The Impact of Violations of Bicycles and Pedestrians on Vehicle Emissions at Signalized Intersections

Abstract EN

An intersection is a typical emission hot spot in the urban traffic network.

And frequent violations such as running the red light have been a critical social problem at signalized intersections in developing countries.

This article aimed to quantify the impact of violations (behaviors which will block the fleet) on emissions at signalized intersections.

Increased emissions of vehicles affected by violations are of two levels: (1) trajectory level for the first four affected vehicles and (2) traffic flow level for the subsequent vehicles.

At the trajectory level, the study focuses on the second-by-second activities of the first four affected vehicles.

First, the trajectory model of the first affected vehicle is developed.

Then, the trajectory of the other three vehicles is constructed using the Gipps car-following model.

At the traffic flow level, a linear emission model is developed to describe the relationship between emission factors and idling time in the one-stop (vehicle stop once) and two-stop (vehicle stop twice) scenarios based on the global position system (GPS)-collected data at 44 intersections in Beijing.

Based on the linear emission model, increased emissions at the traffic flow level are calculated as knowing the number of stops and idling time before and after violations.

The analysis of the subsequent vehicles is divided into unsaturated and saturated conditions.

Under the unsaturated condition, the emissions have barely increased due to the increase of idling time for one-stop vehicles caused by the violations.

Under the saturated conditions, the emission increment increases sharply as the one-stop vehicle gradually transforms to a two-stop vehicle because of violations, and the maximum emission increment reaches 45% in half an hour in the case.

The increment of emissions decreases steadily as the proportion of two-stop vehicles reaches 100% after violations, while the proportion before violations keeps increasing.