Vehicles, Volume 5, Issue 4 (December 2023) – 34 articles

This study tackles the urgent need for efficient condition monitoring of road and rail infrastructure, which is integral to a nation’s economic vitality. Traditional methods proved both costly and inadequate, resulting in network gaps and accelerated infrastructure decay. Employing connected vehicles with integrated sensors and cloud computing capabilities can provide a cost-effective, sustainable solution for comprehensive infrastructure monitoring. In advocating for international standardization, this study furnishes compelling evidence—encompassing trends in transportation, economics, and patent landscapes—that underscores the necessity and advantages of such standards. The analysis confirmed that trucks and rail will remain dominant in freight transport as infrastructure limitations intensify. A noteworthy finding is the absence of patented solutions in this domain, which simplifies the path toward global standardization. By integrating data from diverse sources, agencies can optimize maintenance triggers and allocate funds more strategically, thus preserving vital transportation networks. These insights not only offer an effective alternative to current practices but also have the potential to influence policymaking and industry standards for infrastructure monitoring. Full article

Solar energy is recognized as an alternative to combustion engines to reduce the environmental impact and increase the endurance of unmanned aerial vehicles (UAVs). This work aims to present a project for a solar UAV to contribute to the mission of the Air Force Academy Research Center and test the energy system on the ground. To achieve this study’s objectives, a literature review on photovoltaic cells (PVCs), batteries, and maximum power point tracking algorithms was conducted. The most appropriate airframe and wing designs for this particular type of flight are then investigated. Following that, the project requirements and mission profile were defined, and the copper indium gallium selenide eFilm cells, a solar power management system (SPMS), avionics, and payload required for the mission were chosen based on them. A methodology for ground testing of solar systems was created and used, achieving an endurance of 7 h and 34 min on an April day. The SPMS achieved an efficiency of around 96%, while PVCs ranged from 11.3 to 14.1%. Full article

One of the world’s challenges is the amount of traffic on the roads. Waiting for the green light is a major cause of traffic congestion. Low throughput rates and eventual congestion come from many traffic signals that are hard coded, irrespective of the volume of the amount of traffic. Instead of depending on predefined time intervals, it is essential to build a traffic signal control system that can react to changing vehicle densities. Emergency vehicles, like ambulances, must be given priority at the intersection so as not to spend more time at the traffic light. Computer vision techniques can be used to improve road traffic signal control and reduce real-time traffic delays at intersections without the requirement for substantial infrastructure analysis. Long wait times and significant energy consumption are just two of the problems of the current traffic signal control system. To optimal efficiency, the traffic signal’s duration must be dynamically changed to account for current traffic volume. To lessen congestion, the approach taken in this research focuses on modifying traffic signal time determined by the density of vehicles at the crossroads. The main purpose of this article is to demonstrate heavy traffic and emergency vehicle prioritization from all directions at the traffic intersection for a speedy passage. Using the Pygame tool, the proposed method in this study, which includes a mechanism for estimating traffic density and prioritization by counting vehicles at a traffic junction, is demonstrated. The vehicle throughput for the adaptive traffic light built using Pygame is compared with the vehicle pass rate for the adaptive traffic light built using Simulation of Urban Mobility (SUMO). The simulation results show that the adaptive traffic light built using Pygame achieves 90% throughput compared to the adaptive traffic light built using SUMO. A Two-Dimensional Convolutional Neural Network (2D-CNN) is implemented using Tensorflow for vehicle classification. The 2D-CNN model demonstrated 96% accuracy in classifying vehicles using the test dataset. Additionally, emergency vehicles, such as ambulances, are given priority for quick passing. Full article

