Impact of ridesharing on operational efficiency of shared autonomous electric vehicle fleet

- Proposes a Tabu Search based optimization framework to simulate shared autonomous electric vehicles.
- Case study shows that allowing multiple occupants improves service rate and system savings.
- The average wait time per trip increases exponentially as ridesharing percentage increases.
- Compared to traditional ride-hailing service, the fleet size and the number of charging stations significantly reduce.
- Private vehicle ownership may reduce as vehicle capacity and range increase in the context of ridesharing operations.