Search

The increasing volume of personal motorized vehicles (PMVs) in cities has become a serious issue leading to congestion, noise, air pollution and high land consumption. To ensure the sustainability of urban transportation, it is imperative to transition the current transportation paradigm toward a more sustainable state. Transitions within socio-technical systems often arise from niche innovation. Therefore, this paper pursues the technical optimization of such a niche innovation by applying a technical sustainability perspective on an innovative mobility and logistics concept within a case study. This case study is based on a centrally managed connected, automated, shared and electric (CASE) vehicle fleet which might replace PMV use in urban city centers of the future. The key technical system components of the envisioned mobility and logistics concept are analyzed and optimized with regard to economic, ecological and social sustainability dimensions to maximize the overall sustainability of the ecosystem. Specifically, this paper identifies key challenges and proposes possible solutions across the vehicle components as well as the orchestration of the vehicles' operations within the envisioned mobility and logistics concept. Thereby, the case study gives an example of how different engineering disciplines can contribute to different sustainability dimensions, highlighting the interdependences. Finally, the discussion concludes that the early integration of sustainability considerations in the technical optimization efforts of innovative transportation systems can provide an important building block for the transition of the current transportation paradigm to a more sustainable state. [ABSTRACT FROM AUTHOR]

The introduction of the Euro 7 emission standard is expected to significantly change the typology of the European passenger car. This study analyzes the environmental impact resulting from future trends in fleet composition and proposes an innovative vehicle classification system focused on raising consumer awareness of the importance of their choices with regard to key attributes such as body type, engine power and vehicle weight. A sensitivity analysis of the fleet's greenhouse gas emissions to deviations in their composition is carried out, considering the preferences expressed by the consumers in 2022 and the vehicle's specifications reported by the automotive industry on European digital platforms embodying Industry 4.0 principles. The findings show that internal combustion fleet emissions are expected to rise 0.30% per 1% increase in engine power and 0.44% to 0.69% per 1% increase in weight, according to the Worldwide Harmonised Light Vehicle Test Procedure (WLTP). The plug-in electric vehicle (PHEV) segment is the fastest growing in terms of market share. This trend will continue in the future, as this is the segment best suited to comply with the emissions targets imposed on manufacturers. Another relevant conclusion is that the environmental impact of PHEV vehicles is potentially very negative if the drivers' charging habits do not reflect the manufacturer's design intention. Thus, the development of consumer environmental awareness tools is urgent. This is the study's main motivation: to develop a tool in the scope of the Industry 4.0 while promoting the emergent concept of Industry 5.0, sustainability based and human-centered. [ABSTRACT FROM AUTHOR]

A geographical information system (GIS) is an advanced tool for collecting, managing, and analyzing spatially-referenced data. The contribution of GIS use to process performance indicators can be improved by combining it with multi-criteria decision analysis (MCDA). Combining a GIS and MCDA is, in the scientific literature, rarely discussed for planning an internal transportation system in a manufacturing plant's outdoor area. The purpose of this article is to clarify what mangers can expect from using a combined approach when deciding on a transport fleet and the operational routing of vehicles. Beside the simulation of MCDA, the computer software ArcGIS Pro 3.0.2 with the Network Analyst extension was used for modelling the transportation system in the form of a case study. The article demonstrates the feasibility and effectiveness of GIS and MCDA use and reveals the extent of the challenge of how decision makers could make the most of ArcGIS functionality. The final solution for an internal transportation system in a manufacturing plant's outdoor area includes such a vehicle fleet and the set time windows of orders for transport services, so that there are no violations of time windows and the work is completed within the work shift while minimizing costs, time, and distance. Decision makers can use the program without advanced knowledge of optimization approaches, following a procedure that does not differ much from that of learning to use other business software tools. On the contrary, the listed disadvantages can be summarized as the rigidity of setting detailed boundary conditions for a specific simulation scenario. [ABSTRACT FROM AUTHOR]

