dc.contributor.author	Muslim, Nurul Hidayah
dc.date.accessioned	2023-09-10T01:26:43Z
dc.date.available	2023-09-10T01:26:43Z
dc.date.issued	2021
dc.description	Thesis (PhD. (Civil Engineering))
dc.description.abstract	Vehicles, the environment, and drivers are important factors in driving behavioural studies. However, previous research related to vehicle’s fuel consumption and tailpipe emissions were focused on driving behaviour while treating the driver’s behaviour with a lack of consideration. Therefore, this study aims to model the impact of aggressive driving behaviour on vehicle fuel consumption and tailpipe emissions by considering characteristic of driver in real driving behaviour. Self-reported assessment tool was used to identify aggressive and nonaggressive drivers. Both types of drivers were then invited for on-road driving assessment (ODA) under different traffic conditions over five consecutive days. During the ODA, driver behaviour (anger expressions) were evaluated by an in-car observer, while driving behaviour and driving performances were observed and recorded using video camera and GPS Logger. The recorded anger expression during ODA were then validated with self-reported anger expression and triangulated with the actual driving behaviour and driving performance. Data recorded in the GPS Logger were then extracted in order to develop driving cycles for aggressive and non-aggressive drivers. The driving cycle was developed using micro trips by eliminating idling conditions. Aggressive drive cycle (AGDC) was compared with non-aggressive drive cycle (NGDC) and the findings from previous studies based on kinematic assessment parameters. AGDC and NGDC were then simulated using a chassis dynamometer in the laboratory to measure the vehicle’s fuel consumption and tailpipe emissions. Tailpipe emissions obtained from the AGDC and NGDC were also compared based on speed variations, traffic conditions, and road sections. The results from the Driving Anger Expression Inventory (DAX) questionnaires revealed that 35 out of 330 respondents were aggressive drivers and the rest were non-aggressive drivers. Based on 10 aggressive drivers and 1 non-aggressive driver who agreed to participate in the ODA, the findings on anger expressions showed insignificant difference between recorded and self-reported anger expressions. Based on the validated data, more than 58% consistencies in vehicle and verbal aggressions were found between self rating and in-car observation. While, only 35% and 42 % of vehicle and verbal aggressions, respectively shown by aggressive drivers in the video camera observation. Aggressive drivers were found to tailgate other vehicles, performed dangerous overtaking, violated the lane-keeping and red-light signals. For driving performances, it showed that aggressive drivers had a shorter travel time, higher average speed, and higher maximum speed as compared to non-aggressive drivers. Strong negative correlations was found between aggressive drivers travel time and average speed indicating that higher choice of speed had shortened the travel time. The comparative characteristics of AGDC and NGDC showed that the AGDC had shorter driving time, higher average speed, higher positive acceleration, and lower negative acceleration and positive acceleration kinetic energy (PKE) compared to the NGDC. While the comparison of AGDC with previous studies indicated that AGDC has similar kinematic characteristics with drive cycles in China, Taiwan, Jakarta, Chennai, Hong Kong, Tehran, and Tianjin. Results for the simulated driving cycles showed that AGDC had lower fuel consumption compared to NGDC. It was found that more than 50% of CO2 and less than 2% of CO emissions from AGDC and NGDC have been emitted. As speed increases, CO and CO2 emissions have increased. CO and CO2 emissions were found slightly higher during the afternoon traffic than other traffic conditions. For interrupted and non-interrupted road sections, AGDC illustrated increasing CO emissions in contrast to NGDC. While for CO2, AGDC showed high CO2 emissions at the interrupted section during the afternoon traffic and non-interrupted section during the morning traffic. The study concluded that modelling aggressive driving behaviour impact on vehicle fuel consumption and tailpipe emissions using new methods is capable of conveying realistic results. The application of new methods in the study can be used in other driver and driving behaviour studies that benefit for the environmental management.
dc.description.sponsorship	Faculty of Engineering - School of Civil Engineering
dc.identifier.uri	http://openscience.utm.my/handle/123456789/704
dc.language.iso	en
dc.publisher	Universiti Teknologi Malaysia
dc.subject	Automobiles—Fuel consumption
dc.subject	Automobiles—Motors—Exhaust gas—Measurement
dc.subject	Aggressive driving
dc.subject	Behaviorism (Psychology)—Research
dc.title	Modelling aggressive driving behaviour impact on vehicle fuel consumption and tailpipe emissions
dc.type	Thesis
dc.type	Dataset

Modelling aggressive driving behaviour impact on vehicle fuel consumption and tailpipe emissions

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