STUDY OF THE EFFECT OF VEHICLE DRIVER BEHAVIOUR ON VEHICLE EMISSIONS OF CARBON MONOXIDE AT SIGNALIZED INTERSECTIONS

Al-Neami, Ali H.; Alani, Hamed M.; Talabany, Aso F.S. · 2006 · DOAJ

DOI: 10.31026/j.eng.2006.01.06

archive: archived pipeline: cataloged verified

Get this paper ↗ (DOI — opens at the source; we link to it, we don't host it)

Summary

This study investigates the impact of driver behavior on carbon monoxide (CO) emissions at signalized intersections, addressing the health and environmental concerns associated with vehicular pollution in urban areas. The research was motivated by the significant contribution of motor vehicles to urban air pollution and the specific increase in emissions caused by interrupted traffic flow, such as stop-and-go conditions at intersections. The authors aimed to quantify how specific driver actions, including reaction times and queuing behaviors, influence excess CO emissions. The methodology involved field observations at four signalized intersections on the Kurdistan Ring Road in Erbil City, Iraq, during the morning peak hours of 1999. Traffic data were collected via video recording and processed using a custom computer program called EVENT to extract precise traffic parameters, such as vehicle arrival and departure times. Simultaneously, tailpipe emissions were measured using an Analytical Mobile Gaseous Emissions CART P8334 machine. The study sampled 600 gasoline-powered vehicles (taxis and private cars) and 100 diesel-powered vehicles (buses and trucks), capturing emission rates across various operating modes: cruising, accelerating, decelerating, and idling. Statistical analysis was performed using SPSS to evaluate the relationships between driver behavior metrics and CO emission levels. The results demonstrated that transient operating modes significantly affect emission rates, with deceleration producing the highest CO emissions, followed by acceleration and idling. Gasoline vehicles were found to emit higher percentages of CO compared to diesel vehicles. The study identified strong correlations between specific driver behaviors and excess CO emissions. First, driver starting delay—the time lag between the green signal and vehicle movement—positively correlated with increased CO emissions due to prolonged idling. Second, average vehicle queue length was shown to increase excess CO emissions, as longer queues result in more vehicles idling and greater time spent in low-speed modes. Third, the percentage of stopped vehicles directly increased emissions by extending idle and deceleration times. Finally, "end lost time," defined as the unused portion of the amber signal interval when drivers choose to stop rather than proceed, also correlated with higher CO emissions. The data indicated that most drivers passed the stop line within the first 1.5 seconds of the amber phase, but those who delayed contributed to increased emissions. The findings imply that traffic management strategies can effectively reduce urban air pollution by optimizing intersection control. The authors conclude that improving vehicle movement during amber periods and reducing driver perception-reaction times can lower excess CO emissions without compromising safety. These results provide actionable insights for local authorities, traffic engineers, and transportation planners to design signal timing and intersection controls that minimize environmental impact. By understanding the link between driver behavior and emissions, stakeholders can implement measures that reduce the health risks associated with high CO concentrations in congested urban environments.

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed.

Summary generated by qwen3.6-27b-prismaquant on 2026-06-26; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• traffic density