Vehicle Breakdowns Research Articles

DriveMate - Vehicle Breakdown Assistance using Mobile Application

The increasing need for on-demand vehicle breakdown assistance calls for a system that connects stranded drivers with nearby mechanics through a seamless mobile interface. This paper presents a survey of existing technologies, applications, and algorithms that aid in the development of a real-time mechanic dispatch platform. The app allows for mechanic registration, user-mechanic connectivity based on GPS location, and ratings to enhance service reliability. This survey highlights methods for implementing proximity-based assistance, secure admin control for mechanic vetting, and efficient user-to-mechanic communication

Surveillance Unmanned Ground Vehicle Path Planning with Path Smoothing and Vehicle Breakdown Recovery

As unmanned ground vehicles (UGV) continue to be adapted to new applications, an emerging area lacks proper guidance for global route optimization methodology. This area is surveillance. In autonomous surveillance applications, a UGV is equipped with a sensor that receives data within a specific range from the vehicle while it traverses the environment. In this paper, the ant colony optimization (ACO) algorithm was adapted to the UGV surveillance problem to solve for optimal paths within sub-areas. To do so, the problem was modeled as the covering salesman problem (CSP). This is one of the first applications using ACO to solve the CSP. Then, a genetic algorithm (GA) was used to schedule a fleet of UGVs to scan several sub-areas such that the total distance is minimized. Initially, these paths are infeasible because of the sharp turning angles. Thus, they are improved using two methods of path refinement (namely, the corner-cutting and Reeds–Shepp methods) such that the kinematic constraints of the vehicles are met. Several test case scenarios were developed for Goheung, South Korea, to validate the proposed methodology. The promising results presented in this article highlight the effectiveness of the proposed methodology for UGV surveillance applications.

Hyundai's Modular MBSE Approach to ‘Purpose Built Vehicle’ Architecture Development

AbstractThis paper discusses an ongoing effort at Hyundai to develop a model‐based systems engineering (MBSE) methodology for cross‐domain vehicle architecture development that is practical at the enterprise level. Our approach follows a modular modeling process that complements MBSE. In the age of smart mobility, automobile systems are indeed interdependent elements of a system of systems (SoS). Connectedness favors numerous mobility features that emerge due to the interfaces among these constituent systems. Managing emergent product line variations, changing consumer demands coupled with faster market response require manufacturers to modularize their architecture development processes. This can help scale MBSE across vehicle programs. This study proposes a modular system architecture approach for developing Hyundai's purpose‐built vehicle (PBV) concept that maintains a link to the legacy vehicle breakdown structures already in use. Using the Arcadia method, the ‘to‐be’ developed electric vehicle is expressed as a hierarchical functional partitioning of the subsystem modules. A physical architecture is defined as a solution to the functional partitioning based on an existing vehicle breakdown in a combined ‘top‐down/bottom‐up’ workflow thus capturing a realistic system decomposition. In the SoS hierarchy, the PBV is at the top level and is partitioned into multiple levels of nested subsystem architectures owned and developed by designated module teams in a distributed modeling environment. Results of the preliminary architecture modularization effort indicate significant potential for benefits over classical architecture modeling such as iterative knowledge capture, enhanced reusability across projects, products and programs, and distributed vehicle performance development across the extended MBSE enterprise, which includes the tier 1/2 suppliers.

An Intelligent Vehicle Breakdown Assistance Management Services

In today's fast-paced world, vehicle breakdowns can occur unexpectedly, causing inconvenience and disruption to such individuals' daily routines. Prompt assistance failure, during such situations is crucial to ensure the safety and location. The admin interface allows authorize and well-being of vehicle owners and passengers. Personnel to log in and access a list of problematic to address this need, this project aims to develop a comprehensive vehicle breakdown management both customers and administrators. The system facilitates customers to register their details securely by providing support. Essential information such as username, password, phone number, and email ID. their vehicle details, including vehicle name, date, vehicle number, and the nature of the problem, as oil leakage, breakdown, puncture, engine vehicles reported by customers with their current GPS location.

On Road Vehicle Helper (ORVH) React Native Application

The On Road Vehicle Helper (ORVH) application serves as a vital tool for individuals encountering mechanical issues with their vehicles, especially in remote or faraway locations. This paper introduces ORVH as a reliable platform connecting clients with legally endorsed and proficient mechanics. Users can access a curated list of experts through a streamlined application process, facilitating prompt assistance in challenging situations arising from vehicle breakdowns. Furthermore, the ORVH framework prioritizes the engagement of accredited mechanics, ensuring quality service delivery. This paper highlights the significance of ORVH in addressing the uncertainty faced by vehicle owners regarding mechanical failures in remote areas, providing them with a feasible solution to mitigate such concerns effectively. This is a revolutionary application designed to make your travel experience seamless and convenient. Combining the power of Google Maps with features inspired by popular ride-sharing apps like Ola, it helps us discover nearby shops and reach them effortlessly during your journey.

