TY - CHAP
T1 - Experimental Approximation of a Vehicle’s Fuel Consumption Using Smartphone Data
AU - Christopoulos, Stavros
AU - Kanarachos, Stratis
AU - Papadopoulou, Konstantina A.
N1 - Publisher Copyright:
© The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.
PY - 2022/8/19
Y1 - 2022/8/19
N2 - An algorithm is developed in order to record a vehicle’s fuel consumption using data from a smartphone’s sensors. Six field tests were conducted: (1) Ford Fiesta car with automatic transmission driven around Coventry, UK, with “passive” and “restless” driving behaviors, (2) Ford Fiesta car with manual transmission under heavy traffic driven around Athens, Greece, (3) Ford Fiesta car with manual transmission driven around Athens, Greece, in heavy traffic, in a highway, with “passive” and “restless” driving behaviors and high variation in altitude during the trip, (4) Ford Fiesta car with manual transmission driven around Athens, Greece, with “passive” and “restless” driving behaviors and even higher variation in altitude during the trip, (5) Suzuki Swift car with manual transmission, a route including highway, streets and alleys, in the west Attica in the surrounding area of the capital of Greece, and (6) Suzuki Swift car with manual transmission, with “passive”, “normal” and “restless” driving behaviors in West Attica, in a place with a small hill with a very high slope that we “climbed” three times in a row. The results show that the proposed algorithm improves the smartphone-recorded GPS data so that they show high accuracy when compared to the GPS data extracted from each vehicle’s on-board diagnostic system.
AB - An algorithm is developed in order to record a vehicle’s fuel consumption using data from a smartphone’s sensors. Six field tests were conducted: (1) Ford Fiesta car with automatic transmission driven around Coventry, UK, with “passive” and “restless” driving behaviors, (2) Ford Fiesta car with manual transmission under heavy traffic driven around Athens, Greece, (3) Ford Fiesta car with manual transmission driven around Athens, Greece, in heavy traffic, in a highway, with “passive” and “restless” driving behaviors and high variation in altitude during the trip, (4) Ford Fiesta car with manual transmission driven around Athens, Greece, with “passive” and “restless” driving behaviors and even higher variation in altitude during the trip, (5) Suzuki Swift car with manual transmission, a route including highway, streets and alleys, in the west Attica in the surrounding area of the capital of Greece, and (6) Suzuki Swift car with manual transmission, with “passive”, “normal” and “restless” driving behaviors in West Attica, in a place with a small hill with a very high slope that we “climbed” three times in a row. The results show that the proposed algorithm improves the smartphone-recorded GPS data so that they show high accuracy when compared to the GPS data extracted from each vehicle’s on-board diagnostic system.
KW - Exhaust emissions
KW - Fuel consumption
KW - GPS data
KW - Smartphone
UR - http://www.scopus.com/inward/record.url?scp=85160165101&partnerID=8YFLogxK
UR - https://link.springer.com/book/10.1007/978-3-031-05516-4
U2 - 10.1007/978-3-031-05516-4_8
DO - 10.1007/978-3-031-05516-4_8
M3 - Chapter
AN - SCOPUS:85160165101
SN - 9783031055157
SN - 9783031055188
SP - 129
EP - 139
BT - Technologies for Smart Cities
A2 - Vershinin, Yuri A.
A2 - Pashchenko, Fedor
A2 - Olaverri-Monreal, Cristina
PB - Springer, Cham
ER -