Abstract
Automobile exhaust emission has a serious impact on the environment. Driver models are currently used to predict the amount of CO2 emitted from vehicles, but the current models are inadequate as they do not capture the real road traffic environment. So, it is necessary to clarify the effects of traffic environments on driving operation under real-world driving conditions. In this study, how the driver’s accelerator operation, which has a large impact on CO2 emission behavior, was analyzed. Actual driving experiments using hybrid vehicles on multiple routes on public roads and highways were conducted in the Tokyo metropolitan area, and various data on traffic environments were collected and analyzed. To conduct the analysis, a driving model of a hybrid vehicle were created and which information about the traffic environment influences the driver’s driving operation were examined. Then, a multiple regression model to predict the amount of accelerator operation by the driver was created based on this information. In order to improve the accuracy of the model, a modified version of the model that takes into account the driver’s reaction time and the decision to accelerate off was developed. Finally, the created models were fitted to test data on general roads and highways to verify their accuracy and to analyze the magnitude of the influence of each traffic environment.
