A Life Cycle Cost Analysis Approach for Emerging Intelligent Transportation Systems with Connected and Autonomous Vehicles

Gao, Jingqin; Ozbay, Kaan; Zuo, Fan; Kurkcu, Abdullah · 2017 · ROSA P / Connected Cities for Smart Mobility toward Accessible and Resilient Transportation Center (C2SMART)

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Summary

This paper addresses the inadequacy of traditional Life Cycle Cost Analysis (LCCA) methods when applied to technology-oriented Intelligent Transportation Systems (ITS), particularly those involving Connected and Autonomous Vehicles (CAVs). While LCCA is a standard tool for evaluating conventional infrastructure like pavements and bridges, the authors argue that ITS projects possess distinct characteristics that require a modified analytical approach. The study is motivated by the rapid deployment of CAV technologies and the need for transportation agencies to accurately assess the cost-effectiveness of these emerging systems, which differ from traditional assets in terms of inflation behavior, uncertainty, out-of-pocket costs, technical obsolescence, and inventory management requirements. To address these challenges, the authors propose a novel conceptual ITS LCCA framework. This framework incorporates specific adjustments for ITS characteristics, including the use of component-specific inflation rates rather than general economic indices, and the integration of system effectiveness metrics based on Reliability, Availability, Maintainability, and Capability (RAMC). The methodology also includes modules for obsolescence risk management and stochastic spare parts inventory control to minimize downtime costs. To quantify user costs—specifically traffic delay, vehicle operation, and crash risk—the authors employed a simulation-based approach using the open-source microsimulation software SUMO, coupled with Veins and OMNeT++ for communication simulation. They developed hypothetical failure scenarios for On-Board Units (OBU) and Roadside Units (RSU) to estimate the economic impact of equipment downtime in a connected vehicle environment. The findings reveal that ITS components exhibit divergent inflation trends compared to general consumer and producer price indices; specifically, electronic and communication components show a downward cost trend, while labor and construction costs rise. The simulation results demonstrate that equipment failures significantly increase user costs. For instance, a 30% failure rate in OBUs resulted in a 430.6% increase in traffic delay costs and a 370.0% increase in vehicle operation costs. RSU failures had an even more pronounced impact, with a 20% downtime causing a 279.6% increase in delay costs. Crash risk costs showed mixed results at the network level but increased significantly at local link levels. The study confirms that simulation-based methods are viable for quantifying user costs in the absence of historical field data for CAVs. The significance of this work lies in providing a structured framework for transportation agencies to evaluate the economic feasibility of ITS investments more accurately. By accounting for unique factors like negative inflation for technology components and the high sensitivity of user costs to equipment availability, the proposed approach offers a more realistic assessment of life cycle costs. The authors conclude that this framework supports better decision-making for sustainable transportation systems and suggests future work should incorporate Monte Carlo simulations and real-world field data to refine probabilistic cost estimates.

Key finding

ITS equipment failures significantly increase traffic delay and vehicle operation costs, with RSU failures having a more pronounced impact than onboard unit failures, while inflation rates for wireless telecommunications and electronic components trend downward contrary to general consumer price indices.

Methodology

modeling

Provenance

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Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

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• v2x connected vehicle