Abstract
This study evaluates the environmental benefits of pavement rehabilitation on the M-50 motorway (Madrid, Spain) through a before-and-after analysis based on connected vehicle data. The aim was to quantify the effect of improved surface roughness on vehicle fuel consumption and CO¿ emissions.
The methodology included five phases: (i) validation of roughness data from autonomous and connected vehicles, (ii) vehicle fleet characterization, (iii) data collection and filtering, (iv) segmentation of road sections by surface roughness, vertical alignment, and intervention status, and (v) comparative analysis before and after rehabilitation.
The vehicle fleet consisted primarily of diesel passenger cars (45%), gasoline cars (30%), vans (12%), trucks (8%), and buses (5%). The analysis focused on homogeneous road segments during off-peak hours to avoid congestion effects, comparing data from November 2023 and 2024 under similar weather conditions. Seven rehabilitated segments (¿30 km) and corresponding control sections were analyzed. The dataset included vehicle speed, fuel consumption, CO¿ emissions, and surface roughness.
Results showed substantial post-rehabilitation improvements: lower surface irregularity, higher average speeds, and reduced fuel consumption and emissions. Benefits were especially evident in sections with steeper gradients. On average, fuel consumption and emissions decreased by 9¿10%. Given a daily traffic volume of approximately 115,000 vehicles and a 50-50 directional split, the rehabilitated inbound sections saved an estimated 16,206 liters of fuel and 43.75 tonnes of CO¿ per day. Annually, this equates to roughly 6 million liters of fuel and nearly 16,000 tonnes of CO¿.
These findings underscore the relevance of pavement condition in improving road transport sustainability and highlight the potential of road maintenance actions to contribute to climate change mitigation.
