Service Vehicles Research Articles

Research into the Longitudinal Loading of an Improved Load-Bearing Structure of a Flat Car for Container Transportation

Container transport is one of the most promising modes of international freight transport. Railway container transport is mainly carried out using flat cars. Container cars can be damaged under the most unfavorable operating load conditions of a 1520 mm track gauge, i.e., shunting collisions. In this context, an improvement to the supporting structure of flat cars is proposed to ensure their strength, involving the installation of special superstructures in their cantilever parts to limit the movement of the containers. The choice of the superstructure profiles was made on the basis of the section modulus of their components. Mathematical modeling of the dynamic loading of a flat car with containers in the event of a shunting collision was carried out. The determined value of acceleration was taken into account in the calculation of the strength of the load-bearing structure of the flat car. It was found that the maximum stresses were 24% lower than the allowable stresses. Therefore, the strength condition of the flat car was met. The results of this study will contribute to reducing damage to container transport vehicles in service, to the formulation of recommendations for their construction and to an increase in their profitability, including in international transport.

The Resemiotisation and Intertextuality of Multimodal Discourses in Linguistic Landscape of Public Service Vehicles in Lusaka, Zambia

Using resemiotisation and intertextuality as analytical tools in the broader theoretical conexts of linguistic landscapes and semiotic studies, this article accounts for the diverse and heavily saturated multimodal discourses emplaced on public service vehicles in Lusaka, Zambia (South-Central Africa). As its locus, the study wishes to to unearth the textual and sociocultural sources of emplaced discourses privileging local materialities, agency, and voice. To this end, the article reveals that the multimodal discourses on public service vehicles bring religion into the spotlight, particularly Christianity, as a sociocultural reality of social actors. It is shown that the emplaced multimodal discourses are inescapably related to other texts and narratives predominantly associated with Zambias’ christian religious underpinnings. In this way, the article concludes that resemiotisation and intertextuality are at play in the textual trajectory of discourses seen on public service vehicles in Lusaka, Zambia.

Should Charging Stations Provide Service for Plug-In Hybrid Electric Vehicles During Holidays?

The development of the new energy vehicle (NEV) market in China has promoted the sustainability of the automotive industry, but has also brought pressures to NEV charging infrastructure. This paper aims to determine the strategic role of charging stations, particularly on whether they should provide service for plug-in hybrid electric vehicles (PHEVs) in the highway service area during peak holidays. Firstly, the charging service resource allocation for a charging station that provides services for both electronic vehicles (EVs) and PHEVs is studied. Secondly, different queueing disciplines are compared. At last, a comparison between scenarios where charging services are limited to EVs and those where services extend to both EVs and PHEVs is conducted. A queueing system considering customer balking and reneging is developed. The impacts of parameters, such as the NEV arrival rate and patience degree of different NEV drivers, on the optimal allocation plan, profit, and comparison results are discussed. The main conclusions are as follows: (1) If the EV arrival rate is greater than the charging service rate, the charging station should not provide charging services for PHEVs. Providing service only for EVs derives more revenues and profits and results in a shorter waiting queue. Conversely, if the total arrival rate of NEVs (including EVs and PHEVs) is lower than the charging service rate, then the charging station should also serve PHEVs. (2) If providing service for PHEVs, a mixed queueing discipline should be applied when the total arrival rate approximates the service rate. When the total NEV arrival rate is significantly lower than the charging service rate, the separate queueing discipline should be adopted. (3) When applying a separate queueing discipline, if a certain type of NEV has a higher arrival rate and the drivers exhibit greater patience, then more charging resources should be allocated to this type of NEV. If the charging service is less busy, the more patient the drivers are, the less service resources should be allocated to them, whereas, during peak times, the more patient the drivers are, the more service resources should be allocated to them.