USING OF BIG DATA TECHNOLOGIES IN VEHICLE INDUSTRY

This work contains information about some aspects of the use of Big Data technologies in the transport sector, such as predictive analysis of vehicle breakdowns, issues of delivering large amounts of data from rolling stock. Some options for directions for further research on the use of Big Data technologies are considered. One of the problems of using Big Data technologies in the field of transport is the problem of delivering large amounts of information to data processing centers. If for urban transport, where coverage by networks of mobile cellular operators approaches 100%, there are no problems in sending large amounts of data (data can be accumulated on board the vehicle and transmitted at other times, for example, when the vehicle is in the park), then for this transport, such as trucks, trains, cargo planes, there is a certain problem in delivering large amounts of data. Keywords: Big Data technologies, vehicle industry, collecting data, DFM, risks.

Drive Time Vehicle Breakdown Assistance

Drive Time Vehicle Breakdown Assistance is a user-centric platform dedicated to providing swift and efficient assistance to drivers experiencing vehicle issues. Through seamless chatbot integration, users can easily connect with mechanics in their vicinity, ensuring prompt resolution of breakdowns tailored to their vehicle type and location. Additionally, the platform offers a comprehensive tutorial section empowering users to tackle common issues independently, fostering a sense of self-sufficiency. Moreover, users can seamlessly search for nearby petrol stations from their location, ensuring they have access to essential services during their journeys. In summary, Drive Time Vehicle Breakdown Assistance is more than just a platform—it's a comprehensive solution designed to provide peace of mind to drivers, ensuring safer and more convenient journeys on the road. Keywords- assistance, breakdowns, chatbot, drivers, efficient, independence, mechanics, petrol, platform, tutorial

Dynamic, fair, and efficient routing for cooperative autonomous vehicle fleets

This paper addresses challenges in agricultural cooperative autonomous fleet routing through the proposition, modeling, and resolution of the Dynamic Vehicle Routing Problem with Fair Profits and Time Windows (DVRP-FPTW). The aim is to dynamically optimize routes for a vehicle fleet serving tasks within assigned time windows, emphasizing fair and efficient solutions. Our DVRP-FPTW accommodates unforeseen events like task modifications or vehicle breakdowns, ensuring adherence to task demand, vehicle capacities, and autonomies. The proposed model incorporates mandatory and optional tasks, including optional ones in operational vehicle routes if not compromising the vehicles’ profits. Including asynchronous and distributed column generation heuristics, the proposed Multi-Agent-based architecture DIMASA for the DVRP-FPTW dynamically adapts to unforeseen events. Systematic Egalitarian social welfare optimization is used to iteratively maximize the profit of the least profitable vehicle, prioritizing fairness across the fleet in light of unforeseen events. This improves upon existing dynamic and multi-period VRP models that rely on prior knowledge of demand changes. Our approach allows vehicle agents to maintain privacy while sharing minimal local data with a fleet coordinator agent. We propose publicly available benchmark instances for both static and dynamic VRP-FPTW. Simulation results demonstrate the effectiveness of our DVRP-FPTW model and our multi-agent system solution approach in coordinating large, dynamically evolving cooperative autonomous fleets fairly and efficiently in close to real-time.

Bus Rescheduling for Long-Term Benefits: An Integrated Model Focusing on Service Capability and Regularity

Unplanned disruptions, such as vehicle breakdowns, in a public transportation system can lead to severe delays and even service interruptions, preventing the successful implementation of subsequent plans and the overall stability of transit services. A common solution to address such issues is implementing a bus bridging service using an experience-based response strategy, involving the deployment of spare buses to continue affected services. However, with this approach, it becomes impractical and challenging to generate a feasible and rational rescheduling scheme for the remaining transit services when spare buses are insufficient or widespread disruptions occur. In response to this challenge, we propose an innovative model that integrates service capability and regularity, aiming to minimize rescheduling costs through timetable adjustments and scheduling reassignments. We apply dynamic programming to comprehensively consider the hysteresis effects of disruptions and achieve a long-term optimal rescheduling scheme. To efficiently solve the proposed model, the large neighborhood search algorithm is improved by incorporating operational rules. Finally, several experiments are conducted under an actual transit operation scenario in Shenzhen. The results demonstrate that our method significantly reduces trip cancellations and, simultaneously, diminishes the increase in the departure interval resulting from the adjusted schedule by 23.27%.

