Enhancing Ride-Hailing Efficiency through Machine Learning

Efficient Matching: ML pairs riders and vehicles intelligently to cut down on wait times.

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Demand Forecasting: To improve vehicle positioning, ML forecasts ride demands.

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System Equilibrium: High demand is met by idle cars thanks to algorithms.

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Service Equity: ML takes rider and driver preferences into account to provide equitable service.

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Benefits of Simulation: Tests demonstrate improved vehicle allocation accuracy and fairness.

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Enhancing Ride-Hailing Efficiency through Machine Learning

Efficient Matching: ML pairs riders and vehicles intelligently to cut down on wait times.

Demand Forecasting: To improve vehicle positioning, ML forecasts ride demands.

System Equilibrium: High demand is met by idle cars thanks to algorithms.

Service Equity: ML takes rider and driver preferences into account to provide equitable service.

Benefits of Simulation: Tests demonstrate improved vehicle allocation accuracy and fairness.

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