I have in the past offered advice in the comp.ai.games news group re: AI control of vehicles. Here are a few short notes based on some experience that I have had. I have had the good fortune of getting to spend a fair amount of time (both on my own, and while being paid) writing code to control vehicles in games, etc.:

* Writing example code for my book AI Agents in Virtual Reality Worlds
* Working on the Indy 500 car simulation system at SAIC. I actually worked on the motion platform control, network programming, and sound system software. For this project, you always raced against other people, also in simulators.
* At Angel Studios working on 2 Nintendo games and a PC-based hover craft racing game.

Anyway, I do have some advice on how to write AI driving opponents:

The first thing that you want to do is to define data structures for navigational "way points" that AI vehicles follow and simply have the vehicles move between these "way points". If possible, AI controlled vehicles should use the same physics simulation code as the player's vehicle (at least when the AI vehicle is close and in the player's field of view).

After your AI controlled vehicles can move along using "way points", then, based on the game theme, add logic for detecting the proximity of the player's vehicle (e.g., AI vehicle might swerve into the player's vehicle under specified circumstances), etc. Do not bother with complex behavior if a vehicle is not in the rendered scene for a player.

It should be fairly easy to get the code running to follow way points, but that is definitely your first step. Combining driving logic control with "lerping" between weigh points will also make the vehicles look a lot more realistic while more or less keeping them where you want them.

When possible, your movement logic should depend heavily on where the AI vehicle is in the player's field of view. For efficiency, it might be expedient to use simple finite state machines for the control logic. However, I have experimented (again, see my book) with using expert systems, neural networks, and genetic algorithms. For Java programmers, my book "Intelligent Java Applications" contains a (not practical, but fun!) example of using genetic algorithms to train simple control programs in an "asteroids" style arcade game.

Good luck, and have fun!