Dynamic real-time high-capacity ride-sharing model with subsequent information

Real-time, on-demand mobility systems have gradually revolutionised the transportation means. However, they continue to exhibit problems on inadequate vehicles at peak times. The popularity of 'sharing' may ultimately solve such problems as more passengers are served over time, particularly in high-demand (high-density) locations, thereby realising efficient, comfortable, and environmentally friendly transportation. While, existing sharing methods only arrange each order based on current information and do not apply subsequently received information to pursue more optimal route arrangements. Their research explicitly improves large-scale vehicle sharing methods using subsequent information and proposes the concept of a 'wait time threshold' for a vehicle, to manage the constraint contradictions in this process. Based on a representative high-demand case of serving all inbound and outbound passengers at Shenzhen Bao' an International Airport, a system with consideration of subsequent information provides significant improvements comparing to a system without it. The improvement performance varies with dates under different demand scenarios, high demand indicating a more optimistic influence. Therefore, having such a city-scale sharing model makes it possible to provide decision support to the transportation management department, which encourages to establish a low carbon city.