Decision Making in an Agent-Based Simulation of Long-Distance Travel Demand

被引：2

作者：

Janzen, Maxim ^{[1
]}

Axhausen, Kay W. ^{[1
]}

机构：

[1] Swiss Fed Inst Technol, IVT, Stefano Franscini Pl 5, CH-8093 Zurich, Switzerland

来源：

9TH INTERNATIONAL CONFERENCE ON AMBIENT SYSTEMS, NETWORKS AND TECHNOLOGIES (ANT 2018) / THE 8TH INTERNATIONAL CONFERENCE ON SUSTAINABLE ENERGY INFORMATION TECHNOLOGY (SEIT-2018) / AFFILIATED WORKSHOPS | 2018年 / 130卷

关键词：

agent-based simulation; long-distance travel demand; continuous simulation; target-based approach; decision making; C-TAP; MODEL;

D O I：

10.1016/j.procs.2018.04.072

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Analysis of long-distance travel demand has become more relevant in recent times due to the growing share of traffic induced by journeys related to remote activities. Consequently, there is a need of reliable long-distance travel forecasting tools like agent-based simulations. This paper presents a target-based simulation that simulates long-distance travel behavior for a long period of time. It is shown how decisions are modelled in this simulation. Activity type, duration, destination and mode are chosen simultaneously with respect to time and monetary budgets. The presented approach uses a heuristic to reduce the choice set followed by optimizing a discomfort function. (C) 2018 The Authors. Published by Elsevier B.V.

引用

页码：830 / 835

页数：6

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