近年來大家對於汽車不只是追求操控上的性能，對於安全性的意識也提高許多，各大車廠也紛紛亟欲開發先進駕駛輔助系統(Advanced Driver Assistance System, ADAS)來提升汽車的安全性。先進駕駛輔助系統最重要的功能就是在發生危險情況之前發出警示與輔助駕駛，以降低交通意外發生。
本論文使用影像處理的方式來完成前車距離估測。本論文提出一種區分前方光線是否充足的方法，利用當前車道線找出天空區塊，接著判斷天空區塊內光線是否充足。
車輛辨識上，光線充足時使用車輛底部陰影和後方水平保險桿特徵；在光線不足的情況下使用車輛的兩個紅色後車燈特徵。最後在距離估測上本論文提出新的方法，此方法有別於以往基於車道寬度比例或基於車輛在影像中高度位置比例的方法，先將影像中每個高度像素點所對應的實際距離事先建立參照資料，當找到車輛位置時將參照資料對應出實際估測距離，在計算速度、距離準確度皆比以往文獻所提出方法還要好。
本論文所提出之方法經19種高速公路特殊情況的行車影像測試後，目前測試結果都能正確估測出前車車距，只有在下雨時經過告示牌下方會產生光線辨識錯誤，導致車輛辨識錯誤和下雨時經過水泥混凝土路面時會產生水霧造成影像不清導致車輛辨識錯誤。

In recent years, people have not only pursues automobile performance but also increases their awareness of safety. Major car manufacturers have also been eager to develop Advanced Driver Assistance Systems (ADAS) to enhance the safety of automobiles. The most important function of an ADAS is to issue warnings and assist driving before a dangerous situation occurs in order to avoid traffic accidents.
In this thesis, the image processing methods are used to estimate the distance of the preceding vehicle and a method is proposed to decide whether the front has sufficient light. The lane line is used to find the sky block and then determine if there is enough light in the sky block.
In vehicle detection, when lighting is sufficient, the shadow of a vehicle and the rear horizontal bumper are used for detection. The vehicle's two red rear lights are used as a base in low light conditions
Finally, in distance estimation, this thesis proposes a novel method different from previous methods based on the ratio of lane width. The proposed method is based on the proportion of height position of the vehicle in a image in order to improve system accuracy and processing speed.
The experiment conducted in this thesis is based on 19 driving images taken in highways under various circumstances. In the experiment, the light recognition error took place only when highway sign board and windshield wiper are both located in the light detection area when it is raining.. Fog causes unclear images and therefore results in vehicle recognition errors either.

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