Shared autonomous electric vehicle design and operations under uncertainties: a reliability-based design optimization ap
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RESEARCH PAPER
Shared autonomous electric vehicle design and operations under uncertainties: a reliability-based design optimization approach Ungki Lee 1 & Namwoo Kang 2
&
Ikjin Lee 1
Received: 30 July 2019 / Revised: 19 September 2019 / Accepted: 14 October 2019 # Springer-Verlag GmbH Germany, part of Springer Nature 2019
Abstract Shared autonomous electric vehicles (SAEVs) are a promising car-sharing service expected to be implemented in the near future. However, existing studies on the optimization of SAEV systems do not consider uncertainties in the SAEV systems, which may interfere with the achievement of the desired performance or objective. From the perspective of the company, a SAEV system should be designed to minimize the total cost while securing the targeted wait time of the customer, but uncertainties in the SAEV system can cause variation in the customer wait time, which can lead to inconveniences to customers and damage to the reputation of the company. Therefore, this study considers the uncertainties in a SAEV system and applies reliability-based design optimization (RBDO) to the design of the SAEV system to minimize the total cost of system design while satisfying the target reliability of the customer wait time. A comparison of the optimization results of various wait time constraints and probabilities of failure provides observations on applying RBDO to the design of a SAEV system. Furthermore, several insights can be obtained through various parametric studies. From this study, it is verified that RBDO can be successfully applied to the design of a SAEV system and a design framework for the SAEV system that can both lower the cost and ensure the reliability of the customer wait time is proposed. Keywords Shared autonomous electric vehicle (SAEV) . Reliability-based design optimization (RBDO) . Design and operations under uncertainties
1 Introduction Vehicle electrification is a promising way to reduce fuel consumption and address concerns about environmental pollution and greenhouse gas (GHG) emissions resulting from the use of fossil fuels in transportation systems (Fiori et al. 2016; Tu et al. 2016; Miao et al. 2019). Compared with a conventional vehicle, an electric vehicle (EV) can drive the same distance at Responsible Editor: Pingfeng Wang * Namwoo Kang [email protected] * Ikjin Lee [email protected] Ungki Lee [email protected] 1
Department of Mechanical Engineering, Korea Advanced Institute of Science and Technology, Daejeon 34141, South Korea
2
Department of Mechanical Systems Engineering, Sookmyung Women’s University, Seoul 04310, South Korea
approximately half the cost and reduce GHG emissions by 50% (Mak et al. 2013; Energy Saver 2015). Autonomous driving technology is expected to revolutionize transportation systems over the next few decades, providing customers with safe and low-stress transportation solutions (Litman 2014; Chen et al. 2017), reducing mobility costs (Bösch et al. 2017; Hyland and Mahmassani 2018), and improving transportation accessibility (Meyer et
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