scholarly journals Quantifying the Fleet Composition at Full Adoption of Shared Autonomous Electric Vehicles: An Agent-based Approach

2021 ◽  
Vol 15 (1) ◽  
pp. 47-60
Author(s):  
Peter Hogeveen ◽  
Maarten Steinbuch ◽  
Geert Verbong ◽  
Auke Hoekstra
Keyword(s):  
Electric Vehicles ◽  
Large Population ◽  
Environmental Benefits ◽  
Passenger Vehicle ◽  
Fleet Size ◽  
Agent Based ◽  
Passenger Vehicles ◽  
Vehicle Fleet ◽  
The Impact ◽  
Autonomous Electric Vehicles

Aims: Exploring the impact of full adoption of fit-for-demand shared and autonomous electric vehicles on the passenger vehicle fleet of a society. Background: Shared Eutonomous Electric Vehicles (SAEVs) are expected to have a disruptive impact on the mobility sector. Reduced cost for mobility and increased accessibility will induce new mobility demand and the vehicles that provide it will be fit-for-demand vehicles. Both these aspects have been qualitatively covered in recent research, but there have not yet been attempts to quantify fleet compositions in scenarios where passenger transport is dominated by fit-for-demand, one-person autonomous vehicles. Objective: To quantify the composition of the future vehicle fleet when all passenger vehicles are autonomous, shared and fit-for-demand and where cheap and accessible mobility has significantly increased the mobility demand. Methods: An agent-based model is developed to model detailed travel dynamics of a large population. Numerical data is used to mimic actual driving motions in the Netherlands. Next, passenger vehicle trips are changed to trips with fit-for-demand vehicles, and new mobility demand is added in the form of longer tips, more frequent trips, modal shifts from public transport, redistribution of shared vehicles, and new user groups. Two scenarios are defined for the induced mobility demand from SAEVs, one scenario with limited increased mobility demand, and one scenario with more than double the current mobility demand. Three categories of fit-for-demand vehicles are stochastically mapped to all vehicle trips based on each trip's characteristics. The vehicle categories contain two one-person vehicle types and one multi-person vehicle type. Results: The simulations show that at full adoption of SAEVs, the maximum daily number of passenger vehicles on the road increases by 60% to 180%. However, the total fleet size could shrink by up to 90% if the increase in mobility demand is limited. An 80% reduction in fleet size is possible at more than doubling the current mobility demand. Additionally, about three-quarters of the SAEVs can be small one-person vehicles. Conclusion: Full adoption of fit-for-demand SAEVs is expected to induce new mobility demand. However, the results of this research indicate that there would be 80% to 90% less vehicles required in such a situation, and the vast majority would be one-person vehicles. Such vehicles are less resource-intense and, because of their size and electric drivetrains, are significantly more energy-efficient than the average current-day vehicle. This research indicates the massive potential of SAEVs to lower both the cost and the environmental impact of the mobility sector. Quantification of these environmental benefits and reduced mobility costs are proposed for further research.

scholarly journals Electric Vehicles in Jordan: Challenges and Limitations

2021 ◽  
Vol 13 (6) ◽  
pp. 3199
Author(s):  
Laith Shalalfeh ◽  
Ashraf AlShalalfeh ◽  
Khaled Alkaradsheh ◽  
Mahmoud Alhamarneh ◽  
Ahmad Bashaireh
Keyword(s):  
Electric Vehicles ◽  
Distribution System ◽  
Distribution Systems ◽  
Environmental Benefits ◽  
System Stability ◽  
Loading Conditions ◽  
Stability Margins ◽  
High Penetration ◽  
Node Distribution ◽  
The Impact

An increasing number of electric vehicles (EVs) are replacing gasoline vehicles in the automobile market due to the economic and environmental benefits. The high penetration of EVs is one of the main challenges in the future smart grid. As a result of EV charging, an excessive overloading is expected in different elements of the power system, especially at the distribution level. In this paper, we evaluate the impact of EVs on the distribution system under three loading conditions (light, intermediate, and full). For each case, we estimate the maximum number of EVs that can be charged simultaneously before reaching different system limitations, including the undervoltage, overcurrent, and transformer capacity limit. Finally, we use the 19-node distribution system to study these limitations under different loading conditions. The 19-node system is one of the typical distribution systems in Jordan. Our work estimates the upper limit of the possible EV penetration before reaching the system stability margins.

Insights into the Impact of Social Networks on Evolutionary Games

2008 ◽  
pp. 306-323
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Weibull, 1995; Taylor & Jonker, 1978; Nowak & May, 1993) to model the dynamics of adaptive opponent strategies for large population of players. In particular, we explore effects of information propagation through social networks in Evolutionary Games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2010 ◽  
pp. 150-159
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

The chapter explores the use of evolutionary game theory (EGT) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, it explores effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. The chapter presents experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 1477-1488
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of players. In particular, we explore effects of information propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

When Shared Autonomous Electric Vehicles Meet Microgrids: Citywide Energy-Mobility Orchestration

2021 ◽  
Author(s):  
Wei Qi ◽  
Mengyi Sha ◽  
Shanling Li
Keyword(s):  
New York ◽  
Electric Vehicles ◽  
Problem Definition ◽  
Service Systems ◽  
Fleet Size ◽  
Mobility Service ◽  
Trade Offs ◽  
Self Sufficiency ◽  
Managerial Implications ◽  
Autonomous Electric Vehicles

