Abstract: This review summarized the main methods for the quantification of traffic exposure in studies assessing the health impacts of traffic-related air pollution (TRAP). External and internal exposure assessments are two main approaches to estimate TRAP exposure. In most studies, the quantitative estimation of TRAP external exposure mainly depends on traffic-related metrics (e.g. distance to roads, traffic density) and the prediction of TRAP concentrations based on various models (e.g. air dispersion model, land use regression model, hybrid individual-exposure model). The former is considered as a set of alternative indicators for the long-term effect of TRAP, which can capture long-term changes in traffic emissions at a small spatial scale, and focuses on comprehensive indicators of environmental risks other than traffic-related air pollutants. But it always ignores individuals who are affected by the combined effects of many roads with different traffic levels, and fails to take the effects of conditions such as weather into account. While the latter can better describe the spatiotemporal variability of pollutants without the establishment of intensive monitoring network, but the data quality and accuracy are the main constraints to the accuracy of the models. Additionally, researchers have tried to explore some specific biomarkers to be the proxy of TRAP exposure, such as S-phenylmercapturic acid, trans, trans-muconic acid, 1-hydroxypyrene, and micronucleus frequency. The review was expected to provide a theoretical basis for epidemiological studies to evaluate the correlations between TRAP exposure and different diseases in human, and to give a deeper insight into the related mechanisms.