The increasing volume of personal motorized vehicles (PMVs) in cities has become a serious issue leading to congestion, noise, air pollution and high land consumption. To ensure the sustainability of urban transportation, it is imperative to transition the current transportation paradigm toward a more sustainable state. Transitions within socio-technical systems often arise from niche innovation. Therefore, this paper pursues the technical optimization of such a niche innovation by applying a technical sustainability perspective on an innovative mobility and logistics concept within a case study. This case study is based on a centrally managed connected, automated, shared and electric (CASE) vehicle fleet which might replace PMV use in urban city centers of the future. The key technical system components of the envisioned mobility and logistics concept are analyzed and optimized with regard to economic, ecological and social sustainability dimensions to maximize the overall sustainability of the ecosystem. Specifically, this paper identifies key challenges and proposes possible solutions across the vehicle components as well as the orchestration of the vehicles’ operations within the envisioned mobility and logistics concept. Thereby, the case study gives an example of how different engineering disciplines can contribute to different sustainability dimensions, highlighting the interdependences. Finally, the discussion concludes that the early integration of sustainability considerations in the technical optimization efforts of innovative transportation systems can provide an important building block for the transition of the current transportation paradigm to a more sustainable state.

Introduction. The results of forecast estimation of the number, structure of the Russian motor vehicle fleet by type of power units and greenhouse gas (GHG) emissions up to 2050 are presented, taking into account the update of the initial data used in the calculations and the assumption that it will be decided to stop production of passenger cars with internal combustion engines starting from 2045. Materials and methods. The forecast of the level of motorization, the number of vehicle fleet by type of power plant and fuel type, environmental class were estimated taking into account the renewal of the fleet, the balance of supply and disposal of ATVs. These data are given in the forms of state statistical reporting, long-term strategies of transport industry development, partly generated by researchers themselves. The Copert 5 methodology was also used to calculate greenhouse gas emissions.Results. Compared to earlier projections, the value of total GHG emissions of the vehicle fleet in 2050 according to the current projection will be about the same as in 2045, i.e. will be 5 years behind. Discussion and conclusions. In the near term, the rate of decarbonization of road transport in Russia may slow down significantly. Vehicles with internal combustion engines using hydrocarbon fuels (liquid, gaseous) will still dominate the vehicle fleet by 2050.

European institutions have decided to ban the sale of Internal Combustion Vehicles (ICEVs) in the EU from 2035. This opens a possible scenario in which, in the not-too-distant future, all vehicles circulating in Europe are likely to be Battery Electric Vehicles (BEVs). The Spanish vehicle fleet is one of the oldest and has the lowest percentage of BEVs in Europe. The aim of this study is to evaluate the hypothetical scenario in which the current mobility of ICEVs is transformed into BEVs, in the geographical area of the province of Barcelona and in Spain in general. The daily electricity consumption, the required installation capacity of wind and solar photovoltaic energies, and the potential reduction of NOx and particulate matter (PM) emissions are estimated. The daily emission reduction would be about 314 tons of NOx and 17 tons of PM in Spain. However, the estimated investment required in Spain to generate the additional electricity from renewable sources would be enormous (over EUR 25.4 billion), representing, for example, 5.5% of the total national budget in 2022. [ABSTRACT FROM AUTHOR]

Emissions from vehicular traffic are one of the key drivers of urban environmental air pollution, degrading the ambient air quality in many African cities and across the globe. This study sought to assess the impact of traffic mobility measures on the emission levels of air pollutants from vehicle exhaust in Lagos, Nigeria. Traffic flow and vehicle mix were collected daily during morning, afternoon, and evening peak periods along selected arterial and two-lane collector roadways. Simultaneously, five (5) air pollutants from vehicular traffic emissions were observed at distinct monitoring stations along the roadways using portable gas detectors. The traffic flow and mobility measures were inputted into a multiple exponential model to estimate the concentration of each pollutant. The result of the vehicle fleet composition revealed 3.5%, 4.5%, 57%, 32%, 1.5%, and 2% for motorcycles, tricycles, personal cars, minibuses, large buses, and heavy goods vehicles, respectively, on the two-lane road and 10%, 35%, 27%, 10%, and 18% for motorcycles, personal cars, minibuses, large buses, and heavy goods vehicles, respectively, on the arterial. The results of a multiple exponential regression model (MER) showed significant contributions from traffic flow, speed, vehicle fleet proportion, and pollutant concentration (p