What Drives and Inhibits Consumers from Adopting Electric Two Wheelers: A Behavioural Reasoning Theory Perspective

This study contributes to the body of work on electric vehicle adoption by going beyond traditional frameworks like the Technology Acceptance Model, the Theory of Reasoned Action and the Theory of Planned Behaviour. It presents a comprehensive framework that highlights both the drivers and barriers specific to Tier 2 cities, a significant market for two wheelers in India. Although two wheelers are the preferred mode of transport in India, there has been limited research on the adoption of electric two-wheelers (E2Ws) and their role in achieving decarbonization goals. This study aims to assess the adoption of E2Ws in Tier 2 cities across India, which represents a significant market for two wheelers. To explore this, the study employs a qualitative approach using a theoretical framework to understand the reasons behind the adoption and non-adoption of E2Ws in Tier 2 cities. Eighty-nine interviews were conducted in different Tier 2 cities across four northern states. The results identified several key reasons for adoption, including monetary savings, non-financial incentives, driving pleasure, ease of use for women and senior citizens, suitability for local travel, and a pro-environmental approach. Conversely, the barriers to adoption included high ownership costs, negative motives, inadequate vehicle space, poor repair and service infrastructure, distrust, resale concerns, and negative review consensus. From a managerial perspective, this study provides strategic insights for marketers, outlining ways to promote the mass adoption of E2Ws by understanding and addressing key motivators and inhibitors.

Measuring the mental workload and identifying stress factors among public transportation drivers in Cikande, Indonesia

Public transportation is vital in providing access to important services and job opportunities. Road conditions such as congestion, deposit targets, competition between drivers, noise, and vehicle speed can cause mental stress in drivers. This study aimed to measure the mental burden of public transportation drivers in the Cikande area of Indonesia. The study involved 30 drivers who were selected using stratified random sampling. The mental load was measured using NASA-TLX, and the results showed that the mental workload of red public transportation drivers was high and very high, with mental demand being the highest dimension. The mental workload of red and white public transportation drivers was high and rather high, with the highest dimension being frustration level. The study found that internal and external factors influenced the mental workload of public transportation drivers. External factors include the environment, traffic, customer service, deposit targets, and old vehicle conditions. Internal factors include age, emotional exhaustion, and driver saturation level. This study provides insight into the mental burden experienced by public transportation drivers in the Cikande area and the factors that contribute to mental stress.

Toward real-time operations of modular-vehicle transit services: From rolling horizon control to learning-based approach

Recent technological advancements have opened doors for real-time adjustments and controls during public transport operations. In particular, the introduction of modular vehicles has the potential to significantly enhance public transit service quality. This innovative public transit service with modular vehicles, characterized by its flexible schedules and vehicle formations, allows for the dynamic management of transit capacity to meet the fluctuating passenger demands. This paper proposes to schedule the flexible modular-vehicle transit service in real time considering the varying demands. To jointly optimize the service schedule and vehicle formations, we propose the rolling horizon control approach to decompose the complex problem into subproblems that can be solved efficiently during the process. On top of this, we introduce a learning-based optimization proxy to streamline the optimization process within the rolling horizon framework, enabling near-optimal decisions to be made with minimal execution time without directly solving the optimization problem. Through numerical studies, we demonstrate the effectiveness and efficiency of the proposed methods in terms of solution quality and efficiency. Furthermore, our case studies show that modular vehicles can adapt to the changing demand and effectively reduce the total costs in the transit system.

The multi-depot pickup and delivery vehicle routing problem with time windows and dynamic demands

