Abstract
Understanding the operational characteristics of vocational trucks, and developing a method to assess the suitability of the vocation types with various fuel types is a cornerstone (backbone) of successful fuel transition from incumbents to clean alternatives. With the collected in-vehicle controller area network (CAN) data, operational characteristics of the three vocational CNG vehicle types are analyzed and compared with each other. Through pattern clustering and classification process, the obtained vehicle activity data is translated into drive mode compositions (DMC) which are associated with driving situations and operation conditions. Drive mode composition indicates how a vehicle is being operated in terms of time and distance. To assess the vehicle operation in a stereoscopic view, the obtained vehicle trajectories are geo-mapped into the open-street map and segmented by road facility type which is defined by highway functional classes. The analysis results present that each drive mode has different nitrogen oxides (NOâ??) emission factors in grams per mile or second. Another finding is that vocation type is one of the influential factor determining vehicle activity and environmental impact potential. In addition, it is found that drive mode composition changes over different road facility types and by road conditions, such as trip distance and duration. DMC for each facility trip shows a clearer picture of the operational characteristics between the considered vocation types. The proposed anatomical analysis on vehicle activity can be used to resolve a variety of research issues and policies related with alternative fuel and clean energy vehicles.