The emergence of Automated Driving Systems (ADSs) has transformed the landscape of safety assessment. ADSs, capable of controlling a vehicle without human intervention, represent a significant shift from traditional driver-centric approaches to vehicle safety. While traditional safety assessments rely on the assumption of a human driver in control, ADSs require a different approach that acknowledges the machine as the primary driver. Before market introduction, it is necessary to confirm the vehicle safety claimed by the manufacturer. The complexity of the systems necessitates a new comprehensive safety assessment that examines and validates the hazard identification and safety-by-design concepts and ensures that the ADS meets the relevant safety requirements throughout the vehicle lifecycle. The presented work aims to enhance the effectiveness of the assessment performed by a homologation service provider by using assessment templates based on refined requirement attributes that link to the operational design domain (ODD) and the use of Key Enabling Technologies (KETs), such as communication, positioning, and cybersecurity, in the implementation of ADSs. The refined requirement attributes can serve as safety-performance indicators to assist the evaluation of the design soundness of the ODD. The contributions of this paper are: (1) outlining a method for deriving assessment templates for use in future ADS assessments; (2) demonstrating the method by analysing three KETs with respect to such assessment templates; and (3) demonstrating the use of assessment templates on a use case, an unmanned (remotely assisted) truck in a limited ODD. By employing assessment templates tailored to the technology reliance of the identified use case, the evaluation process gained clarity through assessable attributes, assessment criteria, and functional scenarios linked to the ODD and KETs. Full article

Stakeholders expect emerging urban air mobility (UAM) services that use electric vertical takeoff and landing (eVTOL) aircraft to revolutionize transportation systems. However, to be effective, eVTOL facilities, known as vertiports, must seamlessly integrate with the existing multimodal transportation infrastructure. This research analyzes how to best integrate vertiports with the existing public transit network of a city, with San Francisco in the United States as a case study. This study developed a composite optimization model to identify the locations for an optimum number of vertiports within each of the eleven (11) supervisorial districts of San Francisco that would minimize the network distance to its bus stops. The results revealed that 38 locations for vertiports covered 3245 bus stops with an average walk time close to 10 min. Walking 10 min from each vertiport would cover 41.6% of the total road network length and 49.8% of all bus stop locations. Power-law regressions of the average distances as a function of the number of vertiports will help planners to make informed decisions about the optimal vertiport placements in each district by identifying diminishing returns in travel-time savings, and adjustments that consider income and population as additional demand factors. Full article

The increasing usage of autonomous and automatic systems within the automotive industry is steering us towards a more interconnected world. This enhanced interconnectivity fosters a more streamlined driving experience, reduces costs, and provides timely driver assistance. The electric/electronic (EE) architectures of modern vehicles are inherently complex due to the multitude of components they encompass. Contemporary architectures reveal that these components converge at an electronic control unit (ECU) called the central gateway, which could potentially represent a single point of failure. While this central unit is typically adequately safeguarded, the same cannot be said for the connected components, which often remain vulnerable to cyber threats. The ISO/SAE 21434 standard paved the way for automotive cybersecurity and could be used in parallel with other standards such as ISO 26262 and ISO PAS 21488. Automatic collision notification (ACN) is one of the most typical systems in a vehicle, and limited effort has been dedicated to identifying the most suitable architecture for this feature. This paper addresses the existing security and privacy gap of this feature by conducting a comparative analysis of security threats in two distinct ACN architectures. Notably, despite ACN architectures exhibiting inherent similarities, the primary distinction between the two architectures lies in their strategies for crash estimation and detection, followed by subsequent communication with emergency response teams. A rigorous security assessment was conducted using the ISO/SAE 21434 standard, employing the TARA and STRIDE methodologies through the Ansys medini analyze software. This analysis identified an average of 310 threats per architecture, including a significant number of high-level threats (11.8% and 15%, respectively), highlighting the importance of a comprehensive evaluation. Full article

Electric vehicles and photovoltaic power stations can play an important role in replacing fossil fuels. This article presents a case study on the placement of charging stations powered by photovoltaic energy along an important highway in Brazil. A demand model was adopted to elaborate three scenarios for 2030 with different participation levels of electric vehicles in the Brazilian market. An optimized allocation model was used to derive the location and number of charging stations required to meet the charging demand. The results provided a list of adequate locations for installing the charging stations and offered insights into the consumed electricity and greenhouse gas emissions that could be mitigated by these actions. A financial analysis was conducted, and it was determined that the charging costs, based on the Internal Rate of Return calculation, were 10%. These costs were compared to the fueling costs of other traditional vehicles. The results showed that the costs can be 72% lower than the cost of refueling current conventional automobiles. The results of this study can serve as a reference in the public policy debate, as well as for investors in fast charging stations. Full article

