Small Fleet Research Articles

A Comprehensive Research Agenda for Integrating Ecological Principles into the Transportation Sector

The paper examines the integration of novel Transportation Ecology principles into transit operations, aiming to address the environmental impacts associated with surface services in urban areas and with the purpose of creating a comprehensive agenda for integrating ecological principles into transit planning and management. The research problem is to quantify the tangible benefits for transit operators, particularly in the context of mitigating wildlife-vehicle collisions and improving overall operational efficiency as a motivator for transit managers to adopt Transportation Ecology principles. The study design, after analyzing the regulatory requirements, implements scenario-based methodology, utilizing data from an average Italian bus fleet to estimate potential monetary savings and benefits. Key parameters, such as maintenance costs, insurance premiums, and collision-related expenses, are analyzed to provide a realistic assessment of the economic advantages of implementing Transportation Ecology measures. The findings reveal that significant cost reductions can be achieved by minimizing accidents involving wildlife, alongside other operational improvements. The scenario demonstrates that even a small fleet, when adopting these principles, can yield substantial financial benefits, thereby making a compelling case for broader implementation. The paper concludes that while the qualitative nature of the analysis necessitates conservative estimates, the results underscore the value of incorporating ecological considerations into transit planning and management. These insights are vital for transit operators and policymakers seeking to balance environmental sustainability with operational profitability and protect urban ecosystems. This also implies the need for a more holistic and interdisciplinary approach to transportation planning and management.

Competitive pricing for ride-sourcing platforms with MARL

With the advancement of autonomous driving, the competition between shared autonomous vehicles (SAVs) and the existing human-driven vehicles (HVs) ride-sourcing platforms has emerged as a prominent research area within the fields of transportation and management. Solving the pricing problem, considering the competition between HV and SAV platforms, is critical for the platform’s operation. The competitive pricing problem is hard to solve since it is a partially observable Markov decision process (POMDP), that is, only the strategies of other platforms (such as price and wage) are observable, while their states are unobservable. It is also a multivariable sequential problem pricing since spatial-temporal pricing varies with region and time. To tackle this complex problem, this paper implements the multi-agent reinforcement learning (MARL) approach of multi-agent deep deterministic policy gradient (MADDPG) to an mesoscopic simulation system. The simulation replicates the intricate dynamics within a competitive environment where SAV and HV platforms coexist. MADDPG effectively resolves the competitive pricing issue using data derived from simulation. The findings indicate that the SAV platform secures greater profits with a smaller fleet, as it eliminates the need to compensate drivers. Meanwhile, for the same reason, even with fewer vehicles, the SAV platform can set lower prices to attract more passengers and thereby generate higher profits. We further evaluate the efficacy of dynamic pricing versus spatial-temporal pricing and discover that spatial-temporal pricing yields greater profits.

Fleet scheduling for electric towing of aircraft under limited airport energy capacity

Taxiing aircraft using electric vehicles is seen as an effective solution to meet aviation targets of climate neutrality. However, making the transition to electric taxiing operations is expected to significantly increase the electricity demand at airports. In this paper we propose a mixed-integer linear program to schedule electric vehicles for aircraft towing and battery charging, while considering a limit for the supply of energy. The objective of the schedule is to maximize emissions savings. For computational tractability, we develop an Adaptive Large Neighbourhood Search which makes use of multiple local search heuristics to identify scheduling solutions. For daily scheduling with a small fleet size, the developed heuristic achieves solutions with an average 4% gap to the best linear programming solution. The results show that charging the vehicles during daytime is essential to maximize saved emissions: removing charging opportunities for a few hours during the day reduces the performance by an average of 6.4%. In addition, it is found that fast charging leads to low vehicle downtime, unless the battery size exceeds 750kWh, when charging rates over 150kW become unnecessary. Overall, our model provides support for infrastructure planning of airports during the transition to aircraft electric taxiing.

