In this paper, we revisit the concept of Prospect-basedUser Equilibrium in a dynamic context. We consider a mesoscopic Lighthill-Whitham-Richards(LWR) traffic model to determine time-dependent route costs. We propose a solution algorithm to determine the network equilibria. Monte Carlo simulations are used to account for the travel time distributions. We analyze the dynamic Prospect-basedUser Equilibrium compared to the benchmarks Deterministic and Stochastic User Equilibrium, on a synthetic Manhattan network. We set four endogenous reference points. We show that the setting of the reference point plays a very important role in the route flow patterns and on the network performance at an aggregated level, i.e. in terms of vehicles mean speed as well as internal and outflow capacities. Our results also enhance that the Prospect-basedUser Equilibrium is more sensitive to a change in the reference point than in the calibration of the users' risk-aversionand risk seekingparameters.