The rapid development of the urban logistics recycling industry, combined with the complexity of the pickup and delivery networks, has created a surge in dynamic customer demands and exacerbated the difficulty of logistics resource sharing. Accordingly, this work focuses on a multi-depot pickup and delivery vehicle routing problem with time windows and dynamic demands, which incorporates resource sharing. A bi-objective mathematical model is formulated to minimize the total operating cost and number of vehicles. A three-dimensional affinity propagation clustering and an adaptive nondominated sorting genetic algorithm-II are combined to find Pareto optimal solutions. A dynamic demand insertion strategy is proposed to determine the vehicle service sequences for dynamic situations. Combined with an elite iteration mechanism to prevent the proposed algorithm from falling into search stagnation and improve the convergence performance. The superiority of the proposed algorithm is verified by comparing with CPLEX solver (i.e., ILOG CPLEX Optimization Studio 12.10), multi-objective ant colony optimization, multi-objective particle swarm optimization, multi-objective evolutionary algorithm, multi-objective genetic algorithm, and decomposition-based multi-objective evolutionary algorithm with tabu search. Besides, the proposed model and algorithm are tested by a real-world case study in Chongqing city, China, and the further analysis indicates that significant improvement can be achieved. Furthermore, by incorporating the recognition and prediction techniques of artificial intelligence on dynamic demand data, the proposed approach can realize the self-optimization of multi-depot vehicle routes and the precise allocation of logistics resources in dynamic environments. This study is conducive to the construction of a digitally-intelligent urban logistics system.

Application of the Process Mapping for Identification of Waste for Sustainable Performance Improvement in the Service Processes

This paper examines the pivotal role of high-quality aftersales service in maintaining global automotive industry competitiveness and sustainability. It presents the methodology for utilizing lean principles in sustainable performance improvement by identifying and eliminating waste in aftersales processes. The approach is exemplified through a case study in road freight vehicle service and maintenance using process mapping. The methodology involves developing a comprehensive process map, analyzing current inefficiencies, and proposing improvement measures. The methodology enhances operational efficiency and contributes to sustainable performance in terms of economic, environmental, and social factors. The methodology is generalized and outlines successful improvement phases and sub-steps.

Peer-to-Peer Transactive Energy Trading of Smart Homes/Buildings Contributed by A Cloud Energy Storage System

This paper presents a model for transactive energy management within microgrids (MGs) that include smart homes and buildings. The model focuses on peer-to-peer (P2P) transactive energy management among these homes, establishing a collaborative use of a cloud energy storage system (CESS) to reduce daily energy costs for both smart homes and MGs. This research assesses how smart homes and buildings can effectively utilize CESS while implementing P2P transactive energy management. Additionally, it explores the potential of a solar rooftop parking lot facility that offers charging and discharging services for plug-in electric vehicles (PEVs) within the MG. Controllable and non-controllable appliances, along with air conditioning (AC) systems, are managed by a home energy management (HEM) system to optimize energy interactions within daily scheduling. A linear mathematical framework is developed across three scenarios and solved using General Algebraic Modeling System (GAMS 24.1.2) software for optimization. The developed model investigates the operational impacts and optimization opportunities of CESS within smart homes and MGs. It also develops a transactive energy framework in a P2P energy trading market embedded with CESS and analyzes the cost-effectiveness and arbitrage driven by CESS integration. The results of the comparative analysis reveal that integrating CESS within the P2P transactive framework not only opens up further technical opportunities but also significantly reduces MG energy costs from $55.01 to $48.64, achieving an 11.57% improvement. Results are further discussed.

Customers’ reuse intention to autonomous delivery vehicles in terminal delivery service: A valence theory perspective

Autonomous delivery vehicles (ADVs), as a new tool in terminal delivery, are currently used extensively. However, for the permanent success of the ADV industry, logistics providers need to understand the influencing mechanism of consumers' reuse intention of ADVs. Therefore, this research uses valence theory as basis in analyzing the elements and mechanisms affecting consumers’ reuse intention of ADVs. Survey data were assembled from 550 ADV consumers in China through online questionnaires, and partial least squares structural equation model was used as a tool for data analysis. Findings indicate that convenience and hedonic value can enhance the perceived value of ADVs. Perceived value can positively affect reuse intention through the attitude toward using ADVs, whereas perceived cost negatively affects the reuse intention through the attitude toward using ADVs. The discussion section of this paper summarizes the results and implications and provides valuable suggestions for logistics providers and developers.

