35 research outputs found
Predictive Powertrain Management through Driver Behaviour Recognition
With automotive trends leading towards electrification and inclusion of intelligent technology for advanced driver assistance systems (ADAS), there is a need to research the use of advanced control strategies. This report touches on the development of a powertrain model built in Simulink used for simulation testing and vehicle development. While addressing the needs of incorporating state-of-the-art technology, this report shows how a LiDAR and camera system can function together as ADAS sensors for vehicle detection and range estimation. Lastly, the main purpose of this report is to show how the UWAFT powertrain model and ADAS sensors, along with behaviour recognition software, can be used to reduce emissions and energy consumption while also increasing driveability.
Machine learning techniques are used to classify a driver’s behaviour on a spectrum from aggressive to eco-cautious. 288 hours of driver behaviour data is simulated using the UWAFT’s vehicle model built in Simulink. The data is labelled as aggressive, normal, or eco-cautious depending on the scaling factor applied to the drive cycle inputted. Linear discriminant analysis is performed to maximize the separation between classes and reduce the dimensionality. Support vector machines are used to classify the driver’s behaviour. Lastly, fuzzy logic is used to assign a driver an aggressiveness value between 0 and 100. The classifier implemented achieved 81.53% accuracy; however, the aggression value assigned to the data via fuzzy logic is a more accurate representation. Vehicle testing is performed with the use of a closed-loop testing track and a chassis dynamometer. An acceleration test is conducted by applying a wide-open throttle in various operating modes. This identified drive traces that are only achievable in certain modes, thus concluding that if the driver’s behaviour is predicted prior to an acceleration event, the correct operating mode could be selected ahead of time, increasing the driveability. Additionally, a regenerative braking test is conducted on a chassis dynamometer to determine the optimal regen torque parameters for a given braking rate. It is concluded that using the best parameters for a stopping distance of 2 mph/s would result in a 0.003% state of charge gain per second. Therefore, by knowing a driver’s braking behaviour the UWAFT PHEV could select the best parameters for the current drive to decrease energy consumption
Lobbying for education in a two-sector model
Firms specialized in two different sectors lobby to induce the government to subsidize
the type of education complementary to their production. Lobbying is endogenous. We
show that, if lobbying is not costly, both sectors will lobby in equilibrium and the education
policy will induce the same skill composition that would be chosen by the social planner.
However, if lobbying is costly and there is sufficient asymmetry between the sectors, only
one sector will exert pressure on the policymaker in the attempt to direct resources toward
the type of education required by its production. Which sector will engage in lobbying
depends on relative size, productivity and price
Expanding the criteria for defining success when evaluating weight loss intervention programs
Factors Associated With Weight Change Among Clients of a Residential Weight Control Program Indicating Binge and Nonbinge Traits
The association between the body mass index of first-year female university students and their weight-related perceptions and practices, psychological health, physical activity and other physical health indicators
To investigate the association between the weight status of first-year female
students (FYFS) and various weight management-related characteristics to identify
possible components of a weight management programme for students. Mean (^standard deviation (SD)) body mass index (BMI) of the FYFS was
21.8 ^ 2.6 kg m22
, with 7.2% being underweight, 81.9% normal-weight, 10.0%
overweight and 0.8% obese. Underweight, normal-weight and overweight students
differed with regard to their perception of their weight (P , 0.001), weight goals
(P , 0.001) and previous weight-loss practices (P , 0.001). Mean ^ SD score on the
26-item Eating Attitudes Test (EAT-26) was 8.5 ^ 9.0 with 8.4% classified as high
scorers. Mean ^ SD score on the 34-item Body Shape Questionnaire (BSQ) was
87.7 ^ 32.2, with 76.1% classified as low, 11.9% as medium and 11.9% as high scorers.
The self-concept questionnaire indicated that 36.7% had a high, 43.9% a medium and
19.4% a low self-concept. Higher BMI correlated with a higher BSQ score (P , 0.001),
a lower self-concept (P ¼ 0.029) and a higher EAT-26 score (P , 0.001). Smoking was
prevalent amongst 13.1% of students, and 51.2% used vitamin and/or mineral
supplements. Students who quitted smoking had higher (P ¼ 0.006) BMI
(22.7 ^ 2.9 kg m22
) than those who never smoked before (21.6 ^ 2.5 kg m22
)