Modal Split and Bus Fare Allocation for a Congested Bottleneck: Autonomous Vehicles and Buses

With the goal of reducing traffic congestion for urban commuters, and in alignment with the global shift toward smarter, more sustainable, and more equitable cities, the transportation field is faced with the challenge of improving and optimizing its systems. This paper will tackle the morning commute problem of a congested bottleneck shared between buses and autonomous vehicles (AVs). The objective of this study is to determine the optimal bus fare, departure time, and mode split simultaneously by minimizing the total system social travel cost using numerical techniques. In addition, the paper examines the sensitivity of the system social cost to parameters such as bus capacity and frequency. Using a simple numerical example, the relationships between mode split, bus fare, total cost of a bus trip, dispatching frequency, bus capacity, total cost of an AV trip, and AV fare to the system social cost are examined, and optimal values are presented and discussed. The distribution of trips and the influence of AV capacity are also explored. The findings suggest that, within a reasonable range, the optimal bus fare was the absolute minimum, and the optimal mode split was one with fewer bus passengers but no boundary value. Other interesting findings were observed assuming a predetermined and fixed bus fare. Overall, the methodology and results of this research paper offer valuable insights for traffic and transit authorities, which could aid in planning and operational decisions that ultimately reduce commuter delays and enhance the sustainability of the morning commute.