Ride demand can move cars away from the place where the next requests will appear. In this scenario, many trips begin near the city center and end farther out, while fewer passengers travel back inward. Drivers accumulate around the edges as central riders wait or give up.
The baseline run shows that imbalance emerging from ordinary service. In the second run, selected empty vehicles return toward the center before receiving another passenger, while some remain in outer areas to preserve local coverage. The live displays and final comparison track completed rides, waiting riders, lost requests, and empty-car supply. The insight is that an empty trip can be productive if it places a vehicle where future demand is more likely. But repositioning also consumes time and distance, so sending every vehicle to the apparent hotspot would be too crude. A good strategy balances anticipated demand against the opportunity cost of moving capacity.
An available taxi is useful to passengers even while it is carrying nobody. More idle vehicles spread through a service area make pickup faster, reducing the delay between requesting a ride and entering a car. Keeping those vehicles available, however, costs driver time and money.
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One ride has two different clocks. For the passenger, the trip begins with a request and includes waiting to be matched, waiting for the assigned car to arrive, and riding to the destination. For the driver, the service cycle begins while available, continues through pickup and transport, and ends only when the car is ready for another match.
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An on-demand car, a shared ride, and a fixed-route bus use vehicles very differently. An exclusive car offers direct travel but spends substantial time and distance on each passenger. Pooling shares some of that work at the cost of detours and coordination. A bus gains scale when enough people use a common corridor, but offers less flexible access.
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