Vehicles, Volume 8, Issue 1

The development of modern vehicles faces an increase in complexity, as well as a need for shorter development cycles and a seamless cross-domain integration. In order to meet these challenges, a graph-based design language which formalizes and automa...

This study focused on developing and validating machine learning models to predict pavement marking retroreflectivity using Light Detection and Ranging (LiDAR) intensity data. The retroreflectivity data was collected using a Mobile Retroreflectometer...

Vehicle exhaust gases remain one of the key sources of atmospheric air pollution and pose a serious threat to ecosystems and public health. This study presents an experimental investigation into reducing the toxicity of gasoline internal combustion e...

This study investigates cross-cultural differences in public perception of mobility electrification by applying natural language processing (NLP) techniques to social media discourse in Germany and China. Using a large language model (LLM), this stud...

Predicting the severity of traffic accidents remains challenging due to the limited ability of existing methods to extract deep semantic information from unstructured accident narratives, as traditional approaches typically depend on structured data...

This research paper proposes a solution to reduce CO₂ emissions from a spark ignition engine’s exhaust gases by installing a filtration system on the vehicle’s exhaust pipe. The analyzed filtration system was not patented and was in the t...

This paper presents a kind of dual-channel coupled radial magnetic field resolver (DCCRMFR). The exciting winding and signal winding of this resolver adopt the structure of orthogonal phase. The number of turns and distribution of the four phase sign...

Vehicle repeated passes over soft terrain alter the soil’s bearing and shear behavior, thereby affecting vehicle mobility and energy consumption. To address this issue, this study conducted cyclic compression and shear tests on beach sand with...

Object detection for autonomous vehicles under adverse weather conditions—such as rain, fog, snow, and low light—remains a significant challenge due to severe visual distortions that degrade image quality and obscure critical features. Th...

Improving the ride comfort of commercial vehicles is crucial for driver health and operational safety. This study focuses on optimizing the parameters of a cab suspension system to improve its vibration isolation performance. Initially, nonlinear fit...

Direct injection in hydrogen engines enables flexible combustion control, improves engine efficiency, and reduces the risk of abnormal combustion. However, implementing this injection strategy is challenging due to the need to provide a relatively hi...

To address the issue of insufficient trajectory tracking accuracy and the stability of distributed drive mining dump trucks under complex working conditions, this paper proposes a model predictive control (MPC) strategy based on genetic-particle swar...

A device under test, when applied to the test rig, often does not come with much information about its mechanical properties to the user. There are different applications in which specific properties of the device under test are of interest to the us...

High-altitude long-endurance (HALE) UAVs require navigation payloads that are both fully autonomous and lightweight. This paper presents a full-parameter calibration method for a dual-axis rotational-modulation RINS/CNS integrated system in which the...

The rapid development of China’s high-speed railways (HSRs) and the implementation of revenue management policies have promoted the marketization of railway passenger transport, which is mainly reflected in the gradual transformation from a sel...

This paper proposes an integrated numerical–experimental methodology for the durability assessment and optimisation of a passenger-car rear axle. A dedicated rear-suspension durability test bench was designed to impose a controlled cyclic verti...

Autonomous vehicles (AVs) are expected to operate safely and efficiently in complex urban environments characterized by dynamic and uncertain elements such as pedestrians, cyclists and adverse weather. Although current neural network-based decision-m...

This article presents the results of simulation-based research aimed at assessing the impact of tyre damage on vehicle travel safety. The analysis takes into account various influencing factors, including vehicle speed, load conditions, and road surf...

This paper proposes the integration of the phase-field method (PFM) with deep neural networks (DNNs) for UAV navigation in smart city environments. Using the proposed approach, simulations of an intelligent navigation and obstacle avoidance framework...

Highway traffic incident management is a dynamic and time-dependent process, and rapidly and accurately predicting its complete sequence of actions and corresponding time schedule is essential for improving the refinement and intelligence of traffic...

Road anomaly detection is essential for intelligent transportation systems and road maintenance. This work presents a MATLAB-native hybrid Convolutional Neural Network–Bidirectional Long Short-Term Memory (CNN–BiLSTM) framework for contex...

The study investigates the combined effects of material selection, manufacturing constraints, and a dynamic stress constraint function on the resulting material distribution achieved through a structural optimization process, while ensuring full comp...

The one-step hybrid forming process is a novel process to fabricate a metal fiber-reinforced plastic (FRP) structure with reduced cycle time and cost compared to classical multi-step methods. It is realized by a combined forming tool for both sheet m...

The electric vehicle (EV) battery supply chain plays a critical role in promoting sustainable transportation and tackling scarce resources, environmental costs, and supply chain vulnerabilities. The current study aims to conduct an extensive literatu...