Assessment of longitudinal load spectrum characteristics and structural fatigue damage of metro vehicle body in service

Aiming at the structural integrity requirements of service vehicles, there is an urgent need to construct a set of analytical methods based on service load characterization to realize the life assessment of the critical weak regions of the vehicle body. This study measured the longitudinal load spectrum of a metro vehicle body under a typical service line using a calibrated coupler and traction bar. Based on the signal characteristics of the longitudinal loads, a dynamic load feature decomposition method is proposed to decompose the longitudinal load features into trend and fluctuation signals to reflect the overall and local laws. The longitudinal load transfer characteristics of the vehicle body under traction, braking, linear, and curved conditions are innovatively analyzed, and a longitudinal load distribution ratio coefficient with generality is proposed as the input of effective service load. The service stress spectrum of the vital points of the vehicle body is constructed, which can more comprehensively and realistically respond to the service stress state of the vehicle body compared with the standard design loads, which further improves the accuracy of the structural integrity assessment.

Delivering a mental health response vehicle service in Wales: a pilot initiative.

NHS emergency services, including ambulance services and emergency departments (EDs), are under considerable pressure due, in part, to the lack of availability of alternative healthcare services. People with mental health issues often contact ambulance 999 services when they cannot access the care they require from other sources. Welsh Ambulance Services NHS Trust (WAST) employs mental health professionals in its 999 call centres to provide remote mental health triage and support. While this has been effective in reducing ambulance conveyance to EDs, many patients still require a face-to-face assessment. To address this, WAST explored the option of providing a mental health response vehicle (MHRV) service, which has been shown to be effective in some ambulance trusts in England. This article gives an overview of a pilot MHRV service that was delivered by WAST across the Aneurin Bevan University Health Board locality in south-east Wales in between January and March 2024. Results suggest that the MHRV service can reduce ED conveyance rates and potentially provide cost savings for WAST and the wider NHS in Wales.

Optimizing task assignment and routing operations with a heterogeneous fleet of unmanned aerial vehicles for emergency healthcare services

This paper studies the optimization of task assignment and pickup and delivery operations using a heterogeneous fleet of unmanned aerial vehicles (UAVs). We specifically address the distribution of emergency medical supplies, including medications, vaccines, and essential medical aid, as well as the collection of biological blood samples for testing and analysis. Unique challenges, such as supply shortages, time windows, and geographical considerations, are explicitly taken into account. The problem is first formulated as a mixed-integer linear programming model aimed at maximizing the total profit derived from the execution of a set of emergency healthcare pickup and delivery tasks. An enhanced Q-learning-based adaptive large neighborhood search (QALNS) is proposed for large-scale benchmark instances. QALNS exhibits a superior performance on benchmark instances. It also improves the quality of the solutions on average by 5.49% and 6.86% compared to the Gurobi solver and a state-of-the-art adaptive large neighborhood search algorithm, respectively. Sensitivity analyses are performed on critical factors contributing to the performance of the QALNS algorithm, such as the learning rate and the discount indicator. Finally, we provide managerial insights on the use of the fleet of UAVs and the design of the network.

Quantitative evaluation of corrugation severity by using instrumented wheelset

Accurate evaluation of corrugation severity is essential for timely rail maintenance to prevent potential hazards. This paper aims at the excitation characteristics of corrugation and presents a study on the evaluation method using wheel-rail vertical force (WRVF). First, a 3D wheel-rail dynamic model is established by the parameters of service vehicles and track in China’s high-speed railway, corrugated rail was finely modelled with the consideration of out-of-roundness and random track short irregularity. The model was validated with measured data come from instrumented wheelset in time and frequency domain, the stability and dynamic response of the model are studied numerically to explore the excitation characteristics of corrugation. Then, the variation of WRVF with depth and wavelength respectively was discussed, the mapping relationship between the 95th percentile maximum of the WRVF and the corrugation wavelength is revealed, the influences of the natural frequency and contact behavior of the wheel-rail system on the mapping relationship were analyzed. Finally, the corrugation severity index (Csi) is introduced to quantify the degree of rail damage. The applicability of Csi was tested on 65 sets of corrugated sections on high-speed railway, and the results of field measurement showed that the hit rate of Csi in evaluating the severity of corrugation is 93.8%, indicating that the proposed method has a good performance in actual detection. Thus, Csi can provide a scientific reference for the quantitative evaluation of corrugation severity and decision-making for rail grinding in high-speed railway.

