On the morning commute problem with distant parking options in the era of autonomous vehicles

Due to the confined span of parking location choice for human-driven vehicles (HVs), the spatiotemporal imbalance in parking space utilization has always been a challenging problem in many major cities, leading to a substantial waste of precious land resources. However, in the era of autonomous vehicles (AVs) with parking autonomy, there are more alternative parking options available as AV can park at more distant locations away from the trip maker's destination. This paper aims to investigate the morning commute problem with consideration of AV commuters' distant parking choices in a many-to-one network. Parking sharing scheme is explicitly consid-ered, wherein AV travellers can choose to park at city centre at public parking facilities and then lease their own parking space out, park at home, or park at a shared parking space. We first examine how AV commuters in different residential clusters prioritize their parking location choices, as well as their willingness to share the vacant parking space. Then, we investigate the travellers' trip timing decisions and determine the resultant equilibrium travel pattern. Without other dynamic managing schemes, the model results indicate that appropriate CBD parking supply, together with differentiated parking charges/subsidy, can reduce the total queueing congestion significantly, yet at the cost of higher total travel cost.