Since electric power steering has replaced hydraulic power steering in passenger cars, steering feedback has become a challenging task in steering system development. Test benches represent a valid approach for improving steering feedback since they allow investigations without the real vehicle. To improve the applicability of feedback evaluations on a steering test bench, this paper aims to identify improvements in the current evaluation technique to obtain objective parameters that correlate with a subjective evaluation of safety-relevant steering feedback. Therefore, a previously reported approach of a chirp rack force excitation, using the magnitude of the transfer function from the rack force to steering wheel torque to describe steering feedback, is compared to a similar identification approach in which a pseudo-random-binary-sequence signal is utilized. To reflect realistic applications, driving maneuvers are transferred to the test bench to identify relevant objective data. For a valid representation of the steering wheel operation, a human grip model is implemented and compared to a fixed steering wheel angle control. It is shown that the random signal represents a valid and, on average, improved approach to objectively evaluating the steering feedback. Furthermore, a recommendation can be made to include the human grip model in the feedback evaluation tests, as the identified correlation results are improved by its inclusion. The identified parameters and methods represent an improvement for future steering feedback development. Full article

Unmanned Aerial Vehicles (UAVs) offer a promising solution for road accident scene documentation. This study seeks to investigate the occurrence of systematic deformations, such as bowling and doming, in the 3D point cloud and orthomosaic generated from images captured by UAVs along an horizontal road segment, while exploring how adjustments in flight patterns can rectify these errors. Four consumer-grade UAVs were deployed, all flying at an altitude of 10 m while acquiring images along two different routes. Processing solely nadir images resulted in significant deformations in the outputs. However, when additional images from a circular flight around a designated Point of Interest (POI), captured with an oblique camera axis, were incorporated into the dataset, these errors were notably reduced. The resulting measurement errors remained within the 0–5 cm range, well below the customary error margins in accident reconstruction. Remarkably, the entire procedure was completed within 15 min, which is half the estimated minimum duration for scene investigation. This approach demonstrates the potential for UAVs to efficiently record road accident sites for official documentation, obviating the need for pre-established Ground Control Points (GCP) or the adoption of Real-Time Kinematic (RTK) drones or Post Processed Kinematic (PPK) technology. Full article

The Third Generation Partnership Project (3GPP) has specified Cellular Vehicle-to-Everything (C-V2X) radio access technology in Releases 15–17, with an emphasis on facilitating direct communication between vehicles through the interface, sidelink PC5. This interface provides end-to-end network slicing functionality together with a stable cloud-native core network. The performance of direct vehicle-to-vehicle (V2V) communications has been improved by using the sidelink interface, which allows for a network infrastructure bypass. Sidelink transmissions make use of orthogonal resources that are either centrally allocated (Mode 1, Release 14) or chosen by the vehicles themselves (Mode 2, Release 14). With growing interest in connected and autonomous vehicles, the advancement in radio access technologies that facilitate dependable and low-latency vehicular communications is becoming more significant. This is especially necessary when there are heavy traffic conditions and patterns. We thoroughly examined the New Radio (NR) sidelink’s performance based on 3GPP Releases 15–17 under various vehicle densities, speeds, and distance settings. Thus, by evaluating sidelink’s strengths and drawbacks, we are able to optimize resource allocation to obtain maximum coverage in urban areas. The performance evaluation was conducted on Network Simulator 3 (NS3.34/5G-LENA) utilizing various network metrics such as average packet reception rate, throughput, and latency. Full article

