Exploring the Financial Implications of Operating a Shared Autonomous Electric Vehicle Fleet in Zurich

Richter, Maximilian A.; Hess, Johannes; Baur, C; Stern, Raphael

doi:10.1016/j.urbmob.2021.100001

Cited by 3 publications

(5 citation statements)

References 28 publications

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“…The shared services are merged /d7/ into the SAV service. AVs communicate with each other [31,32] and the mobility management center /d4/; the service is predictable and reliable which may enhance the willingness to use the service and profitability [33].…”

Section: Discussionmentioning

confidence: 99%

“…(e) Unfair advantage -Strong partnerships /e3/ among stakeholders imply a competitive advantage in the mobility market as the development of an AV fleet may be cost-prohibitive [21,34]; small fleets might rise profitability by reaching high turnover and cheaper operational assets [33]. Fewer vehicles are enough to supply the same demand if barriers to pooling are overcome [35,36].…”

Section: Discussionmentioning

confidence: 99%

“…Fewer vehicles are enough to supply the same demand if barriers to pooling are overcome [35,36]. The capacity utilization of vehicles in space and time /e4/generates fewer empty travelled kilometres when serving demand with the pooling option [33].…”

Section: Discussionmentioning

confidence: 99%

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Business Model for Shared Autonomous Vehicles Mobility Services

2024

Teh. vjesn.

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We propose a business model (BM) for mobility services based on shared autonomous vehicles (SAVs) anticipating the changes and opportunities for the current shared mobility service companies in updating their BMs to consider the AV technology. We have analysed the service characteristics of the current shared mobility services-taxi, ride-sourcing, ride-sharing, car rental, peer-to-peer car-sharing, and business-to-consumers car-sharing-and accordingly we determined how they would change when AVs are implemented into these services. The Lean Canvas is used to prepare the new BM, assuming the convergence of the current shared mobility services' BMs. We found that a customized travel fee and involvement of private AV owners in the service will alter revenue streams and customer segments, but modifications of key metrics and channels are not needed. According to the elaborated results, shared mobility companies can determine alterations in their BMs, strategy, and targets.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

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Business Model for Shared Autonomous Vehicles Mobility Services

2024

Teh. vjesn.

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“…Combining the upward trend of vehicle electrification and the promise of automation comes SAEVs [26,27]. A regional, discrete-time, agent-based model was proposed to explore the management of a fleet of SAEVs and the results indicated that SAEVs can serve nearly all requests with an average response time between 7 and 10 min [2]. A novel agent-based simulation framework was developed for electric vehicles by researchers considering the queuing issue in the fast charging stations [28].…”

Section: Previous Studiesmentioning

confidence: 99%

“…Shared autonomous vehicles (SAVs), as a new mode of transportation that combines the sharing economy and autonomous driving technology, have gained significant attention from both commercial and academic communities [1,2]. Many scholars believe that SAVs will revolutionize the future of urban transportation and provide much more convenient, safer, and economical mobility services [3,4].…”

Section: Introductionmentioning

confidence: 99%

Exploring the Impact of Charging Behavior on Transportation System in the Era of SAEVs: Balancing Current Request with Charging Station Availability

Zhu,

Ye,

Yan

et al. 2024

Systems

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Shared autonomous electric vehicles (SAEVs) can offer safer, more efficient, and more environmentally friendly real-time mobility services with advanced autonomous driving technologies. In this study, a multi-agent-based simulation model considering SAEVs’ vehicle range and charging behavior is proposed. Based on real-world datasets from the Luohu District in Shenzhen, China, various scenarios with different fleet sizes, charging rates, and vehicle ranges are established to evaluate the impact of these parameters on parking demand, charging demand, vehicle miles traveled (VMT), and response time in the era of SAEVs. The results show there would be much more charging demand than parking demand. Moreover, a larger fleet size and longer vehicle range would lead to more parking demand, more charging demand, and more VMT while increasing the charging rate can dramatically reduce the charging demand and VMT. Average response time can be reduced by increasing the fleet size or the charging rate, and a larger vehicle range leads to longer response time due to the longer time spent recharging. It is worth noting that the VMT generated from relocating from the previous request destination to the origin of the upcoming request accounts for nearly 90% of the total VMT, which should be addressed properly with appropriate scheduling. A charging policy considering current requests and the availability of charging stations was proposed and verified in terms of reducing the response time by 2.5% to 18.9%.

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How Will Autonomous Vehicles Increase Ease of Life?

Patel,

Ljepava

2024

Smart Innovation, Systems and Technologies

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Exploring the Financial Implications of Operating a Shared Autonomous Electric Vehicle Fleet in Zurich

Cited by 3 publications

References 28 publications

Business Model for Shared Autonomous Vehicles Mobility Services

Business Model for Shared Autonomous Vehicles Mobility Services

Exploring the Impact of Charging Behavior on Transportation System in the Era of SAEVs: Balancing Current Request with Charging Station Availability

How Will Autonomous Vehicles Increase Ease of Life?

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