Privacy-preserving online ride-hailing (ORH) service enables riders and drivers to conveniently establish optimized ride-hailing through mobile applications without disclosing their location information. In order to alleviate the load of central server and unnecessary increased response latency caused by centralized schemes, we investigate the privacy-preserving ORH matching service in distributed deployment environment. In this paper, we first design three secure outsourced calculation protocols based on Distributed Two-Trapdoor Public-Key Cryptosystem (DT-PKC), including ciphertext packing, blinding and decryption protocol across domains (CPBD), secure Euclidean square distance calculation protocol across domains (SESDC) and secure minimum distance selection protocol (SMDS). Then, we apply the protocols to construct a privacy-preserving distributed ORH matching scheme named pdRide. Geographically distributed road-side unit (RSU) and computation service provider (CSP) collaborate to securely select the matching driver for the requesting rider within a range. Specifically, SESDC can effective calculate the Euclidean square distances between multiple drivers and requesting rider over the encrypted location information with different keys. SMDS can select the driver with the minimum distance for the requesting rider on the encrypted distances. Finally, experiment results demonstrate its effectiveness in terms of communication overhead, computation overhead and transmission latency.