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.