In recent decades the market share of electrical cars has increased significantly, which has paved the way for the development of automotive electronics. Some of the most important parts of modern electrical vehicles are motor drives, which are used in car training and mechanization. Electrical drives are used in powertrains for traction, in air conditioning systems to cool cars and their parts, in doors for opening/closing as well as window movements, etc. The most popular motor type in electrical vehicles is synchronous motors with permanent magnets, which are compact and provide high torque. However, these motors require the development of control systems for proper operation. This system has to have the capacity to implement several state-of-the-art techniques, which can fully utilize motor potential, increase its efficiency, and decrease battery usage. One of these techniques is field-weakening, which overcomes speed limitations due to a lack of supply voltage and increases the motor’s speed operation range. This paper discusses the most popular approaches to field-weakening, including a new method proposed by the author. It considers both the pros and cons of each approach and provides recommendations for their usage. After that, this manuscript demonstrates the experimental results of each field-weakening technique obtained in the same motor drive, compares their performance, and discusses their strengths and weaknesses. Finally, the experimental part demonstrates that the proposed field-weakening approach demonstrates similar dynamics in load transients but provides 10 times less load to the microcontroller. Full article

The road alignment design relies on the knowledge of vehicle dynamics variables. However, it assumes that drivers faithfully follow the lane axis on straights and curves. Deviating from this assumption leads to unexpected outcomes and can significantly impact users’ safety. In this context, vehicle speed and longitudinal acceleration play a crucial role as key references in the international standards. They provide insights into critical driving aspects; therefore, it is essential to thoroughly analyze their real trends. Broad data collection campaigns should derive synthetic indicators in order to highlight eventual significant deviations between the ideal and real dynamics. To achieve this objective, the authors propose some indexes deduced during an experimental study with a Sim-Easy driving simulator, by AVSimulation. Importantly, these indicators can be freely applied in real driving scenarios without limitations. These indexes were tested on four different horizontal curves and proved effective in identifying relevant characteristics related to longitudinal acceleration and speed. Looking ahead, by analyzing similar data for numerous driving contexts on real roads, infrastructure managers could use this methodology to identify those sections with increased vulnerability for users’ safety. Moreover, the collected data from sensors, processed using these indicators, can be filtered and transmitted to users (via ADAS tools) while driving on a specific road to provide timely warnings about potential difficulties. The indicators control the physical variable (acceleration or speed) on a certain geometric element with reference to what is prescribed by the standard. For example, the acceleration indicators are normalized with respect to a threshold value while for speed indexes, the result depends on the difference between the end control points of the geometrical element. In both cases, international regulations report prescribed or recommended reference values, so the analyst is immediately aware of any critical issues in the maneuver. Full article

The upcoming Euro 7 regulation for Heavy-Duty (HD) vehicles is calling for a further tightening of the Solid Particle Number (SPN) emissions by means of both lowering the applicable limits and shifting the lowest detectable size from 23 nm (SPN₂₃) to 10 nm (SPN₁₀). A late-technology diesel HD truck was tested on a chassis dynamometer in order to assess the necessary particle filtration requirements for a continuously regenerating system. The study showed that passive regeneration under real-world operating conditions can lead to a significant release of SPN₁₀ particles from the current technology Diesel Particulate Filter (DPF) when soot-loaded, even exceeding the currently applicable emission limits. The actual emissions during passive regeneration and following the clean-up of the DPF exceeded the proposed Euro 7 limits by more than an order of magnitude. A prototype DPF, exhibiting a 99% filtration efficiency when clean, was shown to effectively control SPN₁₀ emissions under both operating conditions. The shift to SPN₁₀ also necessitates control of nanoparticles forming inside the Selective Catalytic Reduction (SCR) system, which for the tested truck exceeded the proposed (hot) limit by up to 56%. A dedicated particle filter specifically designed to capture these particles was also evaluated, showing a better than 60% efficiency. The key message of this study is that SPN emissions can be kept at low levels under all conditions. Full article

