ABMoS-DK (Agent Based Modal Shift-Denmark) is an agent-based model that analyzes the effects of transport policies on travelers’ behaviour for modal shift in the Danish national inland passenger transportation system. In ABMoS-DK, a group of travelers with homogeneous characteristics are regarded as agent that make decision in the traffic system according to a series of rational behavioural rules to meet annual extra short, short, medium and long distance travel demands. Within ABMoS-DK, agents are independent- the chosen transport mode for a given agent does not depend on the outcome for other agents.  The traveler’s heterogeneity is incorporated to take into account that different groups of users have specific preferences affecting modal choice. The mode choice algorithm is based on costs, both tangible (ticket price, fuel price, vehicle taxes, etc.), and intangible (Value of Time (VoT), travel time, level of service, and reliability). For each possible mode, the utility is calculated based on tangible and intangible costs for the same trip, and the algorithm chooses the mode with the lowest total cost and allow us to evaluate the comparative advantages of the alternative modes of transportation. The utility of each mode also depends on the socio-economic and behavioural characteristics of the households (urbanization pattern, income level, value of time). By changing the utilities of modes of transport, modal shift is incentivized within the model.

ABMoS-DK is calibrated by adjusting the decision rules in the mode choice algorithm with the aim of reproducing the historical data of modal share in 2010. The calibrated model is validated by reproducing the historical data of modal share in 2015. The calibrated model is then run until the last year of simulation in order to forecast the modal shares. ABMoS-DK is used to address the following research questions:

1.       How effective are strategies for influencing the travelers’ decision on choosing the mode of transport?

2.       How much is the maximum shift potential from the viewpoint of travelers without considering technological changes?  

3.       Which groups of agents (e.g., geographical zones, travel demand length, urbanization pattern and income group) are most sensitive to various strategies for incentivizing modal shift?

The seven modes of transport included in this model are grouped into three larger categories:

Private: Including private cars (since they represent the vast majority of private means of transportation)

Public: Including public bus, train, S-train and metro

Non-Motorized: Including bicycle and walk

The ABMoS-DK is capable of analyzing non-linear behavioural preferences of travelers and understand factors changing their rational behaviour towards shifting to more sustainable modes with bottom-up approach. The BU approach provides the opportunity to analyze the results on desired level of aggregation. This could help policy makers to formulate several scenarios and analyze the potential of imposing policies in different geographical zones of region in question, specific group of people (e.g., age, income, gender, education level, car ownership) and certain trip purposes in long-time horizon, which in turn are going to help approach the target set by Denmark to become fossil-free by year 2050.

One reference scenario and four alternative scenarios are developed and tested to determine the effect on modal shift, and shifts away from private cars in particular. All scenarios consist of the current expansion of existing Copenhagen Metro, which includes 15.5 km of new underground railway and 17 new stations. The new city ring line opens in 2020. The scenarios are: Expansion of Infrastructure (EIN); Incentives for Sustainable Modes (ISM); Disincentives for Private Cars (DPC) and Combination of all scenarios (COM). The tested strategies are “complementary” when combined; meaning that their combined implementation shifts more demand from car than each policy alone. Under an ambitious policy package to move away from private cars, Denmark has the potential to nearly cut car use in half by 2050 compared to BAU.

The model development efforts are done within the Nordic Flagship Project SHIFT (Sustainable Horizons for Transport) financed by Nordic Energy Research and the COMETS (Co-Management of Energy and Transport Sector) project financed by the Innovation Fund Denmark. The model is developed by Mohammad Ahanchian.