Quantifying road traffic emissions embedded in a multi-objective traffic assignment model

Abstract

In a road network, drivers typically seek to minimize their own travel time, often affecting system-wide performance. With the increasing environmental awareness, for an efficient traffic assignment (TA), besides concerns with travel times, traffic managers should not neglect the system-wide level of both global and local pollutant emissions. Measuring road traffic emissions can be costly and different models based on vehicle-specific parameters with many input variables have been suggested in the literature. This paper proposes a simple way to quantifying carbon dioxide (CO2) and nitrogen oxides (NOX) emissions with only average speed as input variable and presents a multi-objective TA approach that seeks to minimize system-wide travel time, distance travelled (associated with fuel consumption) and global and local pollutant emissions. A real-world case study on an intercity corridor with many alternative routes between two zones is presented. Experiments considering TA based on travel time, and on time, distance travelled, and pollutant emissions are reported. Results highlight that system optimal distribution based on the suggested multi-objective TA based on three components yields savings in terms of distance travelled (2.6%) and emissions (1.3% for CO2 and 1.1% for NOX), but penalizes travel time 3%, which is translated in an increase of 20sec per vehicle, when compared to the solution only focused on minimizing travel time. The developed methodology is a suitable tool for traffic analysts to predict vehicle system-wide travel time, distance travelled and pollutant emissions with few vehicle information but with a reasonable detail for a specific traffic flow on a given road network, to support analyses for sustainable transport policies and may be used, for instance, as an environmental impact component of a pricing scheme, traffic signal control strategies based on emissions reduction, or to minimize congestion by giving prior information to drivers on the specific routes to be chosen.