Holiday destination choice in a continuous activity-based microsimulation

Abstract

Analysis of long-distance travel demand has become more relevant in recent times. The reason is the growing share of traffic induced by journeys related to remote activities, which are not part of daily life. In today’s mobile world, these journeys are responsible for almost 50 percent of the overall traffic. Consequently, there is a need of reliable long-distance travel forecast tools. A potential tool is an agent-based simulation. Due to the complex task of destination choice modelling, there are just few agent-based simulations available. This paper presents a continuous target-based simulation that simulates long-distance travel behavior for a long period of time. It is shown how destination choice is modelled in this agent-based simulation. We focus on the holiday destination choice, because it dominates the long-distances trips for the average traveler. The presented approach uses a heuristic to reduce the solution space. Afterwards, the optimal activity duration and activity location is computed simultaneously. This technique ensures a fast computation.