The conventional process of last-mile delivery logistics often leads to safety problems for road users and a high level of environmental pollution. Delivery drivers must deal with frequent stops, search for a convenient parking spot and sometimes navigate through the narrow streets causing traffic congestion and possibly safety issues for the ego vehicle as well as for other traffic participants. This process is not only time consuming but also environmentally impactful, especially in low-emission zones where prolonged vehicle idling can lead to air pollution and to high operational costs. To overcome these challenges, a reliable system is required that not only ensures the flexible, safe and smooth delivery of goods but also cuts the costs and meets the delivery target.
In the evolving landscape of automated driving systems, the critical role of vehicle localization within the autonomous driving stack is increasingly evident. Traditional reliance on Global Navigation Satellite Systems (GNSS) proves to be inadequate, especially in urban areas where signal obstruction and multipath effects degrade accuracy. Addressing this challenge, this paper details the enhancement of a localization system for autonomous public transport vehicles, focusing on mitigating GNSS errors through the integration of a LiDAR sensor. The approach involves creating a 3D map using the factor graph-based LIO-SAM algorithm based on GNSS, vehicle odometry, IMU and LiDAR data. The algorithm is adapted to the use-case by adding a velocity factor and altitude data from a Digital Terrain model. Based on the map a state estimator is proposed, which combines high-frequency LiDAR odometry based on FAST-LIO with low-frequency absolute multiscale ICP-based LiDAR position estimation.
The global time that is propagated and synchronized in the vehicle E/E architecture is used in safety-critical, security-critical, and time-critical applications (e.g., driver assistance functions, intrusion detection system, vehicle diagnostics, external device authentication during vehicle diagnostics, vehicle-to-grid and so on). The cybersecurity attacks targeting the global time result in false time, accuracy degradation, and denial of service as stated in IETF RFC 7384. These failures reduce the vehicle availability, robustness, and safety of the road user. IEEE 1588 lists four mechanisms (integrated security mechanism, external security mechanism, architectural solution, and monitoring & management) to secure the global time. AUTOSAR defines the architecture and detailed specifications for the integrated security mechanism "Secured Global Time Synchronization (SGTS)" to secure the global time on automotive networks (CAN, FlexRay, Ethernet).
The optimization and further development of automated driving functions offers great potential to relieve the driver in various driving situations and increase road safety. Simulative testing in particular is an indispensable tool in this process, allowing conclusions to be drawn about the design of automated driving functions at a very early stage of development. In this context, the use of driving simulators provides support so that the driving functions of tomorrow can be experienced in a very safe and reproducible environment. The focus of the acceptance and optimization of automated driving functions is particularly on vehicle lateral control functions. As part of this paper, a test person study was carried out regarding manual vehicle lateral control on the dynamic vehicle road simulator at the Institute of Automotive Engineering.
In the context of urban smart mobility, vehicles have to communicate with each other, surrounding infrastructure, and other traffic participants. By using Vehicle2X communication, it is possible to exchange the vehicles’ position, driving dynamics data, or driving intention. This concept yields the use for cooperative driving in urban environments. Based on current V2X-communication standards, a methodology for cooperative driving of automated vehicles in mixed traffic scenarios is presented. Initially, all communication participants communicate their dynamic data and planned trajectory, based on which a prioritization is calculated. Therefore, a decentralized cooperation algorithm is introduced. The approach is that every traffic scenario is translatable to a directed graph, based in which a solution for the cooperation problem is computed via an optimization algorithm.
Reductions in powertrain noise have led to an increased proportion of road noise, prompting various studies aimed at mitigating it. Road excitation primarily traverses through the vehicle suspension system, necessitating careful optimization of the characteristics of bushings at connection points. However, optimizing at the vehicle assembly stage is both time-consuming and costly. Therefore, it is essential to proceed with optimization at the subsystem level using appropriate objective functions. In this study, the blocked force and energy-based index derived from complex power were used to optimize the NVH performance. Calculating the complex power in each bushing enables computing the power flow, thereby providing a basis for evaluating the NVH performance. Through stiffness injection, the frequency response functions (FRF) of the system can be predicted according to arbitrary changes in the bushing stiffness.
With the electrification of powertrains, the noise level inside vehicles reach high levels of silence. The dominant engine noise found in traditional vehicles is now replaced by other sources of noise such as rolling noise and aeroacoustic noise. These noises are encountered during driving on roads and highways and can cause significant fatigue during long journeys. Regarding aeroacoustic phenomena, the noise transmitted into the cabin is the result of both turbulent pressure and acoustic pressure created by the airflow. Even though it is lower in level, the acoustic pressure induces most of the noise perceived by the occupants. Its wavelength is closer to the characteristic vibration wavelengths of the glass, making its propagation more efficient through the vehicle's windows. The accurate modeling of these phenomena requires the coupling of high-frequency computational fluid dynamics (CFD) simulations and vibro-acoustic simulations.
The NVH performance of electric vehicles is a key indicator of vehicle quality, being the structure-borne transmission predominating at low frequencies. Many issues are typically generated by high vibrations, transmitted through different paths, and then radiated acoustically into the cabin. A combined analysis, with both finite-element and multi-body models, enables to predict the interior vehicle noise and vibration earlier in the development phases, to reduce the development time and moreover to optimize components with an increased efficiency level. In the present work, a simulation of a Hyundai electric vehicle has been performed in IDIADA VPG with a full vehicle multibody (MBD) model, followed by vibration/acoustic simulations with a Finite elements model (FEM) in MSC. Nastran to analyze the comfort. Firstly, a full vehicle MBD model has been developed in MSC. ADAMS/Car including representative flexible bodies (generated from FEM part models).
