Automatic driving taxi scheduling system based on big data of car networking

Abstract

The invention relates to the technical field of computers, in particular to an automatic driving taxi scheduling system based on big data of car networking. The system comprises an intelligent scheduling system used for data visualization through a computer to visually display the change of traffic information; and the scheduling system obtains automatic driving taxi vehicle information and passenger taxi taking demands, and the scheduling of the automatic driving taxi is improved through adoption of an intelligent algorithm for globally searching an optimal solution to achieve the global optimization and distribution of taxi resources. The automatic driving taxi scheduling system can greatly improve the taxi industry management, decision-making capability and service level, can relieve the pressure of traffic law enforcement manpower shortage, breaks the limitation of a traditional taxi, and avoids the phenomena of a high empty driving rate, uneven resource distribution, passenger picking and carrying. The traffic hazard caused by the self reason of a driver under the condition of driving by a person cannot occur.

Description

technical field [0001] The invention relates to the field of computer technology, in particular to an automatic driving taxi dispatching system based on big data of Internet of Vehicles. Background technique [0002] The increasingly powerful artificial intelligence and the vigorous development of the mobile Internet have given birth to large-scale data analysis application scenarios such as the Internet of Vehicles. With the maturity of Internet of Vehicles technology, research on autonomous driving has also made many qualitative leaps. The self-driving taxi dispatching system proposed in this patent is based on big data technology, integrates geographical information, passenger travel rules, on-board sensor information, and network communication, and organically combines traffic elements such as people, vehicles, roads, and networks to form a set. Traffic dispatching system for data collection, travel knowledge mining and route optimization. [0003] Currently existing d...

AI Technical Summary

Problems solved by technology

The dispatching methods mentioned in the existing schemes cannot be fully applied to the traffic transportation after the popularization of self-driving taxis in the future society.

From a macro point of view: these schemes only involve simple scheduling behaviors, but do not take into account more complex scheduling situations, such as considering space-time characteristics, passenger needs, and road condition changes; Better use of data, traffic road condition prediction, safety precautions, information collection and enterprise management, etc., failed to subdivide the detour mode of taxi carpooling (the detour mode has shared mode and non-shared mode, and the shared mode is also Divided into complete sharing, internal sharing, partial sharing, and detour sharing, see figure 1 ); there are few existing schemes that involve big data car networking for automatic driving taxi dispatching systems, either starting from automatic driving, or cutting in from the perspective of big data, or just the intelligent dispatching of traditional taxis, which have not achieved all aspects of organic to integrate

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