Traffic state prediction provides key information for intelligent transportation systems (ITSs) for proactive traffic management, the importance of which has become the reason for the tremendous number of research papers in this field. Over the last few decades, the decomposition-reconstruction (DR) hybrid models have been favored by numerous researchers to provide a more robust framework for short-term traffic state prediction for ITSs. This study surveyed DR-based works for short-term traffic state forecasting that were reported in the past circa twenty years, particularly focusing on how decomposition and reconstruction strategies could be utilized to enhance the predictability and interpretability of basic predictive models of traffic parameters. The reported DR-based models were classified and their applications in this area were scrutinized. Discussion and potential future directions are also provided to support more sophisticated applications. This work offers modelers suggestions and helps to choose appropriate decomposition and reconstruction strategies in their research and applications.

During the early stages of autonomous vehicle (AV) adoption, traditional human-driven vehicles (HVs) and AVs will share urban roads—potentially diminishing the capacity benefits of AVs; thus, dedicated infrastructure strategies, such as AV-exclusive lanes and AV/Toll (AVT) lanes, have been proposed in the literature. While these approaches enhance overall travel efficiency in mixed traffic networks, they often neglect social equity concerns. In particular, the benefits of dedicated infrastructure are largely felt by AV users, while HV users experience a disproportionate increase in equilibrium travel time, negatively impacting social equity. This study optimizes AVT lane toll rates to balance efficiency and equity, ensuring a fair distribution of transportation impacts across user groups. New measurement formulas are introduced to quantify spatial and social equity based on disparities in generalized equilibrium travel costs across different origin–destination pairs and travel modes after an AVT tolling scheme. An equitable AVT tolling model, grounded in fuzzy utility theory, is developed, and a numerical example demonstrates its effectiveness in addressing spatial and social equity concerns in AVT lane tolling contexts.