First off, having multiple sensors and integration of that data is never a bad thing in robotics; in fact, it is almost a necessary thing. More information can mean better decisions by the system driving the vehicle. More sensors can help fill in things other sensors can't "see".

That said, you bring up a good point: Humans do a pretty good job driving vehicles with only a pair of eyeballs (usually), ears, and "feel" (I'm not sure how to put this last one, but a good driver tries to stay and feel "as one" with the vehicle, getting information about the road, various forces internal and external about the car, etc - in order to drive it properly and in control while making various maneuvers). So why couldn't we do the same with a self-driving vehicle?

Well - the truth is - we can:

https://devblogs.nvidia.com/parallelforall/deep-learning-sel...

https://images.nvidia.com/content/tegra/automotive/images/20...

I mention that paper so often in these kinds of discussions, that I am sure people are getting sick of it. Note that in that paper, only a single camera is used - like driving with one eye closed (or blind in one eye), yet it still was able to do so properly. Part of Nvidia's purpose here is to advance self-driving vehicles, but they also are trying to sell self-driving vehicle manufacturers on their tech as well:

http://www.nvidia.com/object/drive-px.html

If the need for expensive and exotic LIDAR systems can be overcome, and simpler systems like cameras and radar can instead be used, it will both be a cheaper way to manufacture these cars, as well as being more reliable (as the article noted, it's one thing to make a LIDAR - making a reliable LIDAR for automotive use over 100s of thousands of miles/kilometers is a different ball-o-wax - but manufacturers already have experience with making radar and cameras for vehicles robust).

For another take on using cameras for autonomous navigation - there's this project using high-speed winged drones (and completely open source - including the drone design files):

http://spectrum.ieee.org/automaton/robotics/drones/mit-drone...

https://github.com/andybarry/flight

That one only uses a couple of small cameras for stereo vision.

These two projects (and others if you care to search) both show that such a system is possible; we probably don't need LIDAR for the majority of driving scenarios. Radar can probably cover other areas, and you mention the concept of humans using hearing - but honestly I am not aware of any self-driving vehicle research on that potential kind of sensing, but if none exists, it seems like it might be a fascinating and promising area of study for someone! Audio sensors would also be another one of those "simple and robust" sensors for automobile usage that manufacturers would like.

That said: If they can make a simple but robust LIDAR system, with no moving parts (such designs do exist, like flash LIDAR, for instance), and a low-cost (that part is key), having that on a vehicle certainly can't hurt. There are areas (particularly at night, or in inclement weather, or in other low-visibility situations) where a camera alone will have a similar trouble as a human would (though I wonder if a camera operating at other wavelengths (FLIR, Near-IR, and Near-UV for instance) could help?)

In those situations, having a LIDAR might be the key to a safer driving experience for a self-driving vehicle, whereas a human without that ability might make a wrong (and potentially fatal) decision.