![Aerial view of street intersection with lights, crosswalks and bike paths](https://transportation.asu.edu/wp-content/uploads/sites/9/2021/08/crossroads-hero.jpg)
Featured project
Crossroads: Autonomous Intersection Management
Sponsors
Partially funded by National Science Foundation grants:
- CCF 1055094 (CAREER)
- CNS 1525855
- NIST 60NANB16D305
- NIST 60NANB15D322
Challenge
The introduction and adoption of autonomous vehicles will require intelligent autonomous intersection management. Intersection management includes maintaining a safety buffer around the vehicle while factoring variable network and computational time delays. Modeling these network and computational delays can degrade the throughput of the intersection even when processed by a state-of-the-art intersection manager.
Summary
To combat these limitations, ASU researchers have developed Crossroads, a time-sensitive method to program the interface of a vehicle and intersection that does not require an additional buffer to account for network and computational delays.
Using a small-scale intersection model with radio control cars, the Crossroads approach demonstrated a reduction in average vehicle wait time at a single-lane intersection of 24 percent. Crossroads obviates the need for large buffers to accommodate network and computational delays.
![Simulated Intersection](https://transportation.asu.edu/sites/default/files/inline-images/intersection.jpg)
Results
Through extensive MATLAB simulations, Crossroads has shown increased throughput compared to existing approaches: 1.62X higher throughput (on average) than Velocity Transaction Intersection Management (VT-IM) with extra safety buffers, and 1.36X higher throughput (on average) than autonomous intersection management (AIM).
![chart](https://transportation.asu.edu/sites/default/files/inline-images/computation-time.jpg)
For more information, including publication in the 54th-annual Design Automation Conference (DAC), see https://labs.engineering.asu.edu/mps-lab/.