute the majority of zero-emission vehicles over at least the next ten years. For this reason, the development of energy infrastructure for BEVs currently has the greatest practical importance. Within research activity A4, attention will be focused on battery energy storage infrastructure, which will be necessary to address the short-term variability of power output from renewable energy sources.

Milstones

• M2.1 Methodology for assessing the impact of renewable energy sources on reducing greenhouse gas emissions in road transport

• M2.2 Computational model of the impact of renewable energy sources on reducing greenhouse gas emissions in road transport

• M2.3 Procedure for evaluating the overall conversion efficiency of energy from renewable sources into various energy carriers

• M2.4 Methodology for dimensioning energy storage facilities for clean mobility

• M2.5 Procedure for dimensioning battery storage systems for road transport

• M2.6 Computational model for dimensioning battery storage systems

Research outcomes 

• Conference paper on the use of renewable energy sources in road transport

• Software for assessing the impact of renewable energy sources on greenhouse gas emissions in road transport in the Czech Republic.

• A journal article on the potential of renewable energy sources to reduce greenhouse gas emissions from road transport in the Czech Republic, published in a scientific journal classified as Q1 according to its impact factor.

• A conference paper on the evaluation of conversion efficiency in the renewable energy chain in the Czech Republic.

• An article on the evaluation of the conversion efficiency of energy from renewable energy sources into various energy carriers under the conditions of the Czech Republic, published in a Q1-ranked scientific journal according to its impact factor.

• Methodological procedure for evaluating the overall conversion efficiency of energy from renewable energy sources into various energy carriers.

• Conference contribution on energy carrier storage for road transport under the conditions in the Czech Republic. 

• Article on the dimensioning of storage systems for various energy carriers under the conditions in the Czech Republic, published in a scientific journal classified as Q1 according to its impact factor.

• Methodology for sizing energy storage systems for clean mobility. 

• Conference paper on battery storage systems in road transport under the conditions in the Czech Republic

• Article on the dimensioning of battery storage systems for road transport under the conditions in the Czech Republic, published in a scientific journal classified as Q1 according to its impact factor.

• Software for planning battery energy storage infrastructure. 

Research objectives 

• • Vehicle range optimization through intelligent cooling and energy management using self-learning mechanisms.

  • Analyze the possibilities of V2X communication in higher frequency bands, up to the millimeter wave range, enabling ultra-low latency and high data throughput.

  • Research in the field of electric vehicle safety, together with the incorporation of a gradual increase in the degree of autonomy, using advanced technologies such as deep learning and virtual reality. The key points describing the objective are:

  • Based on currently used design and safety features, determine the limit states for which this design can be applied.

  • Validate the computational model based on both partial crash tests and available whole vehicle crash tests, with a focus on occupant safety.

  • Extend the applicability of computational models under the currently applied boundary conditions, including validation through technical experiments.

  • Create interior concepts with extended crew movement in the vehicle, taking into account the likelihood of integration into series production (a relaxed position is expected within a few years – starting point, followed by partial seat rotation up to complete rotation).

  • Create a virtual environment to research different interior concepts and determine the necessary tests, which will differ due to the new interior design.

  • Create a tool for conducting extensive numerical simulation studies based on simulations from the virtual world and a validated computational model. The tool will use deep learning to perform simulations that are critical for the given concept.

  • Create a knowledge database for individual interior concepts that can be used to identify physical (critical) tests.

Research activities 

• A3.1. Energy Flow Management in Electric Vehicles:  Create a sophisticated system for monitoring and managing energy flows in an electric vehicle using advanced deep learning algorithms. The system will be able to adapt to various factors, such as current operating conditions, battery state, or surrounding traffic situations, and will be able to optimize energy usage to achieve maximum efficiency and vehicle range.

• A3.2. Methodology for identifying critical conditions with regard to vehicle interior design: Based on currently used design and safety features, determine the limit states for which this construction can be applied. Validate the computational model based on both partial crash tests and available full-vehicle crash test data, with a focus on occupant safety. Extend the applicability of the computational models to the currently applied boundary conditions, including verification through technical experiments.

• A3.3. Research into safety features of autonomous vehicle interior designs: Create possible interior concepts with extended occupant movement in the vehicle, taking into account the expected timeline for integration into series production (a relaxed seating position is anticipated within a few years – starting point, followed by partial seat rotation up to full rotation). Create a virtual environment to study different interior concepts and determine the necessary tests, which will differ due to the new interior design. Create a tool for conducting extensive numerical simulation studies based on simulations from the virtual environment and the validated computational model. The tool will utilize deep learning to perform simulations that are critical for the given concept.

• A3.4. Data handling methodology: Create a knowledge database for individual interior concepts to support the identification of (critical) physical tests.

