R&D and deployment valuation of intelligent transportation systems : a case example of the intersection collision avoidance systems

Compared with investments in the conventional infrastructure, those in Intelligent Transportation Technology (ITS) include various uncertainties. Because deployment of ITS requires close public-private partnership, projects concerning the R&D and deployment of ITS technology involve project risks and market risks induced by both the public and private sector. This characteristic makes it difficult to evaluate the value of the project through traditional valuation method such as the benefit cost analysis (BCA) or the discounted cash flow (DCF) method. To address the difficulty, this thesis proposes two appropriate valuation methodologies for R&D and deployment of ITS: decision analysis and "hybrid real options" analysis that combines decision analysis and real option analysis. This thesis applies the proposed methodologies to a case example of the ongoing R&D and deployment project to reduce the automobile crashes at intersection under public-private partnerships. The proposed systems in the project consist of two conflicting concepts; one depends on user acceptance of in-vehicle ITS technology employed, and the other one does not require user acceptance of this ITS technology.