Simulating the impacts of on-street vehicle parking on traffic operations on urban streets using cellular automation

In recent years, many bicycle lanes on urban streets are replaced with vehicle parking places. Spaces for bicycle riding are reduced, resulting in changes in bicycle and vehicle operational features. The objective of this study is to estimate the impacts of on-street parking on heterogeneous traffic operation on urban streets. A cellular automaton (CA) model is developed and calibrated to simulate bicycle lane-changing on streets with on-street parking. Two types of street segments with different bicycle lane width are considered. From the simulation, two types of conflicts between bicycles and vehicles are identified which are frictional conflicts and blocking conflicts. Factors affecting the frequency of conflicts are also identified. Based on the results, vehicle delay is estimated for various traffic situations considering the range of occupancy levels for on-street parking. Later, a numerical network example is analyzed to estimate the network impact of on-street parking on traffic assignment and operation. Findings of the study are helpful to policies and design regarding on-street vehicle parking to improve the efficiency of traffic operations.