Optimization of Grid Energy Balance Using Vehicle-to-Grid Network System

This paper proposes a methodological way to compensate for the imbalance between energy generation and consumption using a battery block from electric vehicles as an energy reservoir through the well-known vehicle-to-grid system (V2G). This method is based on a simulation process developed by the authors that takes into consideration the daily fluctuations in energy consumption as well as the power level generated by an energy source, either conventional, renewable, or hybrid. This study shows that for very large electric vehicle fleets, the system is rendered non-viable, since the remaining energy in the battery block that allows the electric vehicle to be usable during the daytime avoids having to compensate for the energy grid imbalance, only allowing it to cover a percentage of the energy imbalance, which the proposed methodology may optimize. The analysis of the proposed methodology also shows the viability of the system when being applied to a small fleet of electric vehicles, not only compensating for the energy imbalance but also preserving the required energy in the battery of the electric vehicle to make it run. This method allows for predicting the optimum size of an electric vehicle battery, which depends on the energy generation level, coverage factor of the energy imbalance, and size of the electric vehicle fleet.

Total Cost of Ownership Analysis of Fuel Cell Electric Bus with Different Hydrogen Supply Alternatives

In the transition to sustainable public transportation with zero-emission buses, hydrogen fuel cell electric buses have emerged as a promising alternative to traditional diesel buses. However, assessing their economic viability is crucial for widespread adoption. This study carries out a comprehensive examination, encompassing both sensitivity and probabilistic analyses, to assess the total cost of ownership (TCO) for the bus fleet and its corresponding infrastructure. It considers various hydrogen supply options, encompassing on-site electrolysis, on-site steam methane reforming, and off-site hydrogen procurement with both gaseous and liquid delivery methods. The analysis covers critical cost elements, encompassing bus acquisition costs, infrastructure capital expenses, and operational and maintenance costs for both buses and infrastructure. This paper conducted two distinct case studies: one involving a current small bus fleet of five buses and another focusing on a larger fleet set to launch in 2028. For the current small fleet, the off-site gray hydrogen purchase with a gaseous delivery option is the most cost-effective among hydrogen alternatives, but it still incurs a 26.97% higher TCO compared to diesel buses. However, in the case of the expanded 2028 fleet, the steam methane-reforming method without carbon capture emerges as the most likely option to attain the lowest TCO, with a high probability of 99.5%. Additionally, carbon emission costs were incorporated in response to the growing emphasis on environmental sustainability. The findings indicate that although diesel buses currently represent the most economical option in terms of TCO for the existing small fleet, steam methane reforming with carbon capture presents a 69.2% likelihood of being the most cost-effective solution, suggesting it is a strong candidate for cost efficiency for the expanded 2028 fleet. Notably, substantial investments are required to increase renewable energy integration in the power grid and to enhance electrolyzer efficiency. These improvements are essential to make the electrolyzer a more competitive alternative to steam methane reforming. Overall, the findings in this paper underscore the substantial impact of the hydrogen supply chain and carbon emission costs on the TCO of zero-emission buses.

Management of Hybrid Wind and Photovoltaic System Electrolyzer for Green Hydrogen Production and Storage in the Presence of a Small Fleet of Hydrogen Vehicles—An Economic Assessment

Nowadays, with the need for clean and sustainable energy at its historical peak, new equipment, strategies, and methods have to be developed to reduce environmental pollution. Drastic steps and measures have already been taken on a global scale. Renewable energy sources (RESs) are being installed with a growing rhythm in the power grids. Such installations and operations in power systems must also be economically viable over time to attract more investors, thus creating a cycle where green energy, e.g., green hydrogen production will be both environmentally friendly and economically beneficial. This work presents a management method for assessing wind–solar–hydrogen (H2) energy systems. To optimize component sizing and calculate the cost of the produced H2, the basic procedure of the whole management method includes chronological simulations and economic calculations. The proposed system consists of a wind turbine (WT), a photovoltaic (PV) unit, an electrolyzer, a compressor, a storage tank, a fuel cell (FC), and various power converters. The paper presents a case study of green hydrogen production on Sifnos Island in Greece through RES, together with a scenario where hydrogen vehicle consumption and RES production are higher during the summer months. Hydrogen stations represent H2 demand. The proposed system is connected to the main power grid of the island to cover the load demand if the RES cannot do this. This study also includes a cost analysis due to the high investment costs. The levelized cost of energy (LCOE) and the cost of the produced H2 are calculated, and some future simulations correlated with the main costs of the components of the proposed system are pointed out. The MATLAB language is used for all simulations.

