An emergency storage battery (ESB) is an important asset to ensure the reliability and safety of complex technological systems. Even if an asset owner decides to replace a deteriorated ESB in expressway transportation systems , a lead time (LT) from ordering replacement parts to delivery is inevitable because the replacement parts cannot be stockpiled. During the LT, the ESB continues to deteriorate, i.e., the risk of deterioration continuously increases. If the LT has a non-negligible length, it is necessary to find intervention policies that appropriately consider the risk during the LT. In this study, we propose a methodology to derive optimal intervention policies by explicitly considering deterioration risk during the LT in a stochastic control framework. Specifically, the geometric Brownian motion is statistically estimated as the deterioration process of the ESB, and an optimization model is proposed to find the optimal intervention policy. The proposed methodology is applied to a case study on an expressway transportation system. In the case study, a sensitivity analysis is also performed to obtain practical implications through a life cycle cost (LCC) comparison. Our findings show that the proposed methodology can reduce the LCC by 5.49% compared with when the LT is not considered.