TY - GEN
T1 - Assumptions of Lateral Acceleration Behavior Limits for Prediction Tasks in Autonomous Vehicles
AU - Zechel, Peter
AU - Streiter, Ralph
AU - Bogenberger, Klaus
AU - Gohner, Ulrich
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - This paper presents an analysis of the euroFot data set to determine limits for the typical lateral acceleration behavior of drivers. Since recent studies indicate that lateral accelerations close to the physically possible limit are rarely used by drivers, predictions tasks for autonomous driving could consider a smaller, so-called natural lateral acceleration interval (NLAI) instead of all physically possible lateral accelerations. This NLAI should be as small as possible while still fulfilling all safety aspects. Therefore, valid assumptions are required on which the interval can be derived. Since a valid assumption which leads to minimal NLAI is yet unknown, four different assumptions concerning the lateral acceleration behavior are derived and evaluated in this paper. Thereby, detailed examinations regarding the relative frequencies of violations are presented. Finally, two assumptions are recommended for introducing an NLAI, depending on prediction time and safety requirements. Additionally, the advantages of utilizing an NLAI instead of all physically possible lateral accelerations are highlighted by comparing the results of an occupancy prediction approach.
AB - This paper presents an analysis of the euroFot data set to determine limits for the typical lateral acceleration behavior of drivers. Since recent studies indicate that lateral accelerations close to the physically possible limit are rarely used by drivers, predictions tasks for autonomous driving could consider a smaller, so-called natural lateral acceleration interval (NLAI) instead of all physically possible lateral accelerations. This NLAI should be as small as possible while still fulfilling all safety aspects. Therefore, valid assumptions are required on which the interval can be derived. Since a valid assumption which leads to minimal NLAI is yet unknown, four different assumptions concerning the lateral acceleration behavior are derived and evaluated in this paper. Thereby, detailed examinations regarding the relative frequencies of violations are presented. Finally, two assumptions are recommended for introducing an NLAI, depending on prediction time and safety requirements. Additionally, the advantages of utilizing an NLAI instead of all physically possible lateral accelerations are highlighted by comparing the results of an occupancy prediction approach.
KW - Automated Vehicle Operation
KW - Human Factors in Intelligent Transportation Systems
KW - Motion Planning
UR - http://www.scopus.com/inward/record.url?scp=85078868086&partnerID=8YFLogxK
U2 - 10.1109/ICOM47790.2019.8952059
DO - 10.1109/ICOM47790.2019.8952059
M3 - Conference contribution
AN - SCOPUS:85078868086
T3 - 2019 7th International Conference on Mechatronics Engineering, ICOM 2019
BT - 2019 7th International Conference on Mechatronics Engineering, ICOM 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 7th International Conference on Mechatronics Engineering, ICOM 2019
Y2 - 30 October 2019 through 31 October 2019
ER -