The close-open mixed-fleet electric vehicle routing problem

The market of Electric Vehicles (EVs) has grown significantly in recent times. The transportation sector is expected to shift to EVs as well, but there are several significant challenges that make the shift difficult, mainly their capacity for transporting heavy payloads and their high acquisition costs. This research explores a novel business concept wherein a logistics company owns a small fleet of EVs, and rents additional EVs as needed, while providing the option to charge the owned EVs only after completing the final delivery. This concept is modeled as a Close-Open Mixed-fleet Electric Vehicle Routing Problem (COMF-EVRP), and the mathematical formulation is presented. Instances from the literature are adapted for the COMF-EVRP. To solve large instances, three discrete optimization swarm intelligence algorithms are employed, alongside a Variable Neighborhood Search algorithm. Lastly, a comprehensive evaluation of these algorithms’ performance on the COMF-EVRP is provided.

ANALISIS KUALITAS LAYANAN ANGKUTAN UMUM PENUMPANG (MINIBUS) KOTA DENPASAR BERDASARKAN PERSEPSI MASYARAKAT DENGAN METODE CONFIRMATORY FACTOR ANALYSIS

Public transportation in the city of Denpasar reached its peak in the 1990s with the latest fleet being minibus-type public passenger cars with a capacity of 8-10 people. Along with the pace of motorization and ease of buying cars and motorbikes, there can be an increase in private vehicle ownership in the community. The interest of the people in Denpasar City's use of public transportation has decreased significantly. The community can finally feel and have perceptions about the difference between the advantages of using private vehicles and the quality of public transportation services. The purpose of this study was to explore public perceptions of the quality of public transport services, by distributing 400 questionnaires in all sub-districts of Denpasar City. Data on respondents' perceptions were analyzed using structural equation modeling (SEM). Based on the results of the analysis, there are seven indicators that shape people's perceptions of the quality of public transport, namely: small fleet availability, long waiting and travel times, less convenience, irregular time headway, low frequency of arrivals, and accessibility. The reduced availability of public transport is caused by long waiting times and low frequency of arrivals. Low accessibility due to long travel time. Thus, the quality of services like this in the community makes the use of public transportation in the city of Denpasar decreased.

Measuring Eco-Efficiency of the Global Shipping Sector Based on an Energy and Environmental Approach: A Dynamic Slack-Based Measure Non-Oriented Model

The compatibility of shipping with environmental protection is a subject that the international community is becoming increasingly concerned about, considering the threat of climate change. The current study aims to assess the worldwide shipping sector’s eco-efficiency performance for the first time using the Dynamic Slack-Based assess non-oriented Data Envelopment Analysis methodology, while the visualization of the results has been made with the geographic information system of ArcGIS. The findings show that the most vibrant shipping sectors in the world, such as the Marshall Islands, present the lowest eco-efficiency levels due to the nations’ roles as tax havens for shipowners. Furthermore, traditional maritime economies such as the Chinese one show a great growth in the eco-efficiency score due to the strategies of the shipping companies that are headquartered in the region to invest and adopt Environmental, Social, and Governance principles, which help them to achieve high scores in eco-efficiency. Finally, nations with small fleets have the greatest eco-efficiency score, as local governments have engaged in sustainable activities and initiatives over the previous four to five years to enable their marine industry to thrive and dominate the market.

Investigating the min‐cost minimum fleet problem through taxi data analysis

AbstractThe optimization of urban traffic efficiency and reduction of pollution through minimizing the number of taxis has become a topic of increasing interest. However, the problem of determining the minimum fleet that considers both time and distance efficiency has received limited attention. Furthermore, little research has been done on how this problem is influenced by factors such as city size and travel demand (i.e., the number of trips). This study extends the minimum fleet problem to the min‐cost minimum fleet problem, and proposes a method to address the problem by constructing a “dispatch network” and finding the minimum weight and minimum path cover of it. A comparative analysis of the method is conducted with the taxi trajectory data of three cities, New York, Chengdu, and Chicago, and the results show a reduction in the off‐load travel time of vehicles compared to the previous method, while maintaining the same fleet size. With the introduction of an emissions model and its combination with our methodology, emissions can also be minimized. Moreover, the relationship between min‐cost minimum fleet and city size and travel demand (number of trips) is studied. Experimental results indicate that fleet size and idle time (distance) vary linearly with the number of trips. Meanwhile, city size also has an essential impact on the algorithm's performance. Furthermore, these results indicate that the min‐cost minimum fleet will help small cities to achieve higher efficiency (smaller fleet and less connection time) than large cities. The acceleration of urbanization is driving changes in the transportation system. Our findings are expected to have significant implications for transport planning, resource conservation, and reducing pollution.