Milestones of research activities 

• M3.1 Conceptual design, system specification for data collection and processing

• M3.2 Data collection from the experimental vehicle completed

• M3.3 Modification of measuring faculities according to the updated measurement scenario

• M3.4 Completion of propagation characteristics analysis, simulation of model creation

• M3.5 Conference Presentation of Measurement Results 

• M3.6 Completion of computational model development

• M3.7 Completion of the virtual environment for model operation 

• M3.8 Control system with AI, including experimental verification

• M3.9 Articles in scientific journals 

• M3.10 Functional prototype 

• M3.11 Conference publication 

• M3.12 Publication – journal article 

• M3.13 Software completed 

• M3.14 Conference publication 

• M3.15 Article in a Q1 scientific journal 

• M3.16 Creation of methodology for working with data from numerical simulations and experiments, creation of data

• M3.17 Conference publication 

• M3.18 Article in a Q1 scientific journal 

Research outcomes 

The research activities will result in the ability to measure and evaluate large amounts of data from the energy system of electric vehicles, including thermal management and passive safety of electric cars. The results will include software (2xSW), a functional prototype (G), and an uncertified methodology (O). The results will be openly presented in journal publications (Jimp), including research data, and at international conferences. It is also expected that deep learning training data packages will be published and made openly available. The planned results include:

• Software of the AI-based control system 

• Functional prototype of an AI-based thermal management system for an electric vehicle

• Software for evaluating safety in the interior of autonomous vehicles

• Methodology for working with data in vehicle safety testing

• Publications at international conferences and in Q1 journals 

Research objectives 

The research objective of WP4 is the comprehensive research of non-exhaust particles emitted by electric vehicles during driving, including the study of the characteristics of these particles, their production, the modelling of their dispersion into the surrounding environment, and the assessment of population exposure in the vicinity of road transport infrastructure. The activities within WP4 are divided into three research tasks.

Research activities 

• A4.1 Laboratory identification and characterization of particles from automobile brakes: Under laboratory conditions, attention will be focused on particles emitted from automotive brakes, which are currently receiving significant public attention (EURO 7). Extensive experimental research will be focused on collecting particles released from brakes, followed by their categorization and analysis. For this purpose, our own experimental apparatus with a commercial brake system will be designed and constructed. At the same time, laboratory abrasive sampling of particles from the surfaces of brake component materials will be carried out. The results of the experiments will lead to new insights into the characteristics of the emitted particles (shape, size, concentration, composition) and into the influence of individual parameters on these characteristics (braking intensity, ambient temperature, brake temperature, materials used, etc.). The acquired knowledge will be used for the development of a predictive computational model of brake particle emissions from electric vehicles under various driving conditions, with detailed consideration of the current vehicle speed and instantaneous acceleration (both acceleration and braking). This model will subsequently be used within activity A4.3.

• A4.2 Airborne particles and indirect identification of particles from cars: The activities are focused on a comprehensive assessment of particles from ambient air sampling under real-world conditions, and on subsequent procedures for inverse identification of particle sources and their emission intensity in relation to traffic flow. Data from long-term monitoring of ambient particle concentrations will be used, and through the application of statistical analysis and machine learning methods, the characteristics of particle resuspension in the studied locations will be identified. Additionally, ambient particle sampling will be conducted near traffic streams, with the particles analyzed in terms of composition and size distribution. Based on elemental composition, potential particle sources will be assessed, and by linking with the computational models developed under A4.3, the intensity of potential particle sources will be quantified inversely. Particle sampling will be carried out primarily in locations used for the development of computational models in A4.3. Sampling will take place at different times of the day and during different seasons of the year, enabling a robust evaluation of vehicle-emitted particles under typical meteorological conditions and year-round road maintenance practices.

• A4.3 Computational modeling of particle dispersion and population exposure: The activities include the development of computational models for particle dispersion around cars, with particular attention to accurately incorporating the effects of car movement and the generation of the associated turbulent wake of moving cars. Computational tools based on the finite volume method (CFD) will be used for the simulations. Representative areas will be selected for processing into computational models, and for given meteorological and traffic conditions, the airflow velocity fields around vehicles and roadways will be solved. Based on the calculated airflow fields, particle dispersion from vehicles into the surrounding environment will be simulated. Using information on vehicle dynamics in real traffic infrastructure elements, the particle emission models developed under A4.1 will be applied for subsequent computational identification of ambient particle loads near roadways. Extending the study to include models of human movement near traffic corridors will enable a comprehensive assessment of potential population exposure to non-exhaust particles. The stepwise approach will provide new insights and a holistic view of the generation and dispersion of non-exhaust particles emitted by traffic flows, as well as the potential exposure of residents near selected traffic infrastructure elements.

Milestones of research activities 

• M4.1 Construction of an experimental apparatus for the collection of particles from automotive brakes. 

• M4.2 Characterization of the morphology of particles from automotive brakes. 

• M4.3 Identification of the size distribution of particles emitted from automotive brakes.  

• M4.4 Development of a non-exhaust particle emission model accounting for instantaneous vehicle behavior.

