Hyper pooling private trips into high occupancy transit like attractive shared rides

Area of Science:

• Transportation Science
• Operations Research
• Urban Planning

Background:

• High-order ride-pooling is computationally challenging due to large solution spaces.
• Existing ride-sharing models struggle with efficiency and scalability for complex urban demand.

Purpose of the Study:

• Introduce "hyper-pooled rides" as a novel, efficient ride-pooling solution.
• Develop a method to identify hyper-pooled rides within urban travel patterns.
• Demonstrate the efficiency gains of hyper-pooled rides compared to solo travel.

Main Methods:

• Algorithm development for identifying hyper-pooled ride opportunities.
• Simulation of urban demand patterns to test the algorithm.
• Analysis of vehicle hours, occupancy rates, and traveler satisfaction.

Main Results:

• Generated 40 hyper-pooled rides for 225 travelers from 2000 trips in Amsterdam.
• Reduced required vehicle hours sixfold, from 52.5 (solo) to 9 (hyper-pooled).
• Achieved an average vehicle occupancy of 5.8, with a maximum of 14.

Conclusions:

• Hyper-pooled rides present a scalable and efficient solution for urban mobility.
• This demand-driven approach optimizes itineraries for all passengers, enhancing ride-pooling viability.
• Significant reductions in vehicle usage demonstrate the potential for environmental and economic benefits.