A Quantitative Study on Driving Behavior Economy Based on Big Data from the Pure Electric Bus

In order to help improve the economy, energy savings and emission reductions of pure electric buses, based on driving data, a new cycle construction method is proposed. Through dividing short trips calculation characteristic parameter values, two typical conditions (weekday condition weekend condition) are constructed via principal components analysis k-means clustering method, both have high degree compatibility with actual conditions. Based conditions, CRITIC (Criteria Importance Though Intercriteria Correlation) quantitative used establish evaluation model score economy driver’s behavior. The result shows that working better traffic environment promotes generation aggressive behavior increases random fluctuation seen in process: for condition, proportion low economic efficiency about 4.5 times bigger than weekdays, former’s range 37% higher latter, meaning overall bus much worse weekends.