• M4.5. Identification of particle resuspension characteristics from ambient monitoring data. 

• M4.6 Characterization of ambient particulate matter collected in the vicinity of road traffic. 

• M 4.7 Inverse identification of potential sources of ambient particles in relation to road traffic.

• M4.8 Development of a model that takes into account the real dynamic behavior of cars.

• M4.9 Computational identification of particle dispersion from traffic flows into the surrounding environment in representative areas.

• M4.10 Validation of the created model in a specific urban area. 

• M4.11 Development of a model of human exposure to traffic-emitted particles.

Research outcomes 

• A functional prototype of a device for collecting particles from vehicle brakes.

• Model of particle production from vehicle brakes.

• Experimental identification and characterization of particles generated by traffic flow.

• Model of particle dispersion from traffic flow.

• Model of human exposure to traffic-emitted particles in urban areas.

 Research focus 

The research plan focuses on the research and development of algorithms for Lidar point cloud registration, with scene reconstruction during vehicle motion being one of the key tasks. Registration can be based on distance minimization, on methods using statistical evaluation of the surroundings, or on techniques that identify important features within point clouds (so-called feature-based methods). These features can then be aligned, for example, using the RANSAC algorithm. Feature-detection-based methods serve as inputs for further registration techniques and can also be utilized in SLAM algorithms. The latest approach for autonomous driving relies on environmental maps that contain precise descriptions of the trajectory together with information from various sensors. These maps currently serve as the basis for navigation and testing of autonomous transport units.

Cameras on autonomous vehicles are important sensors used for visual perception of the surroundings. Their main purpose is to capture image data, which can be used for the detection, classification, and tracking of objects in the vicinity of autonomous vehicles. Cameras are a key element for detecting and classifying a wide range of objects, such as vehicles, pedestrians, cyclists, traffic signs, traffic lights, and other obstacles. The information obtained enables vehicles to respond dynamically to surrounding objects and adapt their driving behavior to the current situation.

An important function of cameras is also the tracking of moving objects in the vicinity of the autonomous vehicle. This tracking capability is essential for predicting the future motion of objects and ensures safe interaction between the vehicle and its environment. Cameras can also be used for vehicle localization in the environment: by recognizing images of buildings, signs, and terrain, autonomous vehicles are able to determine their position on a digital map. This localization capability is crucial for proper vehicles navigation and for ensuring safe and reliable operation.

Research objectives 

• Algorithms for processing and utilizing information from vehicle sensors: Design of new algorithms for multi-sensor data registration (LiDAR, radar, and cameras) and scene reconstruction during vehicle motion. The outputs are in the form of 3D points ,so-called point clouds or 2D image matrices. These data can then be further analyzed and processed in various ways.

• A vehicle route planning system that allows users to specify their vehicle type, including its dimensions, weight, and other specific parameters: The system will subsequently evaluate routes that are suitable for a given type of vehicle, minimize the risk of obstacles, and enable smooth driving. As part of the development, it is also possible to integrate the proposed solution with available data sources such as GPS, meteorological information, and others, to include current information, for example on road conditions, traffic, or weather. The system should be able to respond dynamically to these events and propose alternative routes.

Research activities 

• A5.1 Processing of image information from the vehicle surroundings: This includes data acquisition, algorithm design, and testing — using data from the CDV Test Area Catalogue.

• A5.2 Application of machine learning algorithms and neural networks for detection and precise characterization of the surroundings: Application of algorithms with evaluation capabilities, including completion of training for the use of advanced artificial intelligence methods.

• A5.3 Vehicle environment analysis using sensor information: Utilization of vehicle-provided information, data processing, design of an appropriate algorithm, and testing on challenging datasets, e.g., for intersections.

• A5.4 Creation of an intelligent route planning system: Research on algorithms capable of automatically and dynamically generating optimal routes for various types of transport, taking into account their specific parameters, such as current traffic conditions, weather influences, or current road traffic capacity.

• A5.5 Optimization of an intelligent route planning system: Optimize the proposed system to maximize travel efficiency and safety and provide users with a reliable and flexible real-time navigation solution.

Milestones of research activities 

• M5.1 Processing of image data and evaluation of results 

• M5.2 Evaluation of results using artificial intelligence methods 

• M5.3 Conference contribution on sensor data processing 

• M5.4 Vehicle surroundings visualization – evaluation of algorithms 

• M5.5 Publication of an article on 3D mapping of the vehicle surroundings 

• M5.6 Conference contribution on sensor data processing 

• M5.7 Publication in Q1 journals 

• M5.8 Collection of data inputs and algorithm development 

• M5.9 Presentations at conferences, seminars, or publications 

• M5.10 Algorithm optimization and testing of proposed methods 

• M5.11 Publication of results in the field of optimization 

Research outcomes 

• Within this research plan, a total of four software packages (R) will be developed 

• A total of 10 journal publications (Jimp) will be published 

• The research results will be presented at four conferences (D)