This study focused on the ride-hailing assignment problem, aiming to optimize drivers' behaviors with respect to simultaneous objectives such as maximizing service level, minimizing CO2 emissions, and minimizing riders' waiting times. Four different policies were proposed and tested with a real-world case study. With respect to current literature, we present a more realistic simulation model, capturing all characteristics of a ride-hailing system and using road networks to approximate real-time road conditions. Furthermore, it is the first work that tests the effects of different passengers' arrival conditions and analyzes the multiple objectives for different zones of a large city. Results suggest that different passengers' arrival conditions affect the four proposed policies nearly identically. Finally, the policy of drivers remaining static instead of driving while searching for passengers had the highest service level and lowest average distance per ride.