Real use of vehicle dynamic capacities: Motorcyclists versus motorists

The risk of serious crashes is much higher for motorcyclists than for motorists. While research into PTW safety is not as extensive as for other road users, there is a need for further understanding of fatal and injury crash patterns and causes, particularly in the critical pre-crash phase. Naturalistic Driving Studies (NDS) have been used to improve road safety and gain a better understanding of car crash mechanisms, but few studies have used this approach to examine PTW behavior. This paper aims to compare the actual use of PTW's dynamic capacities to that of passenger cars based on three Naturalistic Driving Studies conducted in France. A method designed to study the dynamic behavior of cars has been adapted to study the dynamic behavior of PTWs. This adaptation involves combining the longitudinal acceleration, not only with the lateral acceleration (which is adapted for cars), but also with the roll rate or the yaw rate. By doing so, it becomes possible to consider the specific behavior of PTWs in curves, and finally, to compare the dynamic demands experienced by cars and PTWs in all directions. It was found that there are significant differences in the distribution of accelerations, roll rate, yaw rate, and speeds between motorcycles and cars. Motorcycles were observed to endure higher levels of positive acceleration, experience more intense braking, and exhibit slightly higher levels of medium or high yaw rate values. The final analysis of speeds, with a 5 km/h interval, shows that motorcyclists travel at higher speeds than car drivers within a small fleet of equipped cars. However, when compared to a larger fleet of cars with speed data with a 10 km/h interval, car drivers were found to travel faster. Demand levels differ between fleets of cars and fleets of motorists, particularly where lateral demands are concerned. This can be attributed to various factors such as driving context, study duration, road type and weather conditions. Other NDS with more cars and PTWs should be analyzed with this method to complete the results.

Advancements in hydrogen production, storage, distribution and refuelling for a sustainable transport sector: Hydrogen fuel cell vehicles

Hydrogen is considered as a promising fuel in the 21st century due to zero tailpipe CO2 emissions from hydrogen-powered vehicles. The use of hydrogen as fuel in vehicles can play an important role in decarbonising the transport sector and achieving net-zero emissions targets. However, there exist several issues related to hydrogen production, efficient hydrogen storage system and transport and refuelling infrastructure, where the current research is focussing on. This study critically reviews and analyses the recent technological advancements of hydrogen production, storage and distribution technologies along with their cost and associated greenhouse gas emissions. This paper also comprehensively discusses the hydrogen refuelling methods, identifies issues associated with fast refuelling and explores the control strategies. Additionally, it explains various standard protocols in relation to safe and efficient refuelling, analyses economic aspects and presents the recent technological advancements related to refuelling infrastructure. This study suggests that the production cost of hydrogen significantly varies from one technology to others. The current hydrogen production cost from fossil sources using the most established technologies were estimated at about $0.8–$3.5/kg H2, depending on the country of production. The underground storage technology exhibited the lowest storage cost, followed by compressed hydrogen and liquid hydrogen storage. The levelised cost of the refuelling station was reported to be about $1.5–$8/kg H2, depending on the station's capacity and country. Using portable refuelling stations were identified as a promising option in many countries for small fleet size low-to-medium duty vehicles. Following the current research progresses, this paper in the end identifies knowledge gaps and thereby presents future research directions.

An iterated local search algorithm for latency vehicle routing problems with multiple depots

The Multi-depot Cumulative Capacitated Vehicle Routing Problem (MDCCVRP) extends the recently proposed Cumulative Capacitated Vehicle Routing Problem (CCVRP). The aim is to minimize the sum of the arrival times at the customers considering a fleet of Nv capacitated vehicles and a set of Nd uncapacitated depots. This paper proposes valid lower bounds and a novel metaheuristic algorithm for the solution of the MDCCVRP. The initial solution is obtained by combining different heuristic approaches, while the improving phase consists of an iterated local search algorithm (ILS). Computational experiments on 78 MDCCVRP benchmark instances show that the proposed algorithm is able to find, within reasonable computing times, solution values globally better than those obtained by the state-of-the-art heuristic algorithms. For challenging instances (having a large number of customers and a small fleet size), the algorithm can find, within short computing times, solutions globally better than those obtained by the published exact algorithms. The proposed algorithm has also been applied to the recently introduced Multi-depot k-traveling Repairman Problem (MDk-TRP) and the Latency Location Routing Problem (LLRP). The MDk-TRP is a particular case of the MDCCVRP arising when the vehicles are uncapacitated, while the LLRP is a generalization of the MDCCVRP in which, at most, p of the Nd available depots can be used. The computational experiments performed on 87 MDk-TRP benchmark instances and 76 LLRP benchmark instances show that the proposed algorithm globally outperforms the state-of-the-art metaheuristic algorithms for what concerns both the solution quality and the computing time. For large-size instances, the computing time required to provide a good quality solution is considerably smaller than that required by the previously published heuristic and exact algorithms. For all the problems, the proposed algorithm is able to find better solution values than those obtained by the respective state-of-the-art metaheuristic algorithms when it is executed for the same computing time as the respective competitor.