Factors Influencing Sustained Use of Shared E-Scooter Services in Urban Taiwan

This study investigates the factors that drive users to sustain their usage of shared electric scooter (e-scooter) services in Taiwan, distinguishing itself from the conventional focus on predicting consumers’ initial adoption and behavioural intentions. It employs subjective rating questions, incorporating constructs related to user acceptance, attitudes and user experience (UX). Through hierarchical regression analysis of quantitative survey data, the study identifies key factors such as users’ modes of transportation, environmental attitudes, acceptance of shared services, attitudes towards private scooters, UX, total usage instances and age. However, reliance on private scooters as a mode of transportation and frequent usage of shared e-scooters negatively impact the sustained usage of these services. The research further highlights early development challenges in shared vehicle services, including concerns over personal data security, user-unfriendly system designs, lack of convenience, inadequate parking infrastructure and ineffective financial incentives. Based on these findings, the study provides recommendations for service providers and government entities to enhance service design and proactively address these challenges. Implementing these recommendations is expected to mitigate the impact of these challenges and potentially improve user acceptance, UX, and the overall sustainability of shared vehicle services.

Consistency in Subjective Judgments of Service Vehicle Type Based On Vehicle and Flashing Light Colors

The present study focused on the consistency in perceiving the intended function of a simulated service vehicle when its color, the color of its flashing lights, and its flashing light pattern varied. Tests were conducted during the day and at night. Participants driving along a test track were presented with a red or yellow vehicle equipped with either red or yellow flashing lights. Although driving speed differed only between ambient lighting conditions (daytime and nighttime), consistency in the participants’ perceptions of the simulated situation (emergency or nonemergency) was higher when the color of the vehicle was the same as the flashing lights. Ambient lighting conditions also significantly influenced participants’ judgments of each situation because the color of the vehicle was more apparent during the day than during the night with only headlight illumination on the vehicle. The flash pattern (faster or slower) had a negligible impact on participants’ perception of the simulated situation. These results reinforce previous findings that coordinating the colors of the flashing lights and the vehicle better informs drivers about the situations they encounter along the road, improving the safety of emergency responders and other service workers.

Tourism Recommendation Algorithm Based on the Mobile Intelligent Connected Vehicle Service Platform

As to the problems in current tourism recommendation, this paper proposes a tourism recommendation algorithm based on the mobile ICV service platform. Firstly, the ICV service system for the Point of Interest (POI) searching and route recommendation is designed. Secondly, the recommendation service model is set up from two aspects, namely the tourism POI clustering algorithm and the tourism POI searching and route recommendation algorithm. In the aspect of symmetrical-based matching features, the clustered POIs are matched with the tourists’ interests, and the POIs in the neighborhood of the ICV dynamic locations are searched. Then, a POI recommendation algorithm based on the tourists’ interests is constructed, and the POIs that best match the symmetrical interests of the tourists within the dynamic buffer zones of ICV are confirmed. Based on the recommended POIs, the ICV guidance route algorithm is constructed. The experiment verifies the advantages of the proposed algorithm on the aspect of the POI matching tourists’ interests, algorithm stability, traveling time cost, traveling distance cost and computational complexity. As to the iterative sum and the iterative sum average of the POI matching function values, the proposed algorithm has a performance improvement of at least 20.2% and a stability improvement of at least 20.5% compared to the randomly selected POIs in matching tourists’ interests. As to the cost of the guidance routes, the proposed algorithm reduces the average cost by 19.6% compared to the other suboptimal routes. Compared with the control group algorithms, the proposed algorithm is superior in terms of route cost, with an average cost reduction of 13.8% for the output routes compared to the control group. Also, the proposed algorithm is superior in terms of route cost compared to the control group recommendation algorithms, with an average cost reduction of 11.2%.

