A system, comprising: at least one storage medium including a set of instructions for recommending at least one route associated with a request; and at least one processor configured to communicate with the at least one storage medium, wherein when executing the set of instructions, the at least one processor is directed to: receive a request from a terminal (130, 140), the request including a departure location and a destination; characterized in that the system is adapted to determine a Generative Adversarial Network model; determine at least one recommended route that travels from the departure location to the destination based on the GAN model; and transmit the at least one recommended route to be displayed on the terminal (130, 140) in response to the request, wherein to determine the GAN model, the at least one processor is further directed to: obtain a set of sample routes; generate a generative model; determine a set of estimated routes based on the generative model; generate a discriminative model; determine a first loss function of the discriminative model based on the set of sample routes and the set of estimated routes; determine whether the value of the first loss function is less than a first threshold; and store the discriminative model based on the determination that the value of the first loss function is less than the first threshold. at least one storage medium including a set of instructions for recommending at least one route associated with a request; and at least one processor configured to communicate with the at least one storage medium, wherein when executing the set of instructions, the at least one processor is directed to: receive a request from a terminal (130, 140), the request including a departure location and a destination; characterized in that the system is adapted to determine a Generative Adversarial Network model; determine at least one recommended route that travels from the departure location to the destination based on the GAN model; and transmit the at least one recommended route to be displayed on the terminal (130, 140) in response to the request, wherein to determine the GAN model, the at least one processor is further directed to: obtain a set of sample routes; generate a generative model; determine a set of estimated routes based on the generative model; generate a discriminative model; determine a first loss function of the discriminative model based on the set of sample routes and the set of estimated routes; determine whether the value of the first loss function is less than a first threshold; and store the discriminative model based on the determination that the value of the first loss function is less than the first threshold. receive a request from a terminal (130, 140), the request including a departure location and a destination; characterized in that the system is adapted to determine a Generative Adversarial Network model; determine at least one recommended route that travels from the departure location to the destination based on the GAN model; and transmit the at least one recommended route to be displayed on the terminal (130, 140) in response to the request, wherein to determine the GAN model, the at least one processor is further directed to: obtain a set of sample routes; generate a generative model; determine a set of estimated routes based on the generative model; generate a discriminative model; determine a first loss function of the discriminative model based on the set of sample routes and the set of estimated routes; determine whether the value of the first loss function is less than a first threshold; and store the discriminative model based on the determination that the value of the first loss function is less than the first threshold. obtain a set of sample routes; generate a generative model; determine a set of estimated routes based on the generative model; generate a discriminative model; determine a first loss function of the discriminative model based on the set of sample routes and the set of estimated routes; determine whether the value of the first loss function is less than a first threshold; and store the discriminative model based on the determination that the value of the first loss function is less than the first threshold.