In recent years, the urban traffic pressure is increasing, and the proportion of public travel in people's travel mode is increasing year by year, even higher than other travel modes such as cars, bicycles and so on. As the proportion of public travel increases year by year, the demand becomes more and more complex, and the traditional public transport travel mode urgently needs to be upgraded.
For public transport, the characteristics of special lane driving, slow speed, fixed line and short distance reduce the requirements of scene recognition, safety control and other algorithms on the whole, so that it has the basic conditions to realize intelligent operation. Public transport may become the first industry to realize intelligent driving.
In the process of implementation, there are two aspects: one is that the bus is driven automatically or even driverless by auxiliary driving, the other is the intelligent bus background scheduling system.
For buses, transporters and scenic spots sightseeing vehicles with relatively single route and high-intensity work of drivers, the realization of automatic driving or unmanned driving can greatly alleviate driver fatigue. This kind of vehicle has a single driving line, low environmental complexity, and low speed compared with ordinary vehicles. By using sensors and lidar to plan the path, it can detect the distance between the vehicle and the roadside more accurately, so it is easier to take the lead in promoting driverless technology. At present, self driving buses in many provinces have been tested on the road. For example, on December 2, 2017, the driverless bus in Shenzhen was put on the road for test. It is reported that the bus has realized the functions of pedestrian under automatic driving, vehicle detection, automatic stop by station, obstacle detour, lane change, deceleration and avoidance, emergency stop, etc.
The traffic management system in its (Intelligent Transportation System) can carry out real-time video monitoring of public transport vehicles, realize intelligent dispatching of public transport, automatic station reporting, passenger counting and other functions, automatically and effectively adapt to various traffic conditions, reasonably guide and dispatch vehicles, and reduce traffic by means of automatic charging, automatic driving, in transit driver information and path guidance Traffic delays and traffic jams will improve the capacity and service level of the road network.
In the advanced vehicle control and safety system, there are many safety management measures, such as the automatic anti-collision system of the vertical and horizontal intersection, the system of the dangerous encounter police, the vehicle safety monitoring and rescue system, which will greatly reduce the traffic accidents. Comprehensive and rapid application and implementation of its will solve various major traffic problems in the current city to the greatest extent, not only facilitate the public, but also facilitate the traffic management of the whole city, and truly provide a safe, fast and comfortable public transport environment for the public.
Conclusion: significant progress has been made in the field of narrow sense AI, and the application of artificial intelligence in vehicles has exceeded the public imagination. For example, the United States has begun to connect the response scheduling and routes used by taxi services with the scheduling and tracking software provided for public transport to provide faster and cheaper public transport services. However, the public transport system is a more complex field, which belongs to the general AI field in the future, that is, strong artificial intelligence. In addition, the current driverless technology is not mature, so it will take some time for the full implementation of the artificial intelligence public transport system.