TY - GEN
T1 - A vision-based system for a UGV to handle a road intersection
AU - Ahmed, Javed
AU - Shah, Mubarak
AU - Miller, Andrew
AU - Harper, Don
AU - Jafri, M. N.
PY - 2007
Y1 - 2007
N2 - We propose a real-time computer vision system that enables a UGV to safely cross urban road-intersections. Specifically, when the UGV approaches the stop sign at a 4-way intersection, it must be aware of the vehicles at the other three roads and adhere to traffic rules by waiting for its turn to proceed. The proposed solution consists of three main components: a vehicle detector, a tracker, and a finite-state-machine to model the traffic. We use an OT-MACH filter to detect the leading vehicle in each of three camera-views of the corresponding roads. Then, we track the vehicles using an edge-enhanced dynamic correlation tracker, which estimates the current and next positions, velocities, and accelerations of the vehicles. Finally, the finite-state-machine describes the traffic in each road with one of four possible states (i.e. No Vehicle Waiting, Arriving, Waiting, and Passing), and signals an autopilot system when it is safe to pass the intersection. We provide the results from an actual intersection with real traffic to demonstrate that the UGV is able to automatically navigate the intersection using the proposed system.
AB - We propose a real-time computer vision system that enables a UGV to safely cross urban road-intersections. Specifically, when the UGV approaches the stop sign at a 4-way intersection, it must be aware of the vehicles at the other three roads and adhere to traffic rules by waiting for its turn to proceed. The proposed solution consists of three main components: a vehicle detector, a tracker, and a finite-state-machine to model the traffic. We use an OT-MACH filter to detect the leading vehicle in each of three camera-views of the corresponding roads. Then, we track the vehicles using an edge-enhanced dynamic correlation tracker, which estimates the current and next positions, velocities, and accelerations of the vehicles. Finally, the finite-state-machine describes the traffic in each road with one of four possible states (i.e. No Vehicle Waiting, Arriving, Waiting, and Passing), and signals an autopilot system when it is safe to pass the intersection. We provide the results from an actual intersection with real traffic to demonstrate that the UGV is able to automatically navigate the intersection using the proposed system.
UR - http://www.scopus.com/inward/record.url?scp=36348940410&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=36348940410&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:36348940410
SN - 1577353234
SN - 9781577353232
T3 - Proceedings of the National Conference on Artificial Intelligence
SP - 1077
EP - 1082
BT - AAAI-07/IAAI-07 Proceedings
T2 - AAAI-07/IAAI-07 Proceedings: 22nd AAAI Conference on Artificial Intelligence and the 19th Innovative Applications of Artificial Intelligence Conference
Y2 - 22 July 2007 through 26 July 2007
ER -