Trajectory outlier detection is significantly important in the field of trajectory data mining. Algorithm TOP-EYE (Top-k evolving trajectory outlier detection) is an efficient algorithm for detecting abnormal trajectory. From the point of view of the direction and density, algorithm TOP-EYE takes use of the method of evolutionary computation to detect anomalies, which is different from other algorithms. To improve the efficiency of mining trajectory outliers from massive trajectory datasets, the parallel algorithm for detecting trajectory outliers based on evolutionary computation, called PDAT-TOP (Parallel detecting abnormal trajectory based on TOP-EYE), is proposed. The algorithm takes advantages of parallel computation to improve the efficiency of detecting abnormal trajectory. Algorithm PDAT-TOP is implemented on Hadoop. Experimental results demonstrate that the algorithm can effectively detect abnormal trajectory, and it has high scalability and better speedup.