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Recent Analysis and Research in the Field of Vehicle Traffic...
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Recent Analysis and Research in the Field of Vehicle Traffic Safety, 2nd Edition

A special issue of Machines (ISSN 2075-1702). This special issue belongs to the section "Vehicle Engineering".

Deadline for manuscript submissions: 30 November 2025 | Viewed by 681

Special Issue Editor

Dr. Konrad Jan Waluś

E-Mail Website
Guest Editor
Institute of Machine Design, Faculty of Mechanical Engineering, Poznań University of Technology, 60-965 Poznań, Poland
Interests: vehicle traffic safety; vehicle dynamics; tire/road contact
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Following the success of the Special Issue entitled “Recent Analysis and Research in the Field of Vehicle Traffic Safety” (https://www.mdpi.com/journal/machines/special_issues/D95K850925), we are pleased to announce the next in the series, entitled “Recent Analysis and Research in the Field of Vehicle Traffic Safety, 2nd Edition”.

The increase in the number of car users, the development of road infrastructure, and the increase in the number of kilometers traveled is forcing vehicle manufacturers, road infrastructure builders, and those who are responsible for devising legal regulations to take action to increase road safety. The identification and assessment of physical phenomena, as well as the analysis of the impact of the driver's behavior during road incidents, represents an important aspect in reducing road accidents and incidents. The crux of this project is the identification and study of important parameters that determine road safety. The quantification of parameters that affect the scope of vehicle traffic safety can be divided into the following basic sources:

  • Vehicle design/active and passive safety; support for driving and steering systems.
  • Interactions at the contact point between the tire and the road surface.The parameter that describes the shape–friction cooperation is the coefficient of adhesion, which is a characteristic feature of the tire–pavement system that depends on the following factors:
    • Tire construction, tread geometry and depth, rubber material properties, wheel load, tire air pressure, and distribution of local unit pressures at the contact point between the tire and the road surface;
    • The type of materials used for pavement construction, parameters of pavement shape and structure, hydrophobic properties, and pavement condition;
    • The factors that determine tire operation, including the speed of movement, slippage, operating temperature, and wear and tear;
    • External factors, such as humidity, snow cover, ice, and ambient and surface temperature.
  • Road infrastructure;
  • Behavior of the driver.

Additional factors that influence road safety include surface type, the arrangement of road infrastructure, and the behavior of the driver.

This Special Issue will bring together both review articles and in-depth research papers on new developments on the above-defined topics.

Dr. Konrad Jan Waluś
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Machines is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • automotive
  • autonomous vehicles
  • vehicle dynamics
  • mobile measurement
  • active deceleration device
  • intelligent speed assist
  • tire/road contact
  • TPMS
  • road condition
  • driving behavior

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Further information on MDPI's Special Issue policies can be found here.

Related Special Issue

Published Papers (2 papers)

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Research

29 pages, 4633 KiB  
Article
Failure Detection of Laser Welding Seam for Electric Automotive Brake Joints Based on Image Feature Extraction
by Diqing Fan, Chenjiang Yu, Ling Sha, Haifeng Zhang and Xintian Liu
Machines 2025, 13(7), 616; https://doi.org/10.3390/machines13070616 - 17 Jul 2025
Viewed by 235
Abstract
As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the [...] Read more.
As a key component in the hydraulic brake system of automobiles, the brake joint directly affects the braking performance and driving safety of the vehicle. Therefore, improving the quality of brake joints is crucial. During the processing, due to the complexity of the welding material and welding process, the weld seam is prone to various defects such as cracks, pores, undercutting, and incomplete fusion, which can weaken the joint and even lead to product failure. Traditional weld seam detection methods include destructive testing and non-destructive testing; however, destructive testing has high costs and long cycles, and non-destructive testing, such as radiographic testing and ultrasonic testing, also have problems such as high consumable costs, slow detection speed, or high requirements for operator experience. In response to these challenges, this article proposes a defect detection and classification method for laser welding seams of automotive brake joints based on machine vision inspection technology. Laser-welded automotive brake joints are subjected to weld defect detection and classification, and image processing algorithms are optimized to improve the accuracy of detection and failure analysis by utilizing the high efficiency, low cost, flexibility, and automation advantages of machine vision technology. This article first analyzes the common types of weld defects in laser welding of automotive brake joints, including craters, holes, and nibbling, and explores the causes and characteristics of these defects. Then, an image processing algorithm suitable for laser welding of automotive brake joints was studied, including pre-processing steps such as image smoothing, image enhancement, threshold segmentation, and morphological processing, to extract feature parameters of weld defects. On this basis, a welding seam defect detection and classification system based on the cascade classifier and AdaBoost algorithm was designed, and efficient recognition and classification of welding seam defects were achieved by training the cascade classifier. The results show that the system can accurately identify and distinguish pits, holes, and undercutting defects in welds, with an average classification accuracy of over 90%. The detection and recognition rate of pit defects reaches 100%, and the detection accuracy of undercutting defects is 92.6%. And the overall missed detection rate is less than 3%, with both the missed detection rate and false detection rate for pit defects being 0%. The average detection time for each image is 0.24 s, meeting the real-time requirements of industrial automation. Compared with infrared and ultrasonic detection methods, the proposed machine-vision-based detection system has significant advantages in detection speed, surface defect recognition accuracy, and industrial adaptability. This provides an efficient and accurate solution for laser welding defect detection of automotive brake joints. Full article
(This article belongs to the Special Issue Recent Analysis and Research in the Field of Vehicle Traffic Safety, 2nd Edition)
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27 pages, 3401 KiB  
Article
Human–Seat–Vehicle Multibody Nonlinear Model of Biomechanical Response in Vehicle Vibration Environment
by Margarita Prokopovič, Kristina Čižiūnienė, Jonas Matijošius, Marijonas Bogdevičius and Edgar Sokolovskij
Machines 2025, 13(7), 547; https://doi.org/10.3390/machines13070547 - 24 Jun 2025
Viewed by 258
Abstract
Especially in real-world circumstances with uneven road surfaces and impulsive shocks, nonlinear dynamic effects in vehicle systems can greatly skew biometric data utilized to track passenger and driver physiological states. By creating a thorough multibody human–seat–chassis model, this work tackles the effect of [...] Read more.
Especially in real-world circumstances with uneven road surfaces and impulsive shocks, nonlinear dynamic effects in vehicle systems can greatly skew biometric data utilized to track passenger and driver physiological states. By creating a thorough multibody human–seat–chassis model, this work tackles the effect of vehicle-induced vibrations on the accuracy and dependability of biometric measures. The model includes external excitation from road-induced inputs, nonlinear damping between structural linkages, and vertical and angular degrees of freedom in the head–neck system. Motion equations are derived using a second-order Lagrangian method; simulations are run using representative values of a typical car and human body segments. Results show that higher vehicle speed generates more vibrational energy input, which especially in the head and torso enhances vertical and angular accelerations. Modal studies, on the other hand, show that while resonant frequencies stay constant, speed causes a considerable rise in amplitude and frequency dispersion. At speeds ≥ 50 km/h, RMS and VDV values exceed ISO 2631 comfort standards in the body and head. The results highlight the need to include vibration-optimized suspension systems and ergonomic design approaches to safeguard sensitive body areas and preserve biometric data integrity. This study helps to increase comfort and safety in both traditional and autonomous car uses. Full article
(This article belongs to the Special Issue Recent Analysis and Research in the Field of Vehicle Traffic Safety, 2nd Edition)
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