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As a novel urban delivery approach, the coordinated operation of a truck–drone pair has gained increasing popularity, where the truck takes a traveling salesman route and the drone launches from the truck to deliver packages to nearby customers. Previous studies have referred to this problem as the flying sidekick traveling salesman problem (FSTSP) and have proposed numerous algorithms to solve it. However, few studies have considered the stochasticity of the travel time on the road network, mainly caused by traffic congestion, harsh weather conditions, etc, which heavily impacts the speed of the truck, thus affecting the drone’s operations and overall delivery routine. In this study, we extend the FSTSP with stochastic travel times and formulate the problem into a Markov decision process (MDP). The model is solved using reinforcement learning (RL) algorithms including the deep Q-network (DQN) and the …