Abstract
The wide spread traffic congestion witnessed in urban transportation network, especially during rush hours, aggravates vehicle
exhaust emissions. Previous studies reveal that congestion not only slows down the traffic flow but also significantly increases
emissions. This highlights the need of accounting for congestion-related emissions in transportation planning. In this paper,
congestion-related emission is incorporated into a transit bus scheduling problem by a nonlinear programming model to minimize
the total respirable suspended particle emissions during rush hours. A real-world instance is then formulated using the proposed
model and solved by CPLEX in a case study. Computation results from the case study indicate that by taking congestion-related
emission into account, the urban transportation planning can not only significantly reduce the total particle emissions, but also save
passengers’ travel time at the cost of relatively small increases in distance traveled.