By analyzing the dynamic distortion in all body closure openings in a complete vehicle, a better understanding of the body characteristics can be achieved compared to traditional static load cases such as static torsional body stiffness. This is particularly relevant for non-traditional vehicle layouts and electric vehicle architectures. The body response is measured with the so-called Multi Stethoscope (MSS) when driving a vehicle on a rough pavé road (cobble stone). The MSS is measuring the distortion in each opening in two diagonals. During the virtual development, the distortion is described by the relative displacement in diagonal direction in time domain using a modal transient analysis. The results are shown as Opening Distortion Fingerprint ODF and used as assessment criteria within Solidity and Perceived Quality. By applying the Principal Component Analysis (PCA) on the time history of the distortion, a Dominant Distortion Pattern (DDP) can be identified.
Design and Manufacturing of an Inclinometer sensing element for launch vehicle applications Tony M Shaju, Nirmal Krishna, G Nagamalleswara Rao, Pradeep K Scientist/Engineer, ISRO Inertial Systems Unit, Vattiyoorkavu, Trivandrum, India - 695013 Indian Space Research Organisation (ISRO) uses indigenously developed launch vehicles like PSLV, GSLV, LVM3 and SSLV for placing remote sensing and communication satellites along with spacecrafts for other important scientific applications into earth bound orbits. Navigation systems present in the launch vehicle play a pivotal role in achieving the intended orbits for these spacecrafts. During the assembly of these navigation packages on the launch vehicle, it is required to measure the initial tilt of the navigation sensors for any misalignment corrections, which is given as input to the navigation software. A high precision inclinometer is required to measure these tilts with a resolution of 1 arc-second.
Abstract Unlike conventional launch vehicles the winged body reusable launch vehicle needs to be tested and evaluated for its functionality during the pre-flight preparation at the runway. The ground based checkout systems for the avionics and actuators performance testing during pre-flight evaluation and actuation are not designed for rapid movement. The new kind of launch vehicle with conventional rocket motor first-stage and winged body upper-stage demands the system testing at Launchpad and at runway. In the developmental flights of the winged body part of the vehicle, the pre-flight testing needs to be carried out extensively at runway. The safety protocol forbids the permanent structure for hosting the checkout system near runway. The alternative is the development of a rapidly deployable and removable checkout system. A design methodology adopting conventional industrial instrumentation systems and maintaining mobility is presented.
Advanced Air Mobility (AAM) envisions heterogenous airborne entities like crewed and uncrewed passenger and cargo vehicles within, and between urban and rural environment. To achieve this, a paradigm shift to a cooperative operating environment similar to Extensible Traffic Management (xTM) is needed. This requires the blending of Traditional Air Traffic Services (ATS) with the new generation AAM vehicles having their unique flight dynamics and handling characteristics. A hybrid environment needs to be established with enhanced shared situational awareness for all stakeholders, enabling equitable airspace access, minimizing risk, optimized airspace use, and providing flexible and adaptable airspace rules. This paper introduces a novel concept of distributed airspace management which would be apt for all kinds of operational scenarios perceived for AAM. The proposal is centered around the efficiency and safety in air space management being achieved by self-discipline.
To investigate the rollover phenomena experienced by all-terrain vehicles (ATVs) during their motion caused by input from the road surface, a combined simulation using CarSim and Simulink has been employed to validate an active anti-rollover control strategy based on differential braking for ATVs, followed by vehicle testing. In the research process, a nonlinear three-degrees-of-freedom vehicle model has been developed. By utilizing a zero-moment point index as a rollover warning indicator, this approach could accurately detect the rollover status of the vehicle, particularly in scenarios involving low road adhesion on unpaved surfaces, which are characteristic of ATV operation. The differential braking, generating a roll moment by adjusting the amount of lateral force each braked tire can generate, was proved as an effective method to enhance rolling stability.
Cameras, radars, sensors, displays autonomous driving. car must support all these devices safe, secure, reliable. address challenges in-vehicle connectivity, multi-gigabit bandwidth, safetu, resilience data links, connectivity.
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Understanding left-turn vehicle-pedestrian accident mechanisms is critical for developing accident-prevention systems. This study aims to clarify the features of driver behavior focusing on drivers’ gaze, vehicle speed, and time to collision (TTC) during left turns at intersections on left-hand traffic roads. Herein, experiments with a sedan and light-duty truck (< 7.5 tons GVW) are conducted under four conditions: no pedestrian dummy (No-P), near-side pedestrian dummy (Near-P), far-side pedestrian dummy (Far-P) and near-and-far side pedestrian dummies (NF-P). For NF-P, sedans have a significantly shorter gaze time for left-side mirrors compared with light-duty trucks. The light-duty truck’s average speed at the initial line to the intersection (L1) and pedestrian crossing line (L0) is significantly lower than the sedan’s under No-P, Near-P, and NF-P conditions, without any significant difference between any two conditions.
This SAE Recommended Practice is applicable to two- or three-wheel motorcycles intended for highway use. Unless noted, requirements apply to both metallic and nonmetallic tanks. Accessory or aftermarket tanks as well as original equipment tanks are covered.
Abstract With the rapid growth of automobile ownership, traffic congestion has become a major concern at intersections. In order to alleviate the blockage of intersection traffic flow caused by signals, reduce the length of vehicle congestion and waiting time, and for improving the intersection access efficiency, therefore, this article proposes a vehicle speed guidance strategy based on the intersection signal change by combining the vehicle–road cooperative technology. The randomness of vehicle traveling speed in the road is being considered. According to the vehicle traveling speed, a speed guidance model is established under different conditions.
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