Climate change and air pollution are two significant challenges facing our society and represent a major driver for new developments in the transport sector. As a consequence, automotive manufacturers have focused on the electrification of vehicle propulsion systems and offer a wide range of hybrid and full-electric vehicles in different classes. However, in the world’s most densely populated metropolitan areas, small and lightweight vehicles are key for the mobility of millions. Traditionally these vehicles have provided cost-effective transportation which is difficult to preserve with vehicle electrification. Many of these light vehicles, such as scooters and all-terrain vehicles, use internal combustion engines in combination with a continuously variable rubber belt transmission which provides a simple, comfortable and cost-effective transmission technology but with poor efficiency and high maintenance costs. In this contribution, a novel full hybrid powertrain concept is proposed that offers a similar driving experience to conventional continuously variable transmissions while providing significantly improved performance and fuel economy combined with low system complexity. In its basic configuration, the hybrid powertrain can operate without active actuators and even with mechanical throttle control of the internal combustion engine. This minimalist approach reduces system costs and helps to create a competitive solution for price-sensitive markets. The hybrid system is based on a planetary gear set that combines the internal combustion engine and an electric motor. It is complemented by a centrifugal clutch and one-way clutch, resulting in different operating modes for low and high speeds as well as for electric driving. This paper describes the mechanical design and control approach of the proposed hybrid powertrain layout. In order to evaluate the basic functionalities, a prototype vehicle was built and tested. This contribution shows the integration of the hybrid powertrain concept in a prototype vehicle and proves the fulfilment of all required full hybrid functionalities. Full article

In the world of motorsports engineering, improving brake performance is a crucial goal. One significant factor that affects this performance is the increase in brake disc temperature due to reduced cooling airflow, a phenomenon called “blanking”. This temperature increase also impacts the rim and the air inside the tire, causing changes in tire temperature and pressure, which affects the vehicle’s performance. Properly adjusting the brake blanking can be essential to keep the tire running at the right temperature, resulting in maximization of the performance on track. To address this complex problem, this study describes the problem of cooling brake discs, and this problem is then used as an opportunity to introduce a new variable in order to optimize the performance of the vehicle. By changing the thermal evolution of the brake disc, through the blanking, it can change a large percentage of heat that heats the tire. When combining an existing brake model in the literature with a tire thermal model in a co-platform simulation, it was seen that it is possible to work these two models together with the aim of being able to obtain the prediction of the optimal blanking value to be adopted before proceeding on track, thus saving time and costs. Full article

We provide a practical implementation of a free space optical quantum key distribution (FSO-QKD) system within a vehicle-to-infrastructure (V2I) application developed under the Innovate UK AirQKD project. The FSO-QKD system provides the quantum secure encryption keys that serve as the foundation for secure communications throughout the V2I application to address known concerns over V2I security. This document includes summaries of the quantum key generation process and the deployed V2I technology. Subsequently, a high-level view of the system design, the practical experiment, and its execution are presented. Multiple AirQKD project partners developed technologies ranging from semiconductors and hardware to security protocols and software, to enable the QKD-secured V2I system. The developed technology includes a novel zero-trust security protocol used to protect the V2I communications, ensuring that spoofed V2I messages from a compromised device are not accepted by the system. Full article

This work focuses on the design of a hybrid proton exchange membrane fuel cell (PEMFC) solution for any micro vehicle such as an unmanned aerial vehicle (UAV). A hydrogen fuel cell can provide extended operation, low emissions, and a highly efficient form of energy storage compared with alternative methods, while a battery can be used as an additional energy storage system to support the transient and higher loads required by the UAV, which are not suitable for normal fuel cell operation. The choice of hydrogen storage is one of the main challenges in using hydrogen as an energy carrier. The current study discusses a range of hydrogen storage technologies and provides a methodology for selection for a given application. A sizing design methodology for a hybrid fuel cell system is proposed. Then, it is applied to a case study to demonstrate its implementation. Full article

