Novel Algorithm of Light Rail Passenger Trajectory Prediction Based on Markov Chain

By utilizing the smart card data from Chongqing light rail system, the travel characteristics of light rail passengers are analyzed and a trajectory prediction algorithm based on Markov chain is proposed. In the algorithm, the next travel trajectory of a passenger is classified by Bayesian classification and then predicted according to the relationship between the passenger's last travel trajectory and her/his residence. Experimental results based on real datasets show that the algorithm outperforms LTMT, RNN and 2-MC on predicting passenger's next travel trajectory. Meanwhile, the algorithm is coded on Spark, a big data processing framework, which reduces its runtime.