Маломерные суда: спектр их использования и проблемы

Using small boats is not limited to using them as watercrafts for amateur or recreational fishing, as well as an auxiliary fleet of the large-tonnage vessels. Motor boats as a means of performing the main production functions are widely used by the different industrial enterprises, whose activities are related to the operation in inland waterways and other water areas. The Astrakhan region, among other regions with inland waterways, has a large network 
 of branched canals, some of which are located in shallow waters with dense reeds, impassible for the ships with 
 a large draft transferring personnel, cargo and equipment. High speed developed by the small boats in gliding makes it possible to use them in the border service, fish protection service, in transporting passengers, etc. At the same time, the disadvantages of using small vessels are considered, namely, a much lower level of comfort compared to the large vessels, noise and vibrations from the outboard motor, the impact of emissions on the environment. Staying of the navigator in close proximity to the engine, the prolonged exposure to the negative impact of the environment (high and low temperatures, wind, precipitation) increase the fatigue of the human body. Conclusions are drawn about the need to reduce negative factors, creating more comfortable working conditions for the staff. Due to the lack of freely available information on the positive and negative aspects of using a small fleet, the experience of using motor boats with outboard motors is listed and described.

The Venetian Warships of Lake Garda. News of the Benacus Project: What If Fresh Water Is No Longer Protective?

With the French at the door, on May 31st of 1509, the Head of the Venetian Garda fleet received the order to burn and sink the ships and come back to Venice: the war on the lake was temporarily lost. The small fleet, whose base was at Lazise, was formed by one light galley and two fustas, so the commandant sunk the galley and one fusta in front of the town and went with the third ship to the northern lake to take a safe trip to Venice on horseback. One shipwreck was discovered in 1960 and was studied in several campaigns, but it was not clear if it was a small galley or a large fusta. New research was started in 2018 with BENĀCUS, a project of the Department of Humanities and Cultural Heritage of the University of Udine, in a joint venture with the Trieste and Firenze Universities, and under the Superintendency for the Archaeology, Arts and Landscape of the provinces of Verona, Vicenza and Rovigo. The aim of this project was an historical research and geophysical survey to map the underwater cultural heritage (UCH) of Garda Lake.

Least squares smoothed k-nearest neighbors online prediction of the remaining useful life of a NASA turbofan

An accurate prediction of the Remaining Useful Life (RUL) of aircraft engines plays a fundamental role in the aerospace field since it is both mission and safety critical. In fact, a reliable estimate of the RUL can effectively reduce the maintenance costs while fostering safety. This paper proposes a novel data-driven method to increase accuracy of the RUL prediction for real-time prognostic systems, considering multiple degradation mechanisms and making the model easy to implement. The proposed method exploits a novel modified k-Nearest Neighbors Interpolation (kNNI) with an a posteriori Least Square Smoothing (LSS) automatically optimized to obtain the minimum prediction error. The LSS novel formulation was also generalized and proved to be equivalent to a Cumulative and Moving Average (CMA) mixture filter, which can be easily implemented online. The method was developed and validated based on a new NASA dataset generated by the dynamic model Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) with run-to-failure data related to a small fleet of aircraft engines under realistic flight conditions. Finally, a reference kNN-based method already known in the literature was compared to the novel proposed one to demonstrate the goodness of the results and the performance improvements.

Small inland shipping in the Netherlands: Operating below the radar?