This paper proposes a combined system (OPREVU-AES) that integrates optimized AEB and Automatic Emergency Steering (AES) to generate evasive maneuvers, and it provides an assessment of its effectiveness when compared to a commercial AEB system. The optimized AEB system regulates the braking response through a collision prediction model. OPREVU is a research project in which INSIA-UPM and CEDINT-UPM cooperate to improve driving assistance systems and to characterize pedestrians’ behavior through virtual reality (VR) techniques. The kinematic and dynamic analysis of OPREVU-AES is conducted using CarSim© software v2020.1. The avoidance trajectories are predefined for speeds above 40 km/h, which controls the speed and lateral stability during the overtaking and lane re-entry process. In addition, the decision algorithm integrates information from the lane and the blind spot detectors. The effectiveness evaluation is based on the reconstruction of a sample of vehicle-to-pedestrian crashes (INSIA-UPM database), using PCCrash© software v. 2013, and it considers the probability of head injury severity (ISP) as an indicator. The incorporation of AEB can avoid 53.8% of accidents, with an additional 2.5–3.5% avoided by incorporating automatic steering. By increasing the lateral activation range, the total avoidance rate is increased to 61.8–69.8%. The average ISP reduction is 65%, with significant reductions achieved in most cases where avoidance is not possible. Full article

To increase the acceptance of electric vehicles (EVs), inductive charging technology can be an important tool because of the simplified charging process for the user. This paper presents the fundamentals of wireless power transfer (WPT) for EVs, while focusing on electromagnetic compatibility (EMC). This work deals with the investigation of the conducted and field-bound interference emissions using a WPT system with a max. input power of $3.6 \mathrm{k}\mathrm{W}$. During the research, a new frequency-tracking algorithm is developed, to find the optimal operating frequency at any coil misalignment. The impedance behavior as well as the possible interference paths are investigated, showing the great geometric influence of the test bench setup. The conducted interference currents are analyzed and subsequently filtered. The filter shows good performance in attenuating common mode currents. The measured radiated magnetic field is directly rated against the proposed limits of various standards. Finally, the EMC influence of the direct current (DC) power supply line to the inverter is examined, which is not defined precisely in the standard. This underlines the significance of a standardized test setup, since the limit values can be met under different geometric circumstances of the DC cable. Full article

During normal ageing, physical changes take place in the biomechanical, musculoskeletal, and psychomotor systems, that reduce strength, flexibility, motor coordination, balance, and precision of movements. This article analyses the motion behaviour of a sample of 49 senior and pre-senior subjects during the process of entry to (ingress) and exit from (egress) new car models not experienced before, obtained over five days at the Geneva International Motor Show. The methodological process is based on visual studies using photography and video to analyse motion behaviour. This investigation identifies five entry movement strategies and three exit movement strategies in three types of vehicle groups. The movements adopted in the egress of the vehicle were more complex and difficult, in general, than those observed for ingress, requiring greater flexibility, agility/dexterity, and physical strength of subjects, involving more contact or support with vehicle parts. The main factor that influenced movement strategies was essentially related to subjects’ levels of physical capacity and previous experiences. Several subjects’ movement strategies were observed in each type of vehicle, confirming that the user’s somatic experience strongly influences the interaction with new vehicles. User’s vehicles’ past experiences and their psychomotor skills determined the adopted movement strategy, which occurred in an unreflective and natural way, regardless of the new type of vehicle. However, due to substantial differences between the vehicles, some subjects may have adopted a different movement strategy in response to these variations. Full article

Although research has shown that through the additional rigidity introduced in the secondary suspension, traction rods can affect the vertical dynamic performance of railway vehicles, this topic has been less studied by researchers in the field. In this paper, the effect of a traction rod on the vertical vibration behavior of a carbody of a railway vehicle is analyzed, using the results obtained through numerical simulations. Numerical simulation applications are developed based on a vehicle model, where the vehicle carbody is modeled using a free-free equivalent beam Euler–Bernoulli, and the bogie chassis and wheelsets are represented by rigid bodies linked together by Kelvin-Voigt systems that model the secondary suspension and the primary suspension. The novelty element of this paper is found in the model of the traction rod. This includes traction rod damping, which has been neglected in previous research. The stiffness and damping of the traction rod are represented by a longitudinal Kelvin–Voigt system integrated into a secondary suspension model. The effect of the traction rod on the vertical vibration behavior of the vehicle carbody is analyzed based on the power spectral density of the acceleration, the root mean square of acceleration, and the ride comfort index, for three cases for analysis: a ‘without traction rod’ case, a ‘with traction rod—with damping’ case, and a ‘with traction rod—without damping’ case. The conclusions of the paper highlight the influence of the stiffness and damping of the traction rod on the vibration level of the carbody, especially in its middle. Depending on the stiffness of the traction rod, significant increases in the ride comfort index are obtained, which at high velocities can exceed 300%. Damping of the traction rod reduces the ride comfort index by up to 10%. Full article

