TY - GEN
T1 - Determining easily avoidable stop position by predicting surrounding vehicles' paths
AU - Kajiwara, Masahiro
AU - Ohno, Kazunori
AU - Hamada, Ryunosuke
AU - Suzuki, Takahiro
AU - Tadokoro, Satoshi
N1 - Funding Information:
This work was supported by JST CREST program entitled ”Recognition, Summarization and Retrieval of Large-Scale Multimedia Data”, Grant Number JPMJCR1403, Japan.
Publisher Copyright:
© 2017 IEEE.
PY - 2018/2/1
Y1 - 2018/2/1
N2 - We propose a method for deciding an avoidable stop position for a vehicle to not disturb the surrounding traffic. A vehicle needs to pull over and make an autonomous emergency stop when a driver has a seizure and loses consciousness. To develop such an autonomous stop system on a narrow road, considering the surrounding vehicles and not hindering traffic are imperative to rescue a patient. We present an approach based on predicting the paths of other vehicles to avoid the ego-vehicle, a load index of a following vehicle driver for predicted paths, and an index that shows the interference between the paths of the following and oncoming vehicle. The path prediction is computed by applying a lattice path planner comprising the vehicle's position, posture, and path curvature. The load index of the following vehicle is calculated with respect to the cumulative curvature of the predicted path. The interference index of the following and oncoming vehicles is estimated by evaluating the area that both vehicles pass to avoid the ego-vehicle. The simulation results showed the ego-vehicle had to pull over by 1.5 m over the road shoulder and 1.0 m ahead of a parked vehicle on the opposite lane.
AB - We propose a method for deciding an avoidable stop position for a vehicle to not disturb the surrounding traffic. A vehicle needs to pull over and make an autonomous emergency stop when a driver has a seizure and loses consciousness. To develop such an autonomous stop system on a narrow road, considering the surrounding vehicles and not hindering traffic are imperative to rescue a patient. We present an approach based on predicting the paths of other vehicles to avoid the ego-vehicle, a load index of a following vehicle driver for predicted paths, and an index that shows the interference between the paths of the following and oncoming vehicle. The path prediction is computed by applying a lattice path planner comprising the vehicle's position, posture, and path curvature. The load index of the following vehicle is calculated with respect to the cumulative curvature of the predicted path. The interference index of the following and oncoming vehicles is estimated by evaluating the area that both vehicles pass to avoid the ego-vehicle. The simulation results showed the ego-vehicle had to pull over by 1.5 m over the road shoulder and 1.0 m ahead of a parked vehicle on the opposite lane.
UR - http://www.scopus.com/inward/record.url?scp=85050872766&partnerID=8YFLogxK
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U2 - 10.1109/SII.2017.8279324
DO - 10.1109/SII.2017.8279324
M3 - Conference contribution
AN - SCOPUS:85050872766
T3 - SII 2017 - 2017 IEEE/SICE International Symposium on System Integration
SP - 823
EP - 828
BT - SII 2017 - 2017 IEEE/SICE International Symposium on System Integration
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE/SICE International Symposium on System Integration, SII 2017
Y2 - 11 December 2017 through 14 December 2017
ER -