As the need for more sustainable and flexible transport continues to grow, inland shipping is emerging as a sector of interest. This paper is about small inland shipping in the Netherlands with a focus on dry cargo ships. There is currently only a limited number of studies specifically focussed on small dry cargo shipping. It has been at the centre of a societal and political debate in the Netherlands in which it has alternately attracted both positive and negative views. The recurring themes in this debate have been the shrinking of the fleet, the age of ships, the lack of entrepreneurial spirit among skippers and the sustainability of small inland shipping. Despite these discussions, there is currently no analysis of the dry cargo shipping market in the Netherlands.This paper presents an analysis of small dry cargo shipping in the Netherlands from three perspectives: fleet, cargo transport and inland ports. The analysis revealed that the size of the Dutch active small fleet is decreasing significantly. The transport performance also follows a negative development trend. However, there are also positive developments such as a slight increase in the number of trips, the average number of tonnes per loaded trip, the average number of kilometres per loaded trip and the average load factor. Another positive development is the increase in cargo throughput at inland ports situated along small waterways. Previous studies used different market definitions of small dry cargo shipping. This has an impact on the assessment of small dry cargo shipping’s development.

A subpolar-focused stratospheric aerosol injection deployment scenario

Stratospheric aerosol injection (SAI) is a prospective climate intervention technology that would seek to abate climate change by deflecting back into space a small fraction of the incoming solar radiation. While most consideration given to SAI assumes a global intervention, this paper considers an alternative scenario whereby SAI might be deployed only in the subpolar regions. Subpolar deployment would quickly envelope the poles as well and could arrest or reverse ice and permafrost melt at high latitudes. This would yield global benefit by retarding sea level rise. Given that effective SAI deployment could be achieved at much lower altitudes in these regions than would be required in the tropics, it is commonly assumed that subpolar deployment would present fewer aeronautical challenges. An SAI deployment intended to reduce average surface temperatures in both the Arctic and Antarctic regions by 2 °C is deemed here to be feasible at relatively low cost with conventional technologies. However, we do not find that such a deployment could be undertaken with a small fleet of pre-existing aircraft, nor that relegating such a program to these sparsely populated regions would obviate the myriad governance challenges that would confront any such deployment. Nevertheless, given its feasibility and potential global benefit, the prospect of subpolar-focused SAI warrants greater attention.

Pick-Up and Delivery Problem for Sequentially Consolidated Urban Transportation with Mixed and Multi-Pupropse Vehicle Fleet

Different urban transportation flows (e.g., passenger journeys, freight distribution, and waste management) are conventionally separately handled by corresponding single-purpose vehicles (SVs). The multi-purpose vehicle (MV) is a novel vehicle concept that can enable the sequential sharing of different transportation flows by changing the so-called modules, thus theoretically improving the efficiency of urban transportation through the utilization of higher vehicles. In this study, a variant of the pick-up and delivery problem with time windows is established to describe the sequential sharing problem considering both MVs and SVs with features of multiple depots, partial recharging strategies, and fleet sizing. MVs can change their load modules to carry all item types that can also be carried by SVs. To solve the routing problem, an adaptive large neighborhood search (ALNS) algorithm is developed with new problem-specific heuristics. The proposed ALNS is tested on 15 small-size cases and evaluated using a commercial MIP solver. Results show that the proposed algorithm is time-efficient and able to generate robust and high-quality solutions. We investigate the performance of the ALNS algorithm by analyzing convergence and selection probabilities of the heuristic solution that destroy and repair operators. On 15 large-size instances, we compare results for pure SV, pure MV, and mixed fleets, showing that the introduction of MVs can allow smaller fleet sizes while approximately keeping the same total travel distance as for pure SVs.

Estimating the aggregated available capacity for vehicle to grid services using deep learning and Nonlinear Autoregressive Neural Network

In order for vehicle-to-grid (V2G) services to participate in the power and energy market, they must provide as much aggregated capacity as the market needs. In order to provide this capacity, the population of electric vehicle batteries is used. For this participation it is necessary to estimate the available capacity, which makes it possible to reliably distribute the existing reserves in the future. In this study, Long Short Term Memory (LSTM) and Nonlinear Autoregressive Neural Network (NAR) were used and developed to predict the next 59 h aggregated available capacity (AAC) of a small fleet of 7 electric vehicles for a ten-day travel adapted from 72 real driving records. Market activities were simulated to include the delivery of reserves to meet the needs and included in the dataset. The ability of the developed LSTM deep learning network and NAR machine learning networks to successfully adapt their predictions to such market events has been demonstrated. The authors highlight the conclusion that this capability is critical to the viability and success of future V2G services by supporting multiple market events.