In contrast, lane-level navigation is able to provide a reference trajectory that can actually be followed by an autonomous vehicle in the absence of other vehicles or obstacles. As a result, autonomous vehicles supported by road-level navigation must be equipped with a powerful real-time perception and decision-making system, which greatly increases the onboard computation burden.
However, in order to drive autonomously, it is necessary to know more about the exact positions where the vehicle should continue going straight or turn. Such guidance is accurate enough for human drivers.
#Opendrive atmoous vehicle series
Due to the limited accuracy of a road-level map, the generated road-level trajectory is more like a series of driving mission instructions than a specific trajectory that an autonomous vehicle can follow. 1, road-level navigation can only provide assistance in mission planning. However, when the target user is an autonomous vehicle, it is essential for the navigation system to provide more detailed guidance to help the vehicle accomplish its driving tasks.
The target uses of conventional navigation systems are human drivers, who are responsible for choosing the trajectory in real time. This study aims to develop a lane-level map-supported route-planning system, which is designed to support autonomous driving. A representative example of lane-level map-supported driving system was displayed in the Defense Advanced Research Projects Agency (DARPA) 2007 Urban Challenge, in Bohren et al.’s work, a road network definition file was created to describe lane-level driving conditions. When a map reaches the lane level, the navigation system can offer further driving assistance with greater accuracy. These functions can acquire lane-level details of the environment from digital maps in order to enhance the vehicle’s intelligence. The common point of these systems is that the required information is stored in a road-level map, which ignores the lane details. is another example of a map-enabled active safety system. For example, the electronic horizon program uses road slope angles to adjust the driving strategy to save energy. These functions are usually designed to assist human drivers, and the required accuracy is usually approximately 10 m. These map-supported intelligent driving functions can be further categorized into two groups as follows: In the literature, many intelligent driving functions have been developed based on the use of digital maps. In recent research, the development of advanced driver-assistance systems and autonomous driving technology requires increasing assistance from digital maps. At present, most vehicle navigation systems are based on road-level maps with limited and low-precision information. Since then, the benefits in travel efficiency provided by navigation systems have been widely accepted. The first application of a vehicle navigation system, in a BMW passenger car, can be traced back to 1994.
#Opendrive atmoous vehicle drivers
Tests were performed on both a grid network and a real lane-level road network to demonstrate the validity and efficiency of the proposed algorithm.Ī digital map navigation system assists drivers or intelligent vehicles to select the optimal route, given an origin and a destination. In addition, we model the travel costs allocated for lane-level road networks by analyzing vehicle maneuvers in traversing lanes, changing lanes, and turning at intersections. For lane-level route planning, we propose a hierarchical route-searching algorithm to accelerate the planning process, even in the presence of complicated lane networks. The current limitation of the lane-level map model is not its accuracy but its flexibility this study proposes a novel seven-layer map structure, called as Tsinghua map model, which is able to support autonomous driving in a flexible and efficient way.
This study proposes solutions to both problems. In order to extend current navigation systems to more applications, two fundamental problems must be resolved: the lane-level map model and lane-level route planning. In the near future, digital map navigation systems are expected to play more important roles in transportation systems. An increasing number of drivers are relying on digital map navigation systems in vehicles or mobile phones to select optimal driving routes in order to save time and improve safety.
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