Impact Analysis of Road and Parking Lot Congestion on Urban Rail Transit Modal Share

［Objective］To determine the optimal metrics indicators for measuring parking lot congestion and road congestion levels, it is essential to study their impact on the modal share of urban rail transit. ［Method］Eight potential metrics indicators for measuring parking lot congestion are proposed, considering factors such as the number of parking lots, the number of parking spaces, the walking influence range of urban rail transit stations, and travel distance reductions. Additionally, two possible metrics for road congestion are introduced, taking into account road section length and congestion level. Using the inter district transportation data in Kinki metropolitan region of Japan, covering passenger flow, road traffic and parking lots, an empirical analysis is conducted to evaluate the influence of each metric indicator on the variation in urban rail transit modal share. Correlation analysis is then used to determine the optimal metrics. ［Result & Conclusion］Increasing the destination parking lot and road congestion levels leads to a higher all-day urban rail transit modal share between traffic zones. When the O (origin) traffic zone is located in urban or suburban areas, the optimal metric for destination parking lot congestion is advisable to adopt the proportion of highly saturated parking spaces within a traffic zone, adjusted according to distance. When the O-zone is in the central district, the optimal metric indicator for congestion in destination parking lots should adopt the proportion of highly saturated parking lots within the traffic zone, adjusted according to distance reductions. The best metric indicator for road congestion should adopt the total length of congested roads between traffic zones weighted by congestion levels.