## 5 Conclusions  
This paper introduced a strategic blend of incentives and penalty mechanisms, establishing an agent-based multi-objective optimization model to formulate the optimal implementation plan for TRS. It delved into the repercussions of diverse incentives and penalty mechanisms on modifying departure times, the transition between travel modes, and the consequential impacts on a broad spectrum of stakeholders. This study has several contributions: (1) It stands out as one of the few data-driven studies that specifically model and assess TRS in the context of congested urban roads; (2) diverging from most of the extant literature, this study constructs a more comprehensive multimode urban transportation framework that encompasses three basic travel modes and two P+R modes. This more realistically portrays the urban transportation network and captures the travelers' choice behaviors; (3) by incorporating a mix of incentives and penalties, the paper enhances the applicability and effectiveness of TRS in urban road scenarios; and (4) the ABM is used to simulate the heterogeneous behaviors of users with different time values within the reservation system to capture the dynamic decision-making processes of travelers regarding their travel times and modes, offering valuable insights into how individual choices impact the broader traffic system. The results show: (1) Introducing incentives and penalty mechanisms significantly increased the income of the transportation system by 17.26% and decreased the travel costs by 2.67%; (2) after implementing the TRS, the traffic performance and the spatial-temporal distribution of congestion in the road network were significantly improved. Specifically, with the introduction of the reward and punishment mechanism, the average speed, road saturation, and network traffic volume improved by 6.7%, 9.3%, and 3.7%, respectively; and (3) after introducing the reward and punishment mechanism, the proportion of users participating in reservation travel increased by 48.5%, and the willingness of travelers to adjust their travel times significantly increased. Heterogeneous travelers with different time values exhibit significant differences in their responses to the TRS. The results and conclusions of this study have theoretical and practical implications for constructing a sustainable urban transportation system. Theoretically, this study offers a comprehensive understanding of the TRS in the context of urban congested roads. Such an insight paves the way for future research to delve deeper into nuanced transportation models, incorporating varying modes and user preferences. At the practical level, by showing the TRS's capability to decrease private car usage and boost public transit ridership, this study underscores the practical potential of such strategies in shaping more sustainable and environmentally friendly urban transportation choices. These findings can guide the design of tailored transportation strategies that cater to diverse user segments, ensuring maximum impact and acceptability. One of the primary limitations of this study is the reliance on virtual simulation experiments for the case analysis. Although this approach provided a controlled environment for testing the TRS and its impacts, it may not capture the complexities and unpredictability of real-world urban transportation systems. Like many studies, this study had to make certain assumptions to make the modeling and evaluation feasible. While these assumptions are grounded in theoretical frameworks, they may not encompass all possible variables or scenarios in real-life settings. Based on the basic insights from this study, future research can apply the developed models and strategies in real-world road transportation systems. This would validate the TRS's efficacy and provide tangible results that can guide urban planners and policymakers. **Author Contributions:** Conceptualization, H.C. ([PERSON]); Methodology, H.C. ([PERSON]); Software, R.Z. ; Investigation, R.Z.