There are natural synergies between shared autonomous vehicle (AV) fleets and electric vehicle (EV) technology, since fleets of AVs resolve the practical limitations of today's non-autonomous EVs, including traveler range anxiety, access to charging infrastructure, and charging time management. Fleet-managed AVs relieve such concerns, managing range and charging activities based on real-time trip demand and established charging-station locations, as demonstrated in this paper. This work explores the management of a fleet of shared autonomous (battery-only) electric vehicles (SAEVs) in a regional (100-mile by 100-mile) discrete-time, agent-based model. The dissertation examines the operation of SAEVs under various vehicle range and charging infrastructure scenarios in a gridded city modeled roughly after the densities of Austin, Texas. Results indicate that fleet size is sensitive to battery recharge time and vehicle range, with each 80-mile range SAEV replacing 3.7 privately owned vehicles and each 200-mile range SAEV replacing 5.5 privately owned vehicles, under Level II (240-volt AC) charging. With Level III 480-volt DC fast-charging infrastructure in place, these ratios rise to 5.4 vehicles for the 80-mile range SAEV and 6.8 vehicles for the 200-mile range SAEV. However, due to the need to travel while "empty" for charging and passenger pickup, SAEV fleets are predicted to generate an additional 7.1 to 14.0% of travel miles. Financial analysis suggests that the combined cost of charging infrastructure, vehicle capital and maintenance, electricity, insurance, and registration for a fleet of SAEVs ranges from $0.42 to $0.49 per occupied mile traveled, which implies SAEV service can be offered at the equivalent per-mile cost of private vehicle ownership for low-mileage households, and thus be competitive with current manually-driven carsharing services and significantly less expensive than on-demand driver-operated transportation services. The mode share of SAEVs in the simulated mid-sized city is predicted to be between 14 and 39%, when competing against privately-owned, manually-driven vehicles and city bus service. This assumes SAEVs are priced between $0.75 and $1.00 per mile, which delivers significant net revenues to the fleet owner-operator, under all modeled scenarios, assuming 80-mile-range EVs and remote/cordless Level II charging infrastructure and $10,000-per-vehicle automation costs.

The electrification of shared fleets offers numerous benefits, including the reduction of local emissions of pollutants, which leads to ecological improvements such as the improvement of air quality. Electric Vehicles in Shared Fleets considers a holistic concept for a socio-technical system with a focus on three core areas: integrated mobility solutions, business models for economic viability, and information systems that support decision-making for the successful implementation and operation of electric vehicles in shared fleets.In this book, we examine different aspects within these areas including multimodal mobility, grid integration of electric vehicles, shared autonomous electric vehicle services, relocation strategies in shared fleets, and the challenge of battery life of electric vehicles. Insights into the future of transport are provided, which is predicted to be shared, autonomous, and electric. This will require the expansion of the charging infrastructure to provide adequate premises for the electrification of transportation and to create market demand.

Nowadays, many cities are supplied with one or several fleets of shared vehicles as an alternative method for daily transportation. These fleets could be improved in many aspects if they employ autonomous or electric autonomous vehicles. Zero greenhouse gas (GHG) emission, fewer personnel requirements, automatic self-charge evaluation and process, and smooth driving are some of these improvements. This essay models a fleet comprised of shared electric autonomous vehicles (SEAV), giving one-way transportation service for short-distance travels. The case study of the area around Montreal Olympic Park is suggested to test the model's validity. In this regard, five stations are introduced on the streets surrounding the park. Different combinations of the fleet parameters are considered to generate 105 various scenarios. A multi-agent model is developed in the NetLog toolkit to simulate such a fleet under each scenario. The results show that a fleet of 20 vehicles of a 50km range with 30 parking spots can meet the demand under all considered customer arrivals frequencies with 90% or above performance rates. Another finding from the results suggests that the impact of different ranges on the fleet's performance compared to the fleet size and demand probability is almost negligible. The last part investigates the number of parking spots on fleet performance. The results suggest that the fewer the number of parking spots, the fewer rejected customers but at the same time, the higher empty travels.

This edited book comprises papers about the impacts, benefits and challenges of connected and automated cars. It is the third volume of the LNMOB series dealing with Road Vehicle Automation. The book comprises contributions from researchers, industry practitioners and policy makers, covering perspectives from the U.S., Europe and Japan. It is based on the Automated Vehicles Symposium 2015 which was jointly organized by the Association of Unmanned Vehicle Systems International (AUVSI) and the Transportation Research Board (TRB) in Ann Arbor, Michigan, in July 2015. The topical spectrum includes, but is not limited to, public sector activities, human factors, ethical and business aspects, energy and technological perspectives, vehicle systems and transportation infrastructure. This book is an indispensable source of information for academic researchers, industrial engineers and policy makers interested in the topic of road vehicle automation.

