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Private Autonomous Vehicles (PAV) and Shared Autonomous Vehicles (SAV) are known to improve safety, mobility, roadway capacity, driver productivity and reduce parking costs (due to better utilization of space and self-parking to less expensive spots). However, the increased vehicle miles traveled (VMT), might increase overall emission production, system travel time, and operating costs. Also, the purchase price of autonomous vehicle (AV) is expected to be higher than that of human-driven (conventional) vehicles. A multi-objective mathematical model is proposed to minimize the purchase and operating costs, time spent, and emission production. The proposed model captures the tradeoff between the benefits of increased mobility, reduction in the value of travel of time (VOTT), efficient driving pattern, and the negative impacts of increased VMT, ownership cost due to the adoption of AVs. The proposed framework assists with the development of simplified adoption models that can be used by the policymakers and/or investors. SAVs would be the optimal solution if the replacement rate or CO 2  costs are significantly low, or CO costs are sufficiently high. SAVs can also be the optimal solution if the travel time is used efficiently, or the purchase price is below certain relative threshold while minimizing system cost. Considering the private mobility system, PAVs can be the optimal solution only if the on-board amenities are improved, lifetime mileage is increased, AV technology is installed in luxurious cars, and is being adopted by people with high VOTT.

Multi-objective framework for optimum configuration of human-driven and shared or privately owned autonomous vehicles