No abstract

This study aims to find the on-road driving parameters influencing fuel consumption and emissions of motorcycle driving on a congested signalized urban corridor. A motorcycle onboard measurement system was developed to measure instantaneously and continuously record on-road driving data, including speed-time profile, emissions, and fuel consumption, by the second. The test motorcycles were driven by 30 sample motorcyclists on a signalized urban corridor in Khon Kaen City, Thailand, to collect their on-road driving behavior during the morning peak period. Cluster analysis was applied to analyze collected driving data and to categorize the drivers by level of fuel consumption and on-road driver behavior. The on-road driving parameter influencing fuel consumption and emissions was then determined. Results revealed that proportion of idle time significantly influenced fuel consumption and emissions of motorcycle driving on a congested signalized urban corridor, though aggressive driving behavior, hard acceleration and deceleration, did not have the same kind of influence.

This study developed an onboard system to measure the on-road driving pattern for a motorcycle driving cycle in Khon Kaen city, Thailand. The developed system, validated with high accuracy results, could measure and record a driving pattern, i.e. a speed profile of a driving motorcycle. The selected motorcycle was driven along selected routes in Khon Kaen city under the existing traffic conditions to collect the on-road driving pattern. The Khon Kaen motorcycle driving cycle (KMDC) was developed by a repetitive algorithm using the principle of least total variance in the target parameters. The developed KMDC was compared with the existing motorcycle driving cycles for Bangkok and other cities. The result reveals that the KMDC is different from those of other cities.

This study developed on-road exhaust emission and fuel consumption models for application in traffic microsimulations to estimate motorcycle emissions and fuel consumption in an Asian developing city. The motorcycle onboard measurement system was developed to instantaneously measure and continuously record on-road driving data, including the speed-time profile, exhaust emissions, and fuel consumption per second. The test motorcycle was driven on roads around Khon Kaen City, Thailand, to collect on-road driving data during the morning peak hours for a total of 112 hours. The collected on-road driving data were applied to develop on-road exhaust emission and fuel consumption models using regression analysis. The models were developed with high correlations among the amount of exhaust emissions and fuel consumption and the instantaneous speed and acceleration rate. The developed models were applied with a traffic microsimulation to evaluate the exclusive zone for motorcycles stopping at a signalized intersection. The evaluation results reveal that it could improve the level of intersection service by decreasing travel times, delays, and queue lengths at intersections, as well as by reducing the fuel consumption and emissions of vehicles travelling through intersections compared with these values under the existing conditions.

This study developed an onboard system to measure on road driving pattern for a motorcycle. The main components of the developed system consist of a magnetic wheel speed sensor for measuring speed of the motorcycle and a data logger. The developed data logger consists of a microcontroller, memory storage and data display panel for processing and recording the on road speed-time data. The developed system was validated to measure and correctly record speed per time interval. The developed onboard system will be applied by installing on driven motorcycles for recording a speed-time data that will be used to develop the motorcycle driving cycle.