The climate crisis requires substantial shifts in the transportation and energy sectors. Greater use of intermittent renewable energy sources requires demand- and supply-side flexibility in electricity markets. Deployment of on-demand, shared, fully automated, and electric vehicle (SAEV) fleets offers natural synergies in meeting such challenges. Smart charging (and discharging) of electric vehicles (EVs) can shift loads away from peak demand to reduce, or at least delay, expensive infrastructure upgrades, while fleet managers lower emissions and power costs in real time. This dissertation explores (1) optimization-based idle-vehicle dispatch strategies to improve SAEV fleet operations in the Austin metro, (2) integration of power and transportation system (EV-use) modeling across the Chicago metro area, and (3) a case study of demand response participation and charging station siting in a region with multiple energy suppliers. Optimizing SAEV repositioning and charging dispatch strategies jointly lowered rider wait times by 39%, on average, and increased daily trips served per SAEV by 28% (up to 6.4 additional riders), compared to separate range-agnostic repositioning and heuristic charging strategies. Joint strategies may also decrease the SAEV fleet’s empty travel by 5.7 to 12.8 percentage points (depending on geofencing and charging station density). If fleets pay dynamic electricity prices and wish to internalize their upstream charging emissions damages, a new multi-stage charging problem is required. A day-ahead energy transaction problem provides targets for a within-day idle-vehicle dispatch strategy that balances charging, discharging, repositioning, and maintenance decisions. This strategy allowed the Austin SAEV fleet to lower daily power costs (by 15.5% or $0.79/day/SAEV, on average) while reducing health damages from generation-related pollution (2.8% or $0.43/day/SAEV, on average). Fleet managers obtained higher profits ($8 per SAEV per day) by serving more passengers per day than with simpler (price-agnostic) dispatch strategies. This dissertation also coupled an agent-based travel demand simulator (POLARIS) with an electricity grid model (A-LEAF) to evaluate charging impacts on the power grid across seasons, household-EV adoption levels, SAEV mode shares, and dynamic ride-sharing assumptions in 2035 for the Chicago, Illinois metro. At relatively low EV penetration levels (8% to 17%), an increase in electricity demand will require at most 1 GW of additional generation capacity. Illinois’ transition to intermittent variable renewable energy (VRE) and phase-out of coal-fired power plants will likely not noticeably increase wholesale power prices, even with unmanaged personal EV charging at peak hours. However, wholesale power prices will increase during peak winter hours (by +$100/MWh, or $0.10/kWh) and peak summer hours (+$300/MWh) due to higher energy fees and steep congestion fees on Illinois’ 2015-era transmission system. Although a smart-charging SAEV fleet uses wholesale prices to reduce electricity demand during peak hours, spreading charging demand in hours before and after the baseline peak creates new "ridges" in energy demand, which raise prices for all. These simulation results underscore the importance of investing in transmission system expansion and reducing barriers to upgrading or building new transmission infrastructure. If vehicles and chargers support bidirectional charging, SAEVs can improve grid reliability and resilience at critical times through demand response (DR) programs that allow load curtailment and vehicle-to-grid (V2G) power. Scenario testing of DR requests in Austin ranging from 1 MW to 12 MW between 4 and 5 PM reveals break-even compensation costs (to SAEV owners) that range from $86/kW to $4,160/kW (if the city imposes unoccupied travel fees), depending on vehicle locations and battery levels at the time of the DR request. Smaller requests can be met without V2G by reducing charging speeds, usually from 120 kW speed to Level 2 charging. Finally, an incremental charging station heuristic was designed to capture differences in land costs and electricity rate structures from different energy suppliers in the same region. The daily amortized costs over 10 years of hardware, installation, and land costs were estimated to be nearly $0.30/SAEV/day, compared to $0.38/SAEV/day with a baseline heuristic strategy ignoring land costs and marginal costs of expanding existing sites. SAEV charging costs showed no substantial difference between heuristic strategies, although combined daily energy fees were more expensive at $0.43/SAEV/day. Including land costs in charging station investment heuristics is necessary, and modelers should include spatially varying energy prices since the average daily per-vehicle energy costs are higher than the physical station costs. Taken together, this dissertation’s contributions offer hope for a decarbonizing world that provides affordable, clean, and convenient on-demand mobility

Front Cover -- About Island Press -- Subscribe -- Title Page -- Copyright Page -- Contents -- Preface -- Acknowledgments -- 1. Will the Transportation Revolutions Improve Our Lives-- or Make Them Worse? -- 2. Electric Vehicles: Approaching the Tipping Point -- 3. Shared Mobility: The Potential of Ridehailing and Pooling -- 4. Vehicle Automation: Our Best Shot at a Transportation Do-Over? -- 5. Upgrading Transit for the Twenty-First Century -- 6. Bridging the Gap between Mobility Haves and Have-Nots -- 7. Remaking the Auto Industry -- 8. The Dark Horse: Will China Win the Electric, Automated, Shared Mobility Race? -- Epilogue -- Notes -- About the Contributors -- Index -- IP Board of Directors

This edited open access book gives a comprehensive overview of small and lightweight electric three- and four-wheel vehicles with an international scope. The present status of small electric vehicle (SEV) technologies, the market situation and main hindering factors for market success as well as options to attain a higher market share including new mobility concepts are highlighted. An increased usage of SEVs can have different impacts which are highlighted in the book in regard to sustainable transport, congestion, electric grid and transport-related potentials. To underline the effects these vehicles can have in urban areas or rural areas, several case studies are presented covering outcomes of pilot projects and studies in Europe. A study of the operation and usage in the Global South extends the scope to a global scale. Furthermore, several concept studies and vehicle concepts on the market give a more detailed overview and show the deployment in different applications.