車載通訊網路是一種新興的網路型態，其具有在未來提高車輛安全及效率的潛力。由於在這種網路環境裡的車輛可移動範圍受到道路佈局及交通法規的限制，所以車輛可透過其實際的地理位置及電子地圖的幫助提升路由決策的效益。一般而言，車輛在移動時其移動方向及速度會導致網路連結不可靠，使得網路服務品質不穩定。為了解決上述的問題，在本論文中我們發展了ㄧ套協合式的道路資訊收集方法來達到道路的流量感知，進而提升車載通訊網路路由協定的效益。此方法主要透過合作的方式，動態的在各十字路口選擇一個適合的車輛做為訊息聚合點，以便收集道路資訊，而在道路上的車輛則幫忙傳遞道路資訊給各訊息聚合點讓這些資訊可快速的送達。但車輛在傳遞訊息時，訊息傳遞者不一定都會有接收者的地理位置。因此，當無法得知接收者地理位置時，我們透過車輛之間相互合作的方式協助訊息傳遞者找到接收者的實際地理位置，進而提升訊息傳遞的效能。一般來說，在監控交通狀況時，車輛的密度是一個可作為提高道路安全性和效率的重要指標。因此，獲得能真實反映道路狀況的道路密度不僅能提高資訊在路由時的效能，同時也能減少收集道路資訊時所需的時間。所以本論文提供了一個更能真實反映實際道路狀況的方法來提昇路由決策的效益。另一方面，在道路較為空曠的環境裡，訊息的傳遞可能會因為車輛稀少而失敗。在這種情況下車輛往往需要依靠車輛間相遇時才可分享或是幫忙傳遞訊息。而有些訊息可能有其時效性，因此在本論文中我們提供了可依據車輛移動軌跡的抽量模型及訊息的時效性來建構一個高效能協和訊息傳遞方法來傳遞受時效性限制的訊息。最後，經由實驗的結果顯示，本論文所提之方法在車輛密度較高或是車輛密度較稀疏的環境裡都能有效率的傳遞訊息。

The vehicular ad hoc network is an emerging paradigm that has the potential to improve the safety and efficiency of transportation in the future. Since the distribution and movement pattern of vehicles are constrained by road layouts and traffic regulations, digital maps and geographical locations of vehicles can be useful for making routing decisions. However, varying vehicle mobility often results in unreliable connectivity and consequent unstable service quality. To address the aforementioned problem, a cooperative information collection method was developed in this dissertation. This method dynamically selects the most appropriate vehicular nodes at junctions as information aggregators and nodes on road segments as information collectors to cooperatively collect hierarchical information. However, the location of the destination is not always available during data transmission. Thus, a cooperative destination discovery protocol is introduced to enable vehicles to cooperatively assist source vehicle to discover the position of the destination when the location of the destination is unobtainable. Generally, vehicle density is an important metric in monitoring traffic conditions to improve the safety and efficiency of roads. By obtaining reliable traffic density results that faithfully reflect actual road conditions not only improve routing performances, but also require less transmission overhead for the collection of traffic information. Thus, this dissertation introduced a more effective density estimation method that will reflect the real traffic situation to improve the effectiveness when making routing decisions. In sparse vehicular environments, connectivity among vehicles may significantly decrease the probability of information exchange among vehicles or sometimes it’s just simply not feasible due to lack of participants in such environment. In this situation, vehicles may share or exchange content only through opportunistic contact with one another. There are cases where some contents may need to be delivered to destinations within a specific time interval. To this end, this dissertation introduces a time-validity-constrained content delivery method that constructs an abstract model for the traveling behavior of each mobile node on the basis of the node’s travel records and adopts a high-performance cooperative content delivery scheme. The simulation results shows the methods proposed in this dissertation can be used to in both densely and sparsely environments.

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