Classification of Factors Used to Predict Vehicle Break down in Commercial Vehicles

Prediction of vehicle breakdowns in commercial vehicles is of utmost importance to ensure the safety, reliability, and cost-effectivenessof road transport. In today's fast-paced and competitive business landscape, the smooth operation of commercialvehicles is crucial for ensuring efficient logistics and supply chain management. Unplanned breakdowns of commercial vehiclescan lead to significant financial losses, delays in delivery schedules, and potential damage to the reputation of the transportation companies. Commercial vehicle breakdowns pose significant challenges to both fleet operators and the broader transportation industry. The unexpected failure of a commercial vehicle can result in substantial costs, operational disruptions, and safetyhazards. In light of these considerations, the development of effective breakdown prediction models hasbecome an essentialendeavor.Predicting when andwhy abreakdownmight occurnotonly allows for proactive maintenance but also minimizes the economic and safety risksassociated withbreakdowns.©2024 STAIQC.Allrightsreserved

Understanding the performance and challenges of solid waste management in an emerging megacity: Insights from the developing world

Solid waste management has been a cavilling issue in Ghana, especially in Kumasi. Thus, this study examines the challenges and recommendations for solid waste management in the Oforikrom Municipality. Data was obtained from 450 respondents from low, middle- and high-income classes using structured questionnaires and interviews were conducted with 6 waste management stakeholders and 50 market venders. Generally, waste management in the area was described as moderate based on the SWAi rating of 50.8 %. While collection and transportation received high ratings of 71 % and 82 % respectively, challenges are apparent in waste segregation (14 %) and disposal (21 %), marked as critically poor and poor, respectively. The overall moderate rating (50.8 %) underscores a mixed performance, signalling the necessity for enhancing storage conditions (36 %) as well. The study showed that occupation (Chi-Square = 0.893, p = 0.029), income (Chi-Square = 0.933, p = 0.021), and satisfaction with waste management services (p = 0.026) displayed notable effects, highlighting their importance in shaping waste management practices. Data from the respondents revealed inadequate practices due to vehicle breakdowns, high transport costs, and funding limitations. Nevertheless, 59.1 % of households expressed willingness to pay for improved waste collection. The dominant waste types were food waste (40 %) and plastics (5.5 %). Disturbingly, 80 % of the households lacked knowledge about waste disposal methods. The study recommends strengthening education and awareness of waste management to residents, improvement of access routes to households and waste disposal sites, and transport of waste should be done at night to ease traffic congestion.

Algorithm for a simulation model for the selection of a rational type of vans on technological routes of the transport and recycling system for recycling of a metallurgical enterprise

The article presents an algorithm of the simulation model for selecting the rational type of trucks on the technological routes of the transport and production system of waste transportation in the conditions of a metallurgical enterprise. The study was conducted on the basis of formalized models and queuing systems theory. In the simulation, a discrete-event model of a closed queuing system was chosen as the basic model. In this model, cars are represented as requests that go through the following phases of service: loading at the temporary waste storage dump; movement to the unloading point (crushing and sorting complex); unloading raw materials to the crushing and sorting complex; returning to the loading point along the same route; servicing of vehicle breakdowns. The following data were used to build the simulation model through statistical studies of the transportation process on technological routes: vehicle loading time, vehicle unloading time, and time determined by the duration of vehicle failure. When constructing the algorithm of the simulation model, the duration of one experiment and the number of simulation experiments were determined using the methods of mathematical statistics and the theory of experiment planning. The modeling process begins with the input of the following initial data: the number of vehicle units, the average vehicle travel time, the current amount of raw materials in the crushing and sorting complex, the vehicle carrying capacity, the intensity of raw material supply to the crushing and sorting complex, the vehicle unloading time, the intensity of minor vehicle breakdowns, and the intensity of vehicle repair. The algorithm is built in accordance with the principles of special states and meets the requirements for discrete-event models. As a result of the algorithm development, it will be possible to determine the required number (types) of vehicles necessary to ensure the smooth functioning of this transport and production system, to determine the idle time coefficient and the coefficient of time losses due to technological delays of vehicles.
 Key words: modeling, simulation model, dump truck, carrying capacity, metallurgical slag, crushing and screening equipment.

