To study how traffic congestion affects logistics and transportation in terms of cost and carbon emission and countermeasures, we designed congestion-avoidance strategies to reduce vehicle waiting time and vehicle speed. The delivery time in a day is divided into three periods to calculate the roadway travel time under the congestion avoidance strategy. The mathematical models of cold chain logistics route planning with the objectives of minimizing carbon emissions and total costs are constructed, and the congestion-avoidance strategy is applied to plan the cold chain logistics route. An improved ant colony algorithm is proposed to solve the objective model. The reduced speed strategy generates fewer carbon emissions than the waiting strategy. The cost of distribution under different strategies is influenced by the form of distribution and the size of the customer. The results of the study show that the use of congestion-avoidance strategies can reduce the total cost of distribution and carbon emissions. The waiting strategy is more effective in general logistics, and the speed-reduction strategy is more effective in cold chain logistics. By comparing the carbon emissions generated for various average speeds under the reduced-speed strategy, the optimal driving speed is about 45 km/h.