Law enforcement is critical for improving traffic safety. However, disputes on the equity in law enforcement have continuously exacerbated the distrust between the public and the law enforcement agencies in the United States in the past decades. This study explores this issue by identifying factors influencing outcomes of traffic stops - the most common scenarios where people need to deal with law enforcement agencies. To exclude possible confounding factors, this study specifically focuses on speeding traffic stops leading to tickets or warnings in Burlington, Vermont from 2012 to 2017. The Euclidean distance-based autologistic regression model is adopted due to the presence of spatial correlations of traffic stops. It is found that with the increasing speeding severity, a speeding traffic stop is more likely to lead to a ticket. Speeding of 20 mph over the speed limit significantly influences the penalty type. Young drivers, male drivers and minority drivers are found to be more likely to be issued tickets, which suggests the possible presence of some inherent biases against these groups. In addition, time of day and month are also found to influence the likelihood of receiving speeding tickets. These findings are expected to help both the public and law enforcement agencies to better understand the characteristics of law enforcement and take appropriate measures to eliminate possible biases.