High-tech Advanced Roadside Vehicle Breakdown and Accidental Service System

The High-tech Advanced Roadside Vehicle Breakdown and Accidental Service System is an innovative solution designed to enhance the efficiency and effectiveness of roadside assistance and accident response services. High-tech advanced Roadside Vehicle Breakdown And Accidental service system Application is a mobile app designed to provide quick and efficient roadside assistance to users experiencing vehicle breakdowns. The application will be built using Android Studio with Java as the primary programming language, and it will leverage Firebase Database for real-time data storage and retrieval. Additionally, a user-friendly mobile application allows users to request assistance, track progress, and access relevant information. With a built-in data analytic module, the system collects and analyzes data to optimize performance. the High-tech Advanced Roadside Vehicle Breakdown and Accidental Service System aims to revolutionize the industry by providing faster, more efficient, and customer -centric service

Implementation of an Automobile Breakdown Service Provider (ABSP) Model

The increasing frequency of vehicle breakdowns presents a challenge for automobile drivers, especially when faced with unexpected breakdowns in unfamiliar locations. This article addresses the need for an effective solution by proposing and implementing an Automobile Breakdown Service Provider (ABSP) model. Vehicle breakdowns, caused by factors such as poor road conditions, battery failure, or mechanical issues, often require immediate attention from certified artisans. The ABSP model aims to enhance the breakdown assistance process by incorporating driver feedback through ratings and reviews of artisan services, ensuring reliability and trustworthiness. To develop the ABSP model, limitations of existing Road Side Assistance (RoSAS) models were analyzed and taken into account. The iterative process model was employed for implementation, allowing early software versions to accommodate evolving requirements. The system's frontend utilized Hypertext Markup Language (HTML) and Cascading Style Sheet (CSS), while the mobile application was developed using Flutter—a versatile Dart-based framework for cross-platform mobile app creation. The backend was supported by the Laravel Framework, based on Hypertext Preprocessor (PHP), with MySQL serving as the relational database for record storage. The ABSP model's significance lies in its ability to provide drivers with verified and rated artisans, ensuring efficient breakdown resolution, payment automation, and minimizing the challenges associated with breakdowns in unfamiliar or dangerous locations. This article offers insights into the design and implementation of the ABSP model, contributing to enhanced reliability and convenience in addressing automobile breakdowns.

Authenticity, and Approval Framework for Bus Transportation Based on Blockchain 2.0 Technology

The intelligent transport system (ITS) has transformed urban transportation, enhancing daily commutes with services like congestion management, vehicle crash prevention, traffic control, roadside safety, breakdown assistance, ticket booking, vehicle registration, and insurance. However, in urban bus transportation, the ITS faces security threats, such as data forgery and manipulation. To counter these challenges, a blockchain-based framework for bus transportation approval is proposed, ensuring data integrity and security. The framework’s performance is evaluated based on processing time, central processing unit (CPU), graphical processing unit (GPU), cloud usage, and memory consumption, and compared to Ethereum and Aurora testnet, in terms of gas cost, security, and performance. Stochastic algorithms, including the genetic algorithm and Tabu search, are used for time complexity analysis, to obtain an optimized solution. The decision-making trial and evaluation laboratory (DEMATEL) analysis is also performed to assess factors like transaction costs, execution time, memory consumption, and security. The results show that execution time, memory consumption, and processing time are crucial, while transaction cost, reliability, and transparency positively impact the system’s effectiveness. By reducing the risk of false data presentation and ensuring accurate records, the proposed framework contributes to a more efficient and reliable transportation system.

A New Model for Determining the Price of Product Distribution Based on Fuzzy Logic

Background: Distribution is a very important part of logistics and an activity that is present in every area today. One of the basic problems in distribution is how to correctly determine its price. For this reason, this paper presents a model created to determine the price of the product distribution service. Methods: The model first determines the base of the distribution price, which consists of a fixed and a variable part. The fixed part depends on the distance traveled, and the variable part is defined by fuzzy logic. To determine the variable part, a fuzzy logic system was created that depends on four input variables: inaccessibility of the client’s location, driving time, quantity of goods, and unloading time. The reason for applying fuzzy logic is its ability to set the distribution price for each client individually, without generalization. Certain criteria that affect the distribution price such as type of vehicle, quality of service, and type of goods, which could not be represented by fuzzy numbers, were considered as additional corrective factors. Results: The model was tested on hypothetical examples created by the authors from this field and on examples of company that provide distribution services. In the case study, a comparison was made between the distribution price obtained by applying the created fuzzy logic model and the price defined by the model used by the company "X". Conclusions: The model created in this way enables easy adaptation to constant changes in the prices of oil derivatives due to the COVID-19 pandemic and the war but also considers various unpredictable circumstances that may occur during delivery such as roadworks, crowds, vehicle breakdown, location inaccessibility due to bad weather, etc.

