Estimating Fuel Consumption and Carbon Footprint at Signalized Intersections Using Probe Vehicle Trajectories

As vehicle-to-vehicle and vehicle-to-infrastructure communication technologies evolve, data from vehicles equipped with location and wireless technologies will provide a wealth of data to observe the traffic flow dynamics more precisely. Data from a sample of instrumented vehicles (called probe vehicles) can be used to estimate performance measures for the remainder of the traffic stream. The research presented in this paper attempts to estimate the total fuel consumption and CO2 emissions at a signalized intersection from the data provided by probe vehicles. Traffic flow through an intersection is simulated to generate vehicle trajectories under both congested and uncongested conditions. Six different vehicle types are modeled in the simulation for the purpose of calculating fuel consumption levels. By using the Virginia Tech Comprehensive Power-Based Fuel Consumption Model (VT-CPFM), the total fuel consumed by each vehicle is determined for a given trajectory. Several alternative methods are presented to estimate the total fuel consumption from the sample data provided by the probe vehicles. The results show that a simple extrapolation of the fuel consumed by probes to the rest of the traffic does not yield very accurate results. A more accurate solution is obtained by capitalizing on the probe trajectories to construct trajectories for the non-probe vehicles. For the simulated conditions, it is demonstrated that the total fuel consumption can be estimated with a reasonable accuracy at relatively low probe-vehicle market-penetration levels. It is further demonstrated that if a proper “average vehicle” is specified for estimating the total fuel consumption level then, knowing the make & model of individual probe vehicles does not enhance the estimation accuracy. The research presented in this paper will be of benefit to data collection systems for supporting eco-signals and other similar applications to improve fuel consumption and to reduce CO2-emissions that are directly proportional to the fuel usage.