Modelling and managing the integrated morning-evening commuting and parking patterns under the fully autonomous vehicle environment

Abstract This study is the first in the literature to analytically investigate the traffic dynamics of the integrated morning and evening commutes when daily trips are completed with autonomous vehicles (AVs). Given the parking locations of AVs resulting from the morning commute, firstly we analyse the evening commuting pattern, at which no traveller can reduce the individual travel cost given other AVs’ times of departures from the parking spaces. The equilibrium traffic pattern at the evening commute is then integrated with the morning commute, where equilibrium choices of departure time from home and parking location are derived and analysed. We then study the integrated morning-evening commuting pattern at the system optimum and develop the road tolling scheme to achieve the system optimum. Furthermore, this study analyses the optimal AV parking supply strategy to minimise the total system cost, which is comprised of the total social parking cost and the total daily travel cost under either user equilibrium or system optimum traffic pattern. We also illustrate the modelling insights through numerical studies regarding relationship among traffic efficiency, tolling schemes and AV parking supply plans. This study highlights the differences in daily commuting and parking patterns between the AV situation and the non-AV situation, and sheds light on how traffic and parking should be managed or planned in the future.

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