International Journal of Advanced Robotic Systems (Apr 2013)

Autonomous Navigation and Obstacle Avoidance of a Micro-Bus

  • Carlos Fernández,
  • Raúl Domínguez,
  • David Fernández-Llorca,
  • Javier Alonso,
  • Miguel A. Sotelo

DOI
https://doi.org/10.5772/56125
Journal volume & issue
Vol. 10

Abstract

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At present, the topic of automated vehicles is one of the most promising research areas in the field of Intelligent Transportation Systems (ITS). The use of automated vehicles for public transportation also contributes to reductions in congestion levels and to improvements in traffic flow. Moreover, electrical public autonomous vehicles are environmentally friendly, provide better air quality and contribute to energy conservation. The driverless public transportation systems, which are at present operating in some airports and train stations, are restricted to dedicated roads and exhibit serious trouble dynamically avoiding obstacles in the trajectory. In this paper, an electric autonomous mini-bus is presented. All datasets used in this article were collected during the experiments carried out in the demonstration event of the 2012 IEEE Intelligent Vehicles Symposium that took place in Alcalá de Henares (Spain). The demonstration consisted of a route 725 metres long containing a list of latitude-longitude points (waypoints). The mini-bus was capable of driving autonomously from one waypoint to another using a GPS sensor. Furthermore, the vehicle is provided with a multi-beam Laser Imaging Detection