Vehicle re-routing under disruption in cross-dock network with time constraints

This study expands on the investigation of the vehicle routing problem with cross-dock (VRPCD) by incorporating disruption in a network with suppliers, customers, and a single cross-dock. It is assumed that the disruption (e.g., traffic accident or mechanical failure) impacts the scheduled pickup times of vehicles carrying freight; hence, pickup or delivery is affected by late vehicle arrivals to suppliers, cross-docks, and customers as well as increased transportation cost for the carrier. To help decision makers mitigate the impact of this type of disruption, mixed-integer linear programs (MILPs) are developed to model VRPCD with time-window constraints under both normal and disrupted conditions that will quantify the impact of disruption. The Golden Ball metaheuristic is adapted to provide an optimal or near-optimal solution of the MILPs in a short time period. To demonstrate the effectiveness of the proposed models and algorithms, numerical experiments are performed on hypothetical networks containing a realistic number of pickup and delivery locations. Results from numerical experiments and ANOVA analysis showed that: 1) the cross-dock is able to cope with the disruption when the number of disrupted nodes is small, 2) early breakdown of an inbound vehicle with fewer nodes on its routes causes smaller service delays, 3) as the number of disrupted nodes increases, it is advantageous to reroute outbound vehicles, and 4) when the breakdown occurs earlier in the planning horizon, it is better to reroute both inbound and outbound vehicles whereas only outbound vehicles should be rerouted when the breakdown happens later in the day.

Intelligent Vehicle Management: Harnessing Emerging Technologies for Efficiency and Sustainability

Vehicle Management System provides useful features for the users (drivers) to make drive easy and use application smoothly without any friction. In today’s fast-growing digital world of internet, we see often see many conflicts and disputes based on buying and selling old vehicle cause by the lack of transparency. Also, there is huge traffic in metro cities and not able to find parking areas and get fined. So, people are not able to find the available area and if available only some types vehicles can be parked like bikes and cars. There are such more problem related vehicles that exists in real world like connecting with mechanic for breakdown of vehicle. To Solve some of these problems we are intended to make a Vehicle system that helps an drive to make drive easy and reduce dispute.

Need Analysis of English for Specific Purposes at SMK 01 Bombana

The aim of this study is to analyze the needs of students for English for Specific Purposes (ESP) and to find out how to learn ESP in accordance with TKRO department at SMK 01 Bombana. The respondents of this study were grade 12 TKRO students with a total of 35 students. This study used the Needs Analysis theory of Hutchison and Waters (1987), which divided it into 2 namely, target needs and learning needs. The instruments used to collect data were questionnaires and a following up interview. The results of this study show that students TKRO department need ESP to support their future work, with the most needed language skills being speaking and reading. Students need speaking sksills to do presentations in English (about vehicle breakdowns, vehicle repairs, how tools work or inventions) and need reading skills for most students need the skills to help understand the reading in the automotive tool manual (instructions). The final result of this research can be an illustration for English teacher to create syllabus and materials relevant to TKRO department. In conclution, the TKRO student in SMK 01 Bombana needs speaking skill and reading skill in future job.

Disruption recovery for the pickup and delivery problem with time windows—A scenario-based approach for online food delivery

Recently, the pickup and delivery problem has attracted increasing attention due to its applications in online food delivery services. At the same time, unforeseen events, such as vehicle breakdowns, traffic jam, and service time changes, often lead to the delay of delivery services. This paper defines the disruption recovery problem for the pickup and delivery problem with time windows (DR-PDPTW) and presents a scenario-based approach to solve the problem in a computationally efficient way. The approach starts with pre-disruption preparation that generates disruption scenarios and corresponding candidate recovery solutions. Once a disruption occurs, the approach will first check if recovery efforts are necessary based on the magnitude of delays caused by the disruption. If such delays are not acceptable, the approach will move to the post-disruption response stage to match the disruption with an already generated disruption scenario. Then corresponding candidate recovery solutions will be adjusted based on the actual disruption and executed. Computation experiments demonstrate the quality and efficiency of the proposed approach. This study can help to provide real-time decision support for disruption management in online food delivery services.