Actors of the Cooperative Intelligent Transport Systems (C-ITS) generate various amounts of data. Useful information on various issues such as anomalies, failures, road profiles, etc., could be revealed from the analysis of these data. The analysis, could be managed by operators and vehicles, and its output could be very helpful for future decision making. In this study, we collected real data extracted from road operators. We analyzed these streams in order to verify whether abnormal behaviors could be observed in the data. Our main target was a very sensitive C-ITS failure, which is when a road-side unit (RSU) experiences transmission failure. The detection of such failure is to be achieved by end users (vehicles), which in turn would inform road operators which would then recover the failure. The data we analyzed were collected from various roads in Europe (France, Germany, and Italy) with the aim of studying the RSUs’ behavior. Our mechanism offers compelling results regarding the early detection of RSU failures. We also proposed a new C-ITS message dedicated to raise alerts to road operators when required. Full article

Vehicle-to-grid means that electric vehicles are charged when electricity is plentiful and discharged when it is scarce. New battery-electric vehicles have an energy capacity above 60 kWh installed and practically always have a DC connector. With over 1 million of such vehicles in Germany alone already, the flexibility potential to balance out fluctuating renewable generation or compensate for grid constraints is large. While many actors are working to enable this market, the readiness of hardware and regulations as well as the potential volume are hard to grasp. This paper provides an overview of these factors for Europe with a special focus on Germany. We find that some countries started to implement regulatory frameworks but none are ready yet. Issues include taxation, the fulfillment of grid codes, and the lack of smart meters. In terms of vehicles, 25 manufacturers with bidirectional charging ability were identified, but most vehicles were only used in field tests or operate in island mode. In terms of charging infrastructure, the picture is brighter with at least 20 manufacturers that offer DC bidirectional charging stations and 2 offering an AC variant. Full article

Path planning is the most fundamental necessity for autonomous mobile robots. Traditionally, the path planning problem was solved using analytical methods, but these methods need perfect localization in the environment, a fully developed map to plan the path, and cannot deal with complex environments and emergencies. Recently, deep neural networks have been applied to solve this complex problem. This review paper discusses path-planning methods that use neural networks, including deep reinforcement learning, and its different types, such as model-free and model-based, Q-value function-based, policy-based, and actor-critic-based methods. Additionally, a dedicated section delves into the nuances and methods of robot interactions with pedestrians, exploring these dynamics in diverse environments such as sidewalks, road crossings, and indoor spaces, underscoring the importance of social compliance in robot navigation. In the end, the common challenges faced by these methods and applied solutions such as reward shaping, transfer learning, parallel simulations, etc. to optimize the solutions are discussed. Full article

The vast majority of autonomous driving systems are limited to applications on roads with clear lane markings and are implemented using commercial-grade sensing systems coupled with specialized graphic accelerator hardware. This research reviews an alternative approach for autonomously steering vehicles that eliminates the dependency on road markings and specialized hardware. A combination of machine vision, machine learning, and artificial intelligence based on popular pre-trained Convolutional Neural Networks (CNNs) and Recurrent Neural Networks (RNNs) was used to drive a vehicle along roads lacking lane markings (unmarked roads). The team developed and tested this approach on the Autonomous Campus Transport (ACTor) vehicle—an autonomous vehicle development and research platform coupled with a low-cost webcam-based sensing system and minimal computational resources. The proposed solution was evaluated on real-world roads and varying environmental conditions. It was found that this solution may be used to successfully navigate unmarked roads autonomously with acceptable road-following behavior. Full article

