New algorithm may help autonomous vehicles navigate narrow, crowded streets

It is a scenario familiar to anyone who has driven down a crowded, narrow street. Parked cars line both sides, and there isn’t enough space for vehicles traveling in both directions to pass each other. One has to duck into a gap in the parked cars or slow and pull over as far as possible for the other to squeeze by.

Drivers find a way to negotiate this, but not without close calls and frustration. Programming an autonomous vehicle (AV) to do the same — without a human behind the wheel or knowledge of what the other driver might do — presented a unique challenge for researchers at the Carnegie Mellon University Argo AI Center for Autonomous Vehicle Research…

While at CMU, Killing teamed up with research scientist John Dolan and Ph.D. student Adam Villaflor to crack this problem. The team presented its research, “Learning To Robustly Negotiate Bi-Directional Lane Usage in High-Conflict Driving Scenarios,” at the International Conference on Robotics and Automation.