Transportation is one of the major contributors in global energy consumption and greenhouse gas emissions. Currently, there are approximately 1.32 billion on-road vehicles around the world, which is expected to be doubled by 2040. This increase has triggered deep concerns over the global issues of climate change and sustainable development. Current GPS navigation systems determine the best travel route in terms of time or distance. However, there are significant challenges to determine an optimal travel route considering sustainability. This paper aims to develop an automated system in order to evaluate different travel routes and suggest the most sustainable one. In this paper, a mathematical model is proposed to estimate the travel time and fuel consumption given different travel route options. Five operational and engine variables of acceleration rate, speed, road slope, engine load, and fuel consumption rate are incorporated in the quantitative analysis. Remote data acquisition was conducted using a GPS-aided inertial navigation system (GPS-INS) and an engine data logger for seven days. The results indicate that the fastest route selected by the current navigation system may not be the most sustainable option. It was also found in the field experiments that the most sustainable route could potentially save on average 5% fuel consumption compared to the fastest route.