Within the multiple urban–rural interactions that make up the territorial dynamics, this article addresses and identifies how mobility relations are produced between neighbouring municipalities that share services. The aim of this research is to carry out a diagnosis of the current mobility situation in an area of low population density in order to identify the needs and possible shortcomings in this area. The initial identification of weaknesses is essential in order to propose solutions for rural mobility. The methodology adopted is based on two distinct lines of work: (1) analysis of information in open data from public repositories using geographic information system tools (GIS), and (2) surveys of citizens living in the study area. The results allude to the fact that the most transcendental problem in the study area is the lack of a quality collective public transport service that meets minimum utility requirements for users, a fact that generates a transfer towards the use of private vehicles. No serious parking, noise, pollution or road safety problems are observed; however, similar dynamics to other rural areas with low demographic density are confirmed, such as the age of the mobile fleet and an aging population with accessibility problems. The presence of new modes of transport (electric bicycles, personal mobility vehicles, and even electric vehicles) is practically insignificant. Both teleworking and the new consumer habits associated with online shopping have not yet had a strong impact. Political decision making by public administrations is identified as a direct application of this research. [ABSTRACT FROM AUTHOR]

This work focuses on examining the contribution of passenger cars to CO2, NOX, CO, PM10, and NMVOC emissions, as well as the changes in future emissions resulting from the usage of different types of vehicles. Initially, the importance of the road transport sector is discussed, followed by a presentation of data regarding the vehicle fleet. Subsequently, a methodology for forecasting the fleet, and calculating emissions, is introduced. Finally, the results are presented, focusing on the release of gaseous pollutants under different possible scenarios regarding the extent of electric vehicle penetration into the passenger vehicle fleet, for the year 2030.

There is a growing demand for energy consumption in Colombia. For this reason, the country wants to promote policies for the diversification of energy in its the transport systems. Thus, it is relevant to evaluate the energy and environmental impacts of promoting the increase of zero and low emission vehicles. The objective of this study is to show the development of a computational tool that implements several models and allows for the configuration of different technology scenarios to determine the impact of the implementation of zero and low emission vehicle fleets. To develop the tool, an agile software development methodology is used, which facilitates following a systematic process for its construction. Using the computational tool, the user can obtain results for short-, medium-, and long-term projections. [ABSTRACT FROM AUTHOR]

Copyright of ESPOCH Congresses: The Ecuadorian Journal of S.T.E.A.M. is the property of Knowledge E DMCC and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Purpose: The aim of the work is to present selected research results of the first stage of work, the so-called pre-design research related to the implementation of electric vehicles into the company's fleet. Design/methodology/approach: the article presents inconsistencies and problems related to the use of electric buses as well as problems related to point infrastructure. The results of the research were obtained from the observations of the analyzed transport processes, the process of fleet management, from interviews with employees, as well as from the analysis of documentation and comparison of records with the actual state. Findings: The results confirm that the effective elimination of nonconformities leads to the improvement of the process quality and the reduction of costs related to vehicle breakdowns. Research limitations/implications: The research indicates the need for continuous improvement of the process of using electric vehicles. Validation studies have confirmed that it is impossible to eliminate all problems, therefore the process should be constantly improved. Originality/value. The article indicates the need to amend the subsequent projects and the current methodology of the procedure. [ABSTRACT FROM AUTHOR]

Emerging data-driven approaches, such as deep reinforcement learning (DRL), aim at on-the-field learning of powertrain control policies that optimize fuel economy and other performance metrics. Indeed, they have shown great potential in this regard for individual vehicles on specific routes/drive cycles. However, for fleets of vehicles that must service a distribution of routes, DRL approaches struggle with learning stability issues that result in high variances and challenge their practical deployment. In this paper, we present a novel framework for shared learning among a fleet of vehicles through the use of a distilled group policy as the knowledge sharing mechanism for the policy learning computations at each vehicle. We detail the mathematical formulation that makes this possible. Several scenarios are considered to analyze the framework's functionality, performance, and computational scalability with fleet size. Comparisons of the cumulative performance of fleets using our proposed shared learning approach with a baseline of individual learning agents and another state-of-the-art approach with a centralized learner show clear advantages to our approach. For example, we find a fleet average asymptotic improvement of 8.5% in fuel economy compared to the baseline while also improving on the metrics of acceleration error and shifting frequency for fleets serving a distribution of suburban routes. Furthermore, we include demonstrative results that show how the framework reduces variance within a fleet and also how it helps individual agents adapt better to new routes. • A shared learning algorithm for a fleet of vehicles serving a distribution of routes. • A characterization of the scalability and computational complexity of the algorithm. • Demonstration of the benefits of shared learning for fleets in varying scenarios. [ABSTRACT FROM AUTHOR]

