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The shareability potential of ride-pooling under alternative spatial demand patterns
Jaime Soza-Parra1, Rafał Kucharski2, Oded Cats1
1Transportation & Planning Department, Delft University of Technology, Delft, The Netherlands.
Transportmetrica. A, Transport Science
|February 28, 2024
Summary
Ride-pooling services are most effective with concentrated destinations and longer trips, potentially reducing vehicle hours by 18-59%. Shifting to polycentric travel patterns has minimal impact on ride-pooling efficiency.
Area of Science:
- Transportation Science
- Urban Planning
- Operations Research
Background:
- Ride-pooling services offer potential environmental and economic benefits by optimizing shared rides.
- Understanding the impact of spatial travel demand patterns on ride-pooling effectiveness is crucial for service optimization.
- Existing research often simplifies demand patterns, limiting insights into real-world complexities.
Purpose of the Study:
- To investigate how diverse spatial patterns of travel demand influence the efficiency of ride-pooling services.
- To quantify the shareability potential of ride-pooling across various demand scenarios.
- To identify key demand characteristics that maximize ride-pooling benefits.
Main Methods:
- Generation of synthetic travel demand patterns with varying numbers of attraction centers, destination dispersion, and trip length distributions.
- Application of a strategic ride-pooling algorithm to assess shareability potential.
- Utilizing ride-pooling specific metrics to evaluate service effectiveness.
Main Results:
- Vehicle-hour reduction due to ride-pooling can range from 18% to 59% under fixed demand levels.
- Ride-pooling efficiency increases with longer trip lengths and higher destination concentration around centers.
- Transitioning from monocentric to polycentric demand patterns shows a limited effect on ride-pooling prospects.
Conclusions:
- Spatial demand patterns, particularly destination concentration and trip length, significantly impact ride-pooling efficiency.
- Ride-pooling services can achieve substantial operational improvements by aligning with specific demand characteristics.
- Future research should consider the interplay of dynamic demand and network effects on ride-pooling performance.
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