TY - GEN
T1 - Towards a parameter tuning approach for a map-matching algorithm
AU - Blazquez, Carola A.
AU - Ries, Jana
AU - Miranda, Pablo A.
N1 - Funding Information:
J. Ries is a Senior Lecturer at the University of Portsmouth, UK, e-mail: [email protected] P. Miranda is a full time faculty member at the School of Industrial Engineering at the Pontificia Universidad Catolica de Valparaiso. e-mail: [email protected] *Research supported by project funds at Universidad Andres Bello Project N°DI-1236-16/RG, and the Fondecyt Project N°1140811.
Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/25
Y1 - 2017/7/25
N2 - Map Matching Algorithms (MMA) are developed to solve spatial ambiguities that arise in the process of assigning GPS measurements onto a digital roadway network. There is a lack of systematic parameter tuning approaches for optimizing the MMA performance. Thus, a novel integrated framework is proposed for a systematic calibration of the parameters of a post-processing MMA. The calibration approach consists of an Instance-specific Parameter Tuning Strategy (IPTS) that employs Fuzzy Logic principles. The proposed fuzzy IPTS tool determines the best algorithm parameter values by using instance-specific information a priori to the execution of the MMA. A preliminary prototype of an IPTS system is designed based on real-world data, which identifies the explanatory variables that condition the MMA performance. The implementation of the fuzzy IPTS tool on real-word data yields an enhanced MMA performance in the solution quality and computational time compared to the results of the execution of the MMA with constant algorithm settings.
AB - Map Matching Algorithms (MMA) are developed to solve spatial ambiguities that arise in the process of assigning GPS measurements onto a digital roadway network. There is a lack of systematic parameter tuning approaches for optimizing the MMA performance. Thus, a novel integrated framework is proposed for a systematic calibration of the parameters of a post-processing MMA. The calibration approach consists of an Instance-specific Parameter Tuning Strategy (IPTS) that employs Fuzzy Logic principles. The proposed fuzzy IPTS tool determines the best algorithm parameter values by using instance-specific information a priori to the execution of the MMA. A preliminary prototype of an IPTS system is designed based on real-world data, which identifies the explanatory variables that condition the MMA performance. The implementation of the fuzzy IPTS tool on real-word data yields an enhanced MMA performance in the solution quality and computational time compared to the results of the execution of the MMA with constant algorithm settings.
UR - http://www.scopus.com/inward/record.url?scp=85034217024&partnerID=8YFLogxK
U2 - 10.1109/ICVES.2017.7991906
DO - 10.1109/ICVES.2017.7991906
M3 - Conference contribution
AN - SCOPUS:85034217024
T3 - 2017 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2017
SP - 85
EP - 90
BT - 2017 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2017
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2017 IEEE International Conference on Vehicular Electronics and Safety, ICVES 2017
Y2 - 27 June 2017 through 28 June 2017
ER -