## 2 Literature Review  
TDM is a promising and cost-effective approach to alleviating traffic congestion. TDM aims to guide and alter residents' travel habits through various measures, including regulation, pricing, planning, and persuasion [15]. These interventions can be divided into a punitive \"stick\" and incentivizing \"carrot\", alternatively conceptualized as \"push\", and \"pull\" factors within the TDM paradigm. The \"push\" or \"stick\" strategies mainly impose certain penalties on road users to reduce peak-period travel, whereas the \"pull\" or \"carrot\" strategies focus on providing various incentives to encourage the public to consider and adopt more sustainable travel modes [16]. Research by [PERSON] et al. [17] indicates that both penalty-based and incentive-based TDM strategies can effectively promote a shift toward sustainable travel behaviors among residents. Some \"push\" strategies, such as congestion pricing and tradable credit schemes, have been proven feasible and efficient, especially in reducing traffic congestion and vehicular emissions [18,19]. However, these penalty-based traffic demand management (PBTDM) strategies often face public resentment and resistance due to the additional economic burden they impose on citizens. More critically, these strategies can potentially trigger social equity issues, especially for low-income groups facing increased economic pressure. Studies suggest that the popularity of congestion pricing is significantly constrained by factors such as residents' acceptance, fairness, and income distribution [20,21]. Diverging from the PBTDM paradigm, incentive-based traffic demand management (IBTDM) hinges on the allocation of rewards, ranging from monetary inducements to vouchers and subsidized travel fares, to entice commuters towards more sustainable travel modes [22]. Evidencesuggests that IBTDM is more palatable to policy-makers and possesses the latent capacity to catalyze a shift in travel behavior in favor of sustainability [23]. The \"Spitsmijden\" experiment in the Netherlands exemplifies the successful deployment of IBTDM, where commuters were incentivized to avoid peak travel times, leading to a 60% reduction in peak-hour traffic [24]. Similarly, the \"Metropia\" mobile application, which offered personalized incentives and predictive travel-time information, motivated 35% of its users to adjust their travel schedules and paths, resulting in a 20% reduction in travel times for those who modified their patterns [25]. These examples highlight the potential effectiveness of incentive-based strategies in reducing congestion and encouraging sustainable travel [26]. As a novel TDM strategy, the implementation mechanism of the TRS is shown in Figure 1. By mandatorily allocating the total travel volume on extremely congested urban roads, such as expressways or major commuter corridors during specific peak hours, the number of vehicles allowed on these roads is regulated. Travelers can reserve their routes and timeslots in advance on a public reservation platform. Integrating technology and management strategies, TRS meticulously modulates the spatial-temporal right-of-way of vehicles. It aims to alleviate the discrepancies between traffic supply and demand, maximize the utility of road resources, and thereby enhance the overall efficiency of the transportation system. It can significantly reduce urban traffic congestion, optimize the urban ecological environment, and enhance the satisfaction associated with citizens' commuting experiences. Notably, TRS aligns well with current concepts of Intelligent Transportation and Mobility-as-a-Service (MaaS), underscoring its significant value and broad potential in future urban traffic management. To some extent, TRS embodies a \"push\" strategy, aspiring to attenuate or redistribute peak traffic volume via the imposition of restrictive conditions, thus alleviating congestion. This approach shares its foundational principles with other \"push\" strategies, which sway commuters' decisions through restrictive or penal measures.