Problem definition: We develop a crossdisciplinary analytics framework to understand citywide mobility-energy synergy. In particular, we investigate the potential of shared autonomous electric vehicles (SAEVs) for improving the self-sufficiency and resilience of solar-powered urban microgrids. Academic/practical relevance: Our work is motivated by the ever-increasing interconnection of energy and mobility service systems at the urban scale. We propose models and analytics to characterize the dynamics of the SAEV-microgrid service systems, which were largely overlooked by the literature on service operations and vehicle-grid integration (VGI) analysis. Methodology: We develop a space-time-energy network representation of SAEVs. Then, we formulate linear program models to incorporate an array of major operational decisions interconnecting the mobility and energy systems. To preventatively ensure microgrid resilience, we also propose an “N − 1” resilience-constrained fleet dispatch problem to cope with microgrid outages. Results: Combining eight data sources of New York City, our results show that 80,000 SAEVs in place of the current ride-sharing mobility assets can improve the microgrid self-sufficiency by 1.45% (benchmarked against the case without grid support) mainly via the spatial transfer of electricity, which complements conventional VGI. Scaling up the SAEV fleet size to 500,000 increases the microgrid self-sufficiency by 8.85% mainly through temporal energy transfer, which substitutes conventional VGI. We also quantify the potential and trade-offs of SAEVs for peak electricity import reduction and ramping mitigation. In addition, microgrid resilience can be enhanced by SAEVs, but the actual resilience level varies by microgrids and by the hour when grid contingency occurs. The SAEV fleet operator can further maintain the resilience of pivotal microgrid areas at their maximum achievable level with no more than a 1% increase in the fleet repositioning trip length. Managerial implications: Our models and findings demonstrate the potential in deepening the integration of urban mobility and energy service systems toward a smart-city future.

scholarly journals Influence of Increasing Electrification of Passenger Vehicle Fleet on Carbon Dioxide Emissions in Finland

2020 ◽  
Vol 12 (12) ◽  
pp. 5032 ◽  
Author(s):  
Antti Lajunen ◽  
Klaus Kivekäs ◽  
Jari Vepsäläinen ◽  
Kari Tammi
Keyword(s):  
Carbon Dioxide ◽  
Electric Vehicles ◽  
Carbon Dioxide Emissions ◽  
Passenger Vehicle ◽  
Estimation Model ◽  
Passenger Cars ◽  
Emission Analysis ◽  
The Future ◽  
Light Duty Vehicle ◽  
Vehicle Fleet

Different estimations have been presented for the amount of electric vehicles in the future. These estimations rarely take into account any realistic dynamics of the vehicle fleet. The objective of this paper is to analyze recently presented future scenarios about the passenger vehicle fleet estimations and create a foundation for the development of a fleet estimation model for passenger cars dedicated to the Finnish vehicle market conditions. The specific conditions of the Finnish light-duty vehicle fleet are taken into account as boundary conditions for the model development. The fleet model can be used for the estimation of emissions-optimal future vehicle fleets and the evaluation of the carbon dioxide emissions of transportation. The emission analysis was done for four different scenarios of the passenger vehicle fleet development in Finland. The results show that the high average age of the fleet and high number of older gasoline vehicles will slow down the reduction of carbon dioxide emissions during the next five to ten years even with a high adoption rate of electric vehicles. It can be concluded that lowering the average age, increasing biofuel mixing ratios, and increasing the amount of rechargeable electric vehicles are the most effective measures to reduce carbon dioxide emissions of the Finnish passenger vehicle fleet in the future.

Economic and environmental benefits of 3-wheeler electric vehicles during covid-19: A case study of Rajshahi, Bangladesh

2021 ◽  
pp. 38-44
Author(s):  
Md. Raquibul Hasan
Keyword(s):  
Air Quality ◽  
Labour Market ◽  
Electric Vehicles ◽  
Vital Role ◽  
Google Earth ◽  
Environmental Benefits ◽  
Industrial Emissions ◽  
Market Impacts ◽  
The Impact

This paper provides an insight into the labour market impacts of the COVID-19 crisis in Bangladesh, focusing on Rajshahi City Corporation. A survey was built to collect data about job switching nature before and during the crisis to shed light on the implications of COVID-19 on employment and earnings. The findings presented here indicate substantial labour market impacts both at the extensive and intensive margin, mainly due to the nature of the crisis's occupations. And the sufferers switch their jobs to 3-wheeler EVs industry as a driver or mechanic. Bus helper job was the most susceptible job during the pandemic, followed by garments. Due to the countrywide lockdown, emissions from vehicles were restricted, it was found that the air quality has been improved throughout the country during the lockdown. And 3-wheeler electric vehicles play a vital role to ease this issue. The study also assesses the impact of lockdown measures on air quality in Rajshahi. Four different air pollutants data from the google earth engine (NO2, SO2, CO, and O3) were analyzed. The study evaluated that the lockdown measures significantly reduced air pollution because of reduced vehicular and industrial emissions in Bangladesh.

Insights into the Impact of Social Networks on Evolutionary Games

2009 ◽  
pp. 317-331
Author(s):  
Katia Sycara ◽  
Paul Scerri ◽  
Anton Chechetka
Keyword(s):  
Game Theory ◽  
Social Networks ◽  
Evolutionary Game Theory ◽  
Information Diffusion ◽  
Large Population ◽  
Evolutionary Game ◽  
Evolutionary Games ◽  
Agent Based ◽  
The Social ◽  
The Impact

In this chapter, we explore the use of evolutionary game theory (EGT) (Nowak & May, 1993; Taylor & Jonker, 1978; Weibull, 1995) to model the dynamics of adaptive opponent strategies for a large population of pl ion propagation through social networks in evolutionary games. The key underlying phenomenon that the information diffusion aims to capture is that reasoning about the experiences of acquaintances can dramatically impact the dynamics of a society. We present experimental results from agent-based simulations that show the impact of diffusion through social networks on the player strategies of an evolutionary game and the sensitivity of the dynamics to features of the social network.

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