Integrated development plan strategies for service delivery in Nelson Mandela Metropolitan Municipality

Background: Following the end of apartheid in 1994, the democratic government recognised the importance of local government as a key vehicle for service delivery.Aim: This article examined the effectiveness of the integrated development plan (IDP) strategies of the Nelson Mandela Metropolitan Municipality (NMMM) as a public service delivery tool.Setting: In South Africa, poor service delivery has remained a challenge. This has been attributed to the challenge of transparency and accountability. Thus, the lack of access to basic needs is more profound at the local government level. While urban centres have access to certain basic facilities, rural communities such as Walmer and Motherwell townships remain underdeveloped.Methods: The study used a qualitative research design for data collection and analysis. Thirty participants were purposively selected among municipal officials, ward councillors and community members for semi-structured interviews. Thematic data analysis was used for the analysis of data.Results: Despite the IDP’s well-structured strategic framework, various challenges, such as insufficient community participation, inadequate resource allocation and a lack of essential planning skills among officials hindered its effective implementation.Conclusion: The study concluded that for the IDP to achieve its aims, its implementation should be evidence-based and responsive to community needs. Effective service delivery requires a fundamental transformation in municipal leadership and public participation.Contribution: The article presents the challenge of public service delivery within the context of the IDP strategies in a specific municipality. It serves as a signpost for understanding the implementation of the IDP as a public service delivery strategy.

Enhancing Federated Learning in Heterogeneous Internet of Vehicles: A Collaborative Training Approach

The current Internet of Vehicles (IoV) faces significant challenges related to resource heterogeneity, which adversely impacts the convergence speed and accuracy of federated learning models. Existing studies have not adequately addressed the problem of resource-constrained vehicles that slow down the federated learning process particularly under conditions of high mobility. To tackle this issue, we propose a model partition collaborative training mechanism that decomposes training tasks for resource-constrained vehicles while retaining the original data locally. By offloading complex computational tasks to nearby service vehicles, this approach effectively accelerates the slow training speed of resource-limited vehicles. Additionally, we introduce an optimal matching method for collaborative service vehicles. By analyzing common paths and time delays, we match service vehicles with similar routes and superior performance within mobile service vehicle clusters to provide effective collaborative training services. This method maximizes training efficiency and mitigates the negative effects of vehicle mobility on collaborative training. Simulation experiments demonstrate that compared to benchmark methods, our approach reduces the impact of mobility on collaboration, achieving large improvements in the training speed and the convergence time of federated learning.

PELATIHAN SERVIS RINGAN KENDARAAN SEPEDA MOTOR BAGI MASYARAKAT DESA RIDOGALIH

Motorbikes are a means of transportation that is often used in daily activities, the development of increasingly sophisticated technology has begun to be combined with the help of electronic control circuits such as injection systems to control combustion in the motorcycle combustion chamber or indicators to show hot engine temperatures that make it easier for motorcycle owners to carry out vehicle maintenance. Therefore, due to the lack of workshops or vehicle service services, here the author will share information about motorcycle maintenance that can be done by yourself to save costs and can be developed as a form of business, such as a workshop. With this lack of information, most people only use motorbikes for their daily needs and ignore motorcycle maintenance. Here the author will educate the community on how to maintain their two-wheeled vehicles in Citeureup 1 hamlet by socializing the importance of maintaining two-wheeled vehicles, training on maintaining two-wheeled vehicles, and evaluation to ensure that the community can maintain their own motorbikes. This program also has the aim that the people of Sirnajaya Village, Serang Baru District, Bekasi Regency are able to maintain their own motorbikes and can be developed as a form of business, namely a workshop. Based on the light service training, there are several impacts, among others can increase understanding related to light service procedures such as engine oil change, axle oil, CVT maintenance and replacement of front brake lining and understand about safety riding and have understood how to drive properly.