傳統交通量分派主要通過求解使用者均衡模式來預測路網中各路段的車流量，其中使用者均衡的基本定義為用路人不能透過單方面改變其使用路徑來減少其旅行成本。換句話說，每對起訖點中，用路人使用之路徑的旅行成本，皆小於或等於未被使用之路徑的旅行成本。傳統使用者均衡假設用路人掌握路網中所有路徑資訊(距離、時間、成本等)。但在現實生活中，受限於用路人有限的路網資訊，他們所會考慮的路徑是有限，意即用路人只在特定路徑集合中選擇其使用路徑。為了因應現實狀況，本論文提出新的使用者均衡模式，包含路徑集合使用者均衡(N-path user equilibrium)以及彈性需求路徑集合使用者均衡(N-path user equilibrium with elastic demand)兩個模式。在模式中，用路人只能在特定路徑集合中尋找成本最低的路徑作為其使用路徑。本論文除了介紹數學模式、推導最佳化條件(Optimality condition)外，並且驗證傳統使用者均衡是NPUE以及NPUEED其中一個特例，以及均衡解為唯一(Uniqueness)解。為了有效對模式進行求解，我們分別發展以路徑和路段為基礎的演算法，並測試兩者於不同規模路網中之績效。研究結果發現，當用路人可選擇的路徑增加，新的均衡解會逐漸趨向傳統的均衡解，某些狀況下還會導致運輸系統總旅行時間上升，由此可知提供用路人道路資訊不一定有利於整體運輸系統，相反的有可能弊大於利。

The traditional trip-based approach to transportation modeling has been employed for the past decade. The last step of the trip-based modeling approach is traffic assignment, which has been typically formulated as a user equilibrium (UE) problem. In the conventional perspective, the definition of UE traffic assignment is the condition that no road user can unilaterally change routes to reduce their travel time. An equivalent definition is that the travel times of all the used paths between any given origin-destination pair are equal and less than those of the unused paths. The underlying assumption of the UE definition is that road users have full information on the available transportation paths and can potentially use any path if the currently used path is overly congested. However, a more practical scenario is that each road user has a limited path set within which she/he can choose routes from. In this new scenario, we call the resulting user equilibriums N-path user equilibrium (NPUE) and N-path user equilibrium with elastic demand (NPUEED), in which each road user has only N paths to select from when making route choices in the network. We introduce two new formulations of the NPUE and NPUEED. Next, we derive optimality conditions based on these formulations. Different from traditional modeling framework, the constraints of the proposed model are of linear form, which makes them possible to solve the problem with conventional convex programming techniques. We also show that the traditional UE is a special case of an NPUE (NPUEED) and prove the uniqueness of the resulting flow pattern of the NPUE (NPUEED). To efficiently solve this problem, we devise path-based and link-based solution algorithms. The proposed solution algorithms are empirically applied to networks of various sizes. Numerical results demonstrate that NPUE (NPUEED) results can differ significantly from UE results depending on the number of paths available to road users. In addition, we observed an interesting phenomenon, where increasing the number of paths available to road users can sometimes decrease the overall system performance due to their selfish routing behaviors. This paradox demonstrates that network information should be provided with caution, as such information can do more harm than good in certain transportation systems.

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