Travel Behavior of Car Travelers with the Presence of Park-and-Ride Facilities and Autonomous Vehicles

Travelers' behavior is predicted based on their individual preferences. People search for alternatives to maximize their benefit from doing activities, such as increasing the activity time by minimizing the travel time. Traffic congestion and the scarcity of parking spaces in the city center motivate the decision-makers to encourage travelers to use the park-and-ride (P&R) system. An evaluation concerning the impact of using the P&R system on the travel behavior of car users is conducted. Some of the existing P&R facilities are incorporated into the daily activity plans of car travelers to produce new daily activity plans (i.e., P&R facility is considered an activity). By using the Multi-Agent Transport Simulation (MATSim) open-source tool, simulations of the daily activity plans including the P&R system and autonomous vehicles (AVs) are conducted. The study examines three scenarios: (1) a simulation of the existing condition, (2) a simulation of the daily activity plans of the travelers with the P&R system, and (3) a simulation of the daily activity plans of the travelers with the P&R system and AVs. The results show that using the P&R system increases the overall travel time compared with the existing conditions, and the use of AVs as a transport mode impacts the existing modal share as follows: 64 % of the car users switch to AVs, while 15 % of the car users switch to public transport. The output of this study might be used by policy-makers in parking pricing and the location of the P&R facilities.

Early Bird Scheme for Parking Management: How Does Parking Play a Role in the Morning Commute Problem

This paper extended the Vickrey’s point-queue model to study the early bird parking mechanism during morning commute peak hours. We not only investigated how commuters choose departure times in view of morning commute traffic congestion and the discounted early bird parking fee, but also analyzed the conditions which are determined for the existence of the user equilibrium in the analysis model provided in this paper. Moreover, the tendency of the total queuing time and the incremental parking pricing revenue was derived along with the different choice strategy between early bird parkers (ERPs) and regular parkers (RPs). The results showed that the number of commuters was jointly determined by the desired time and the bottleneck capacity for different schedules. Additionally, the method of fare incentive showed a better effect on reducing queue than the initial no-incentive method with the instantaneous travel demand. Most importantly, the incremental parking revenue can be increased by properly adjusting the parking pricing gap between ERPs and RPs. Our research not only provided several important propositions for the early bird parking mechanism but also included the optimal solutions for optimal parking pricing and schedule gap in two groups of parkers. This work is expected to promote the development of early bird parking to mitigate morning commute traffic congestion and motivate the related research of schedule coordination for regulating parking choice behavior in morning peak hours.

The role of parking pricing and parking availability on travel mode choice

This research examines the impact of parking pricing and parking availability on potential travel mode substitution among current drivers, in four case study areas in the Greater Toronto Area (GTA). It serves to evaluate opportunities to decrease private vehicle usage among the GTA’s workforce. More specifically, the objective of this study is to analyze whether and to what extent parking pricing and parking availability alter drivers’ willingness to change their mode of transportation. Results from ordered logit models demonstrated that a driver’s willingness to change their mode of transportation was statistically correlated with parking cost and parking availability. Parking availability also impacted the correlation between parking pricing and drivers' willingness to change their mode of transportation. The results from this MRP suggests that interventions focused on reducing driving for commuting purposes may focus on changing parking pricing, but depending on the availability of parking, the impacts of such policy/ program may be different.

The role of parking pricing and parking availability on travel mode choice

This research examines the impact of parking pricing and parking availability on potential travel mode substitution among current drivers, in four case study areas in the Greater Toronto Area (GTA). It serves to evaluate opportunities to decrease private vehicle usage among the GTA’s workforce. More specifically, the objective of this study is to analyze whether and to what extent parking pricing and parking availability alter drivers’ willingness to change their mode of transportation. Results from ordered logit models demonstrated that a driver’s willingness to change their mode of transportation was statistically correlated with parking cost and parking availability. Parking availability also impacted the correlation between parking pricing and drivers' willingness to change their mode of transportation. The results from this MRP suggests that interventions focused on reducing driving for commuting purposes may focus on changing parking pricing, but depending on the availability of parking, the impacts of such policy/ program may be different.

Assessing Urban Road Network Capacity considering Parking Supply and Parking Pricing

To enhance the assessment of the network capacity for a given urban road system, the effects of the parking management strategies at destination areas are supposed to be considered in the network capacity assessment model. This study provides an extended road network capacity model which takes into consideration both the parking supply and parking pricing at each traffic zone. The network capacity model is formulated as a bilevel programming problem, with the maximization of total trip generation in the upper level and the combined trip distribution and traffic assignment (CTDTA) problem in the lower level. To reasonably characterize the impacts of the parking pricing and parking delay due to the congestion effect, two classes of travel demand are involved in the CTDTA model. An efficient and practical algorithm is provided for the solution of the bilevel network capacity model. Numerical experiments show the advantages of the proposed model and also demonstrate the effect of the parking supply and parking pricing on the assessment results of the road network capacity.