In the current scenario of fast technological advancement, increasingly characterized by widespread adoption of Artificial Intelligence (AI)-driven tools, the significance of autonomous systems like chatbots has been highlighted. Such systems, which are proficient in addressing queries based on PDF files, hold the potential to revolutionize customer support and post-sales services in the automotive sector, resulting in time and resource optimization. Within this scenario, this work explores the adoption of Large Language Models (LLMs) to create AI-assisted tools for the automotive sector, assuming three distinct methods for comparative analysis. For them, broad assessment criteria are considered in order to encompass response accuracy, cost, and user experience. The achieved results demonstrate that the choice of the most adequate method in this context hinges on the selected criteria, with different practical implications. Therefore, this work provides insights into the effectiveness and applicability of chatbots in the automotive industry, particularly when interfacing with automotive manuals, facilitating the implementation of productive generative AI strategies that meet the demands of the sector. Full article

In hybrid vehicle development, the operating strategy has a decisive role in meeting the development goals, such as compliance with emission standards and high energy efficiency. A considerable number of interactions and cross-influences on other topics, such as emissions, on-board diagnostics, or drivability, must be considered during the calibration process. In this context, the given time constraints pose further challenges. To overcome these, approaches for virtualization of the calibration process are an effective measure. For this purpose, in the current study, a real engine control unit is embedded into a virtual simulation environment on so-called hardware-in-the-loop (HiL) testbenches, which allow virtual calibration and validation of the complete target vehicle. In this context, the paper presents a novel method for virtual calibration of operating strategies for hybrid-electric propulsion systems. This includes an innovative multi-criterial approach that considers the requirements of several development tasks, such as emission and OBD calibration. Measurement data for this optimization is generated on a HiL testbench setup tailored for the described methodology, including both the electrical setup and the simulation environment. To validate the selection of modeling approaches and the parametrization, the simulation environment is operated in open loop. The results of the open loop validation show promising behavior regarding the proposed use case. Finally, the presented methodology is evaluated regarding time and cost savings compared to a conventional approach. Full article

This paper proposes a control strategy for active lateral secondary suspension that uses preview data. Based on a derived analytical model, a model predictive controller (MPC) is implemented. The influence of the track irregularities upon carbody lateral dynamics is considered explicitly. The controller developed is applied to a full-scale rail vehicle model. Ride comfort is evaluated according to EN 12299. Multibody simulations show that there is a significant increase in continuous ride comfort on poor-quality tracks. Full article

This paper presents methods for vehicle state estimation and prediction for autonomous driving. A round intersection is chosen for application of the methods and to illustrate the results as autonomous vehicles have difficulty in handling round intersections. State estimation based on the unscented Kalman filter (UKF) is presented in the paper and then applied to state estimation of vehicles in a round intersection. The microscopic traffic simulator SUMO (Simulation of Urban Mobility) is used to generate realistic traffic in the round intersection for the simulation experiments. Change point detection-based driving behavior prediction using a multipolicy approach is then introduced and evaluated for the round intersection. Finally, these methods are combined for vehicle trajectory estimation based on UKF and policy prediction and demonstrated using the round intersection. Full article

Electric vehicles are becoming more popular as an alternative to conventional gasoline-powered vehicles. In order to strengthen charging infrastructure, dynamic wireless charging (DWC) is a promising technology through which the vehicle battery can be continuously charged while the vehicle is in motion. The main challenge of the DWC system is to investigate the capability for power transfer with the variation in operating parameters in consideration of enhanced efficiency. This study proposes an innovative approach to improve the performance of dynamic wireless charging systems by investigating the magnetic coupler via finite element analysis, exploring power pulsation and mutual inductances with variations in longitudinal, lateral, and air gap distances as variable factors. In addition to this, efficiency analysis is also explored with respect to the mutual inductance and various compensation schemes. The simulation studies are carried out using computer-assisted software, i.e., COMSOL Multiphysics 5.5 and MATLAB version 2022b. Finally, a comparative analysis of power transferred, mutual inductance, and efficiency is presented by the compensation schemes. Full article