Evaluating impacts of road pricing and teleworking policy in Jakarta metropolitan area by analyzing activity pattern

In recent years, many countries have tried to adapt traffic demand management measures to tackle social problems such as reducing traffic congestion and lowering vehicle emissions. When trying to consider these traffic demand management measures, it is necessary to consider people's travel behavior in detail. It was understood that the implementation of traffic management measures such as road pricing and teleworking has not just affected people's modal choice and route choice, these measures have a high likelihood to change activity patterns of all the people affected either directly or indirectly. The current method of the conventional trip-based traffic demand forecasting (four-step model) focuses only on the change of travel behaviors; however, this method could not represent the change of activity patterns when the traffic demand management measures were implemented. Therefore, it is necessary to apply a much more robust Activity-Based Model (ABM) that could explicitly incorporate the change of activity patterns and estimate the effectiveness of implementing these measures. Thus, this study focuses on evaluating traffic demand management measures based on the change of activity patterns. By applying the ABM, road pricing and teleworking as traffic demand management measures were evaluated using the typical performance indices and activity patterns in the case of the Jakarta metropolitan area, Indonesia. Several key findings were found, population synthesis plays an integral part in ABM calculation. By applying ERP policy in the CBD area, some people shift mode, increase work-related activity patterns, and reduce the generation of secondary activities in order to avoid extra expenses for the toll. Teleworking policy increases other activities such as shopping and leisure, while it reduces work-related activities Hence, it was concluded that the analysis of activity patterns can provide additional information for decision-makers to consider in implementing a policy, by understanding how people change their activity patterns, much more efficient planning can be organized in the future.