Case Studies May 26, 2026
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How Can Taxi Ridesharing Optimize Commuting Time?

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A simulation study co-authored by AIM researchers indicates that taxi ridesharing can decrease overall commuter travel times by reducing passenger wait periods during peak hours.

A simulation study indicates that taxi ridesharing can decrease overall commuter travel times by reducing passenger wait periods during peak hours.

Taxi ridesharing (TRS), in which multiple passengers “share” a single driver and vehicle en route to their respective destinations, can optimize the travel time of commuters and reduce the optimal number of taxis in urban settings, according to a January 7, 2020, study published inTransportation Science, a peer-reviewed academic journal, and co-authored by Dr. Christopher Monterola and Dr. Erika Fille Legara of the Asian Institute of Management.

The study noted, however, that less car ownership fixes traffic only if people share taxi rides, rather than swap their private car for a private taxi.

Some of the main objectives of the paper tackle the following:

  • Is there an ideal taxi fleet size for a certain city size such that the demand for taxi service is met?
  • How will this number change if commuters are more open to TRS? 
  • Do commuters who share rides always sacrifice their total duration of travel (waiting time plus actual trip duration) for a more economical ride? 

Simulating an Entire Taxi System

To understand how ridesharing changes traffic dynamics, researchers from Singapore’s Nanyang Technological University, the Agency for Science, Technology and Research (A*STAR), and collaborators from AIM built a large-scale microscopic simulation of Singapore’s taxi network.

The simulation modeled both occupied and empty taxis, commuter bookings, boarding and drop-offs, route matching between passengers, and the roaming behavior of vacant taxis searching for riders. The system tracked the movement and status of every taxi and commuter across the road network in real time.

The researchers discovered a “phase transition” in taxi dynamics: there exists a tipping point between an oversaturated state, where demand exceeds taxi supply, and an undersaturated state, where too many taxis are on the road relative to demand.

“The boundary between these two phases effectively determines the optimal number of taxis a city should accommodate,” the researchers noted.

Why Ridesharing Can Save Time

The findings revealed that ridesharing does not always force commuters to sacrifice convenience for lower cost. Under certain conditions, sharing rides can actually reduce overall travel time.

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Frequently Asked Questions

Taxi ridesharing can reduce overall commuter travel time, but only under specific conditions. An AIM co-authored simulation study found that during peak hours or oversaturated conditions, ridesharing sharply reduces waiting times — even if trips involve minor detours — resulting in shorter total journey times for commuters.

The optimal taxi fleet size depends on the balance between supply and demand. The AIM co-authored study identified a "phase transition" tipping point — a boundary between oversaturated and undersaturated states — that effectively determines how many taxis a city should operate to meet commuter demand efficiently.

Ridesharing reduces the number of taxis needed to meet demand, according to the simulation study. As public acceptance of ridesharing increases, the system shifts toward greater efficiency — fewer vehicles are needed on the road, reducing empty taxi movement, congestion, and overall fleet size required for a given city.

No. Ridesharing does not always reduce travel time. The AIM study found that in undersaturated conditions — where taxi supply already exceeds demand — ridesharing may lengthen trip durations due to detours without meaningfully reducing wait times, making it less beneficial for commuters in those situations.

The AIM co-authored study concludes that ridesharing is a systems-level strategy, not just an economic option for commuters. For policymakers, the priority should be increasing vehicle occupancy and reducing empty vehicle movement — rather than simply adding more taxis — to reduce congestion and optimize road usage in urban areas.

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