Finding an appropriate price using thousands of data points
It is not clear from your question if you are trying to predict value for many used cars as a function of different vehicle characteristics (like age of car, model, mileage) or predicting price of a single car.

Assuming the former (prediction using variables), you can set it up as a regression problem, where price is dependent variable and (age, model, mileage) are independent variables. Google "Boston housing price prediction" which is a similar application in different domain.

If you have only prices data (ignoring vehicle characteristics), you are looking for summary statistics. You can start with the mean (average) or median price. You can then it little more complex by modelling the price as some reasonable statistical distribution (normal or Poisson) and then take typical summary statistics on the distribution as estimate (say inter-quantile range).