Dataset for driver behavior classification (normal, aggressive, risky) based on accelerometer (X,Y,Z axis in meters per second squared (m/s2)) and gyroscope (X,Y, Z axis in degrees per second (°/s) ) data. Sampling Rate: 50 Hz default Cars: Ford Figo 1.2, Maruti Suzuki Swift VXI, Tata Nexon XMS Drivers: 3 different drivers with the ages between 35-40 yrs. Driver Behaviors: Normal, Aggressive, and Risky Smartphone Sensor: Accelerometer, Gyroscope Smartphone Device: Redmi 4, MI A
This paper faces the human factor in driving and its consequences for road safety. It presents the c...
The aim of this paper is to explore driving behaviour during mobile phone use on the basis of detail...
Driving behaviour has a significant impact on traffic safety, eco-driving, and country development. ...
Dataset for driver behavior classification (normal, aggressive, risky) based on accelerometer (X,Y,Z...
Dataset for modeling risky driver behaviors based on accelerometer (X,Y,Z axis in meters per second ...
(1_20210317_184512.csv, 2_20210317_171452.csv) - Data has been recorded on an android phone attached...
Abstract—Real-time abnormal driving behaviors monitoring is a corner stone to improving driving safe...
The data was collected from 633 different drivers using smartphones with embedded accelerometer and ...
The objective of this paper is to detect and analyze risky driving behaviour characteristics on the ...
peer reviewedToday's smartphones and mobile devices typically embed advanced motion sensors. Due to ...
Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver behavior p...
Since pervasive smartphones own advanced computing capability and are equipped with various sensors,...
Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver behavior p...
This paper utilizes smartphone sensing of vehicle dynamics to determine driver phone use, which can ...
Traffic safety and energy efficiency of vehicles are strictly related to driver’s behavior. The scie...
This paper faces the human factor in driving and its consequences for road safety. It presents the c...
The aim of this paper is to explore driving behaviour during mobile phone use on the basis of detail...
Driving behaviour has a significant impact on traffic safety, eco-driving, and country development. ...
Dataset for driver behavior classification (normal, aggressive, risky) based on accelerometer (X,Y,Z...
Dataset for modeling risky driver behaviors based on accelerometer (X,Y,Z axis in meters per second ...
(1_20210317_184512.csv, 2_20210317_171452.csv) - Data has been recorded on an android phone attached...
Abstract—Real-time abnormal driving behaviors monitoring is a corner stone to improving driving safe...
The data was collected from 633 different drivers using smartphones with embedded accelerometer and ...
The objective of this paper is to detect and analyze risky driving behaviour characteristics on the ...
peer reviewedToday's smartphones and mobile devices typically embed advanced motion sensors. Due to ...
Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver behavior p...
Since pervasive smartphones own advanced computing capability and are equipped with various sensors,...
Driver behavior impacts traffic safety, fuel/energy consumption and gas emissions. Driver behavior p...
This paper utilizes smartphone sensing of vehicle dynamics to determine driver phone use, which can ...
Traffic safety and energy efficiency of vehicles are strictly related to driver’s behavior. The scie...
This paper faces the human factor in driving and its consequences for road safety. It presents the c...
The aim of this paper is to explore driving behaviour during mobile phone use on the basis of detail...
Driving behaviour has a significant impact on traffic safety, eco-driving, and country development. ...