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Smart Car macro path planning

Author: LiKeDi
Tutor: GuanXin
School: Jilin University
Course: Vehicle Engineering
Keywords: Smart Car Macro path planning Comprehensive information on the road network Route guidance
CLC: U463.6
Type: Master's thesis
Year: 2011
Downloads: 217
Quote: 0
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Abstract

Smart Car is to deal with the problem of modern urban transport is an advanced solution. Smart car can be based on the surrounding road traffic environment and their own motion, in the local decision-making within the feasible region of safe, legal and efficient running track, so as to control the smart car to achieve unmanned. However, at the macro map, in order to reach a particular destination, to avoid blind with smart car navigation is an indispensable link. Vehicle positioning and navigation system, the digital map database, route planning and route guidance are three important complementary modules. In order to achieve path planning and route guidance, you first need a digital map databases. For smart cars, in addition to the common roads on a digital map form and roadside environmental information, but also the road network topology abstraction for reasonable path on the macro level and micro-level planning precise route guidance. Challenge competition at home and abroad unmanned vehicles used in road network definition file good abstract network topology. Smart cars driving through the analysis required during automatic road network and traffic environment information, refer to the standard navigation geographic data model that combines smart Car Challenge definition files using the road network, the paper designed a comprehensive road network hierarchy of expression and information storage Methods. Path planning is a key module navigation system, is widely regarded in the field of car navigation is a basic question. The road network in the nature of macro-path planning is to solve a graph search problem. Although the macro path is in determining a good driving task after the pre-planning, but taking into account the dynamic traffic information and emergencies, smart car should be taken by the event-triggered dynamic path planning approach. This paper compares a variety of graph theory classic search algorithms, analyzes their scope, test their performance and dynamic path planning based on smart car timeliness and accuracy of the algorithm requirements, selected macro path planning methods Algorithm foundation. On this basis, combined with comprehensive information on the road network, we propose a macro for smart car route planning methods to ensure the optimal path of macro and legitimacy. In order to provide a more accurate Smart car route guidance, real-time dynamic path planning does not affect the operational efficiency, this paper also envisioned a hierarchical path planning approach: the first level of intelligent vehicle path planning decisions only need to loop through sections and regional sequence; second level of planning in the sections or areas for smart cars provide directional guidance, it is only in the smart car is about to enter the road or area to be triggered. The ultimate goal of the macro path planning is to provide smart car automatic driving directional guidance, the specific needs intelligent vehicle travel path feasible region according to local decision-making and control. Track basis for making decisions has security, legitimacy, efficiency and ease of handling, etc., but the realization of intelligent vehicle route guidance, but also from both efficient and legitimate considerations. Smart car based on its own motion, preview the current direction of travel at a certain distance from the macro path through ergonomics macroeconomic indicators to assess how close the fastest path to the target point. Although we hope to reach the target point, speed is also subject to restrictions on road traffic regulations, which require intelligent vehicle based on the road network integrated information to judge the legality of speed. Finally, programming test for smart car macro path planning methods, and classical graph search algorithms run results were compared to verify the paper out of the macro-planning optimal paths and legitimacy, and reflected in the performance of the improved algorithm on the edge. This result also proves that the road network of integrated information data validity and completeness. The main contribution of this paper is to solve the driverless smart car navigation system in the application problems. In the process of trying to solve this problem in this paper, the expression of road network and storage integrated information, the macro path planning and route guidance and other key technologies, made some improvements and innovations.

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