In this paper, research is done in the influence of different terrain and traffic conditions on road sections on the driver's driving performances, i.e. on the car energy efficiency and CO2 emission. A methodology aimed at determining to which extent unfavorable traffic and/or terrain conditions on a road section contribute to the driver's worse driving performances, and also to determine when the driver's aggressive driving style is responsible for greater fuel consumption and greater CO2 emission is proposed. In order to apply the proposed methodology, a research study was carried out in a cargo transportation company and 12 drives who drove the same vehicle on five different road sections were selected. As many as 284014 of the instances of the data about the defined parameters of the road section and the driver's driving style were collected, based on which and with the help of machine learning a prediction of the scores for the road section and the scores for the driver's driving style was performed. The obtained results have shown that the proposed methodology is a useful tool for managers enabling them to simply and quickly determine potential room for increasing the energy efficiency of the vehicle fleet and decreasing CO2 emission. [ABSTRACT FROM AUTHOR]

Running business activity in the field of transport requires managing people to coordinate many factors at the same time. The most important factor for the functioning of an enterprise is the planning of execution of transport orders, which is an inherent element of effective management of a fleet of vehicles. The management of logistics and transport is a field of science derived from economic practice, therefore, real events occurring in an enterprise providing transport services at the national and international level were examined. Research and analysis of transport processes were conducted in an enterprise from the TSL sector functioning in the European Union in the aspect of efficient use of a fleet of vehicles.

The present research work analyzes the noise pollution of the automobile fleet in the District of Jesús María located in Lima - Perú. The general objective was "To determine the incidence of the application of Ordinance N° 310-2009-MDJM. in the noise pollution of the vehicle fleet in the district of Jesús María, 2020" the type of research is applied; descriptive and explanatory level and non-experimental design. The population object of study was constituted by the inhabitants of the district and the floating population, considering a non-probabilistic sample of 210 people. The instruments used were: measurements of sound pressure in fixed stations, counting of public and private vehicles in the time of measurement of good pressure, and a questionnaire that was validated by expert judges, the same one that constituted 32 items of the scale of Likert. The results found in the sound pressure measurements exceeded the maximum sustainability of the analyzed Ordinance, showing noise pollution. The statistical test used was the Spearman correlation coefficient, determining that there are differences in noise pollution at the stations and not at the timetables; that public and private vehicles increase sound pressure measurements under different conditions; concluding that: "The application of Ordinance N° 310-2009-MDJM significantly affects noise pollution in the vehicle fleet in the district of Jesús María, 2020". [ABSTRACT FROM AUTHOR]

Within the multiple urban–rural interactions that make up the territorial dynamics, this article addresses and identifies how mobility relations are produced between neighbouring municipalities that share services. The aim of this research is to carry out a diagnosis of the current mobility situation in an area of low population density in order to identify the needs and possible shortcomings in this area. The initial identification of weaknesses is essential in order to propose solutions for rural mobility. The methodology adopted is based on two distinct lines of work: (1) analysis of information in open data from public repositories using geographic information system tools (GIS), and (2) surveys of citizens living in the study area. The results allude to the fact that the most transcendental problem in the study area is the lack of a quality collective public transport service that meets minimum utility requirements for users, a fact that generates a transfer towards the use of private vehicles. No serious parking, noise, pollution or road safety problems are observed; however, similar dynamics to other rural areas with low demographic density are confirmed, such as the age of the mobile fleet and an aging population with accessibility problems. The presence of new modes of transport (electric bicycles, personal mobility vehicles, and even electric vehicles) is practically insignificant. Both teleworking and the new consumer habits associated with online shopping have not yet had a strong impact. Political decision making by public administrations is identified as a direct application of this research.

Due to the great market competition, transport companies face the need to reduce their vehicle fleet costs. The vehicle fleet managers' actions on the driver's driving style to achieve fuel consumption savings are measures to increase the fleet's energy efficiency. The authors developed a model for evaluating driving style using a type-2 fuzzy logic system. The model comprehensively considers three parameters: engine speed, accelerator pedal position, and acceleration/deceleration. These parameters can precisely describe the driving style and additionally have a strong influence on fuel consumption. The model output is the driver's score, representing the influence of driving style to fuel consumption. The model is tested in the company whose drivers have attended the eco-driving training course. Each driver's driving style was monitored for 15 days to obtain trustworthy assessments regarding driving style. The result was twofold: firstly, we point out the importance of simultaneous observation of all three defined parameters to get reliable driver's score in terms of driving style, and secondly, it is established that drivers have significantly different driving styles regardless of whether they have attended the same eco-driving training. The established differences in driving styles have a direct impact on the obtained differences in fuel consumption among drivers. The proposed model can significantly reduce fuel consumption depending on the driving style and increase the vehicle fleet's energy efficiency. [ABSTRACT FROM AUTHOR]

Road transport on one hand plays an important role in the world economy and significantly contributes to the global gross domestic product; on the other hand, it is one of the main sources of air pollution and greenhouse gas emissions, mostly originating from the consumption of liquid fossil fuels. One of the main tools to monitor emissions, in an effort to reduce them, is to maintain inventories where emissions are estimated on a regular basis. Many countries maintain their own inventories, while there are also centralised databases gathering data from various countries and producing aggregated results, e.g. on total European Union level. However, maintaining emission inventories on a global scale is a tedious process mainly due to lack or poor quality of data for some countries and because of inconsistencies in the emission estimation methodologies followed. This article presents the methodology and results of a global road transport emission inventory, as part of the EDGAR (Emissions Database for Global Atmospheric Research) v6.1 database. It covers the majority of countries and regions in the world, i.e. global road vehicle fleet emissions. The vehicle emission processes considered comprise exhaust, fuel evaporation, tyre and brake wear, and road abrasion. The methodology involves the collection and processing of the relevant statistical data, i.e. vehicle fleet, activity, and energy from various sources. This information is combined with the appropriate emission factors, resulting in emission calculations per country, year, and vehicle category. The dataset developed is validated by comparison against official inventories and third-party emission estimates. The current database can be used to obtain a global view of emissions from the road transport sector for the period 1990–2020. Significant conclusions can be reached from analysing this dataset, for example which countries contribute the most to each pollutant, which vehicle types are the biggest emitters and more. The dataset can be useful for emission and air quality modellers, scientists and policy makers and can help design better policies for the future. [Display omitted] • Global road transport inventory with main trends of vehicle fleet, fuel, emissions. • Complete time series as a tool to monitor emissions and evaluate their impact. • Robust methodology with concrete steps that can be followed for any country. [ABSTRACT FROM AUTHOR]

Running business activity in the field of transport requires managing people to coordinate many factors at the same time. The most important factor for the functioning of an enterprise is the planning of execution of transport orders, which is an inherent element of effective management of a fleet of vehicles. The management of logistics and transport is a field of science derived from economic practice, therefore, real events occurring in an enterprise providing transport services at the national and international level were examined. Research and analysis of transport processes were conducted in an enterprise from the TSL sector functioning in the European Union in the aspect of efficient use of a fleet of vehicles. [ABSTRACT FROM AUTHOR]

The recent growth in real‐time, high‐capacity ride‐sharing has made on‐demand public transit (ODPT) a reality. ODPT systems serving passengers using a vehicle fleet that operates with flexible routes, strive to minimise fleet travel distance. Heuristic routing algorithms have been integrated in ODPT systems in order to improve responsiveness. However, route computation time in such algorithms depends on problem complexity and hence increases for large scale problems. Thus, network segmentation techniques that exploit parallel computing have been proposed in order to reduce route computation time. Even though computation time can be reduced using segmentation in existing techniques, it comes at the cost of degradation of route quality due to static demarcation of boundaries and disregarding real road network distances. Thus, this work proposes, a directionality‐centric bus transit network segmentation technique that exploits parallel computation capable of computing routes in near real‐time while providing high scalability. Additionally, a dynamic fleet allocation algorithm that exploits proximity and flexibility to minimise vehicle detours while maximising fleet utilisation is proposed. Experimental evaluations on a real road network confirm that the proposed method achieves notable speed‐up in flexible route computation without compromising route quality compared to a widely used unsupervised learning technique. [ABSTRACT FROM AUTHOR]

• Using a multi-user driving simulator to conduct experiments. • Exploring the patterns of FRECs occurrence under foggy conditions and speed limits. • Safety margin in fleet were reduced in heavy fog led to high frequency of FRECs. • Lower speed limits satisfy drivers' visual and psychological requirements in fog. • Vehicles at the front positions of a fleet were more likely to have collisions. Vehicle fleet rear-end collisions (FRECs) are an extremely fatal type of traffic collisions on freeway and they usually occur in foggy weather. This study aimed to explore the patterns of vehicle fleet rear-end collisions occurrence under different foggy conditions and speed limits on freeway. A multi-user driving simulator system was used to conduct the experiment and the driving behavior data were collected from eight participants. The experimental results showed that as the fog density increased, the length of vehicle fleet decreased significantly, and drivers tended to keep a more stable car-following distance. The fog weather and short vehicle gap prompted drivers to react faster and brake harder in respond to the leading vehicle's brake. In spite of the compensational behaviors, more FRECs were observed under heavy fog condition. Lowering speed limit can significantly reduce the FRECs under foggy conditions. As the speed limits reduced, drivers' brake response time and speed variance significantly reduced. The study also found that drivers' brake response time was negatively correlated with their positions in the fleet. Drivers in the front positions of the fleet had a longer response time than drivers in the back positions and thus were more likely to encounter collisions. The study generated a better understanding of drivers' behavioral pattern in a vehicle fleet and the patterns of vehicle fleet rear-end collisions occurrence. The findings also shed lights on the design of driver assistance system for complex driving situations such as freeway driving under adverse weather. [ABSTRACT FROM AUTHOR]

The value proposition for ground vehicle modularity in the U.S. Army and other services has been a topic of continuing debate. Studies to date have largely focused on individual system elements such as manufacturing or maintenance, lacking a holistic perspective of the implications of modularity for the entire fleet operation and life-cycle. The U.S. Army Science and Technology community has demonstrated the technical feasibility of large-scale, transformative ground vehicle modularity, but the business case for modularity remains incomplete. There are multiple criteria tradeoffs between modular and mission-specific (conventional) vehicle platforms, such as total life-cycle cost, mission utility, personnel requirements, and fleet adaptability. This paper presents a system-of-systems framework to address these tradeoffs to support high-level decisions on the strategic feasibility of ground vehicle modularity. We demonstrate this framework with a notional example and an application to the Joint Tactical Transport System (JTTS), a U.S. Army Tank Automotive Research, Development and Engineering Center demonstrator program. Under certain modeling assumptions with regards to the operation of a modular fleet, results for the JTTS study indicate that modularity can lead to significant cost savings at the expense of increased personnel requirements. [ABSTRACT FROM AUTHOR]

The composition and size of the passenger car fleet is often influenced by legislation and policy, including taxation, scrappage, and vehicle registration policies. Numerous measures at national and international level have been investigated to reduce the air pollution and/or climate change impacts of passenger fleets. However, the objectives of climate change and air pollution policy occasionally are conflicting, and this has resulted in a number of well publicised policy shortcomings. This paper outlines the development of a fleet emissions control (FEC) framework which enables the dynamic and adaptive optimisation of fleet emissions through changes in taxation policy in Ireland. The data for analysis was obtained from national sources including datasets from the national emission inventory and COPERT model. Applications of regression-based modelling and statistical analysis were conducted to predict fleet, mileage, and emissions changes. The results of the FEC framework showed that no increase in NO x emissions, above 2007 levels, could be achieved at a cost of a small increase in CO 2 in 2016 (+1.8%). This could be achieved by taxation policy primarily resulting in a shift away from small engine diesel vehicles (<1.4 L) in the fleet which were responsible for the largest contribution to emissions. In the transition of vehicle fleets to full electrification or full decarbonisation, the FEC framework developed here offers the potential to formulate practical and optimised adjustments in static taxation systems. These adjustments will assist in achieving the requirements of national policies on reducing emission. • A Fleet Emissions Control Framework for passenger cars was developed enabling practical optimisation of fleet emissions. • Incentivising one vehicle category over another, is a complex process with potentially positive and negative outcomes. • Incentivising diesel or petrol each have negative consequences. • Policy should incentivise a fleet composition which optimises the total emission. [ABSTRACT FROM AUTHOR]

Each business faces large competition in the market, and it is necessary to adopt the most effective methodology as possible in order to obtain the best solution. Six Sigma (6σ) is a set of techniques and tools for process improvement. The tools of Six Sigma apply within a simple improvement model known as Define–Measure–Analyze–Improve–Control (DMAIC). This paper shows that implementing Six Sigma can be more effective in managing the vehicle fleet. The combination of mathematical, i.e., statistical basis and practice makes Six Sigma so successful. The Six Sigma project, implemented to reduce costs and increase the availability of a vehicle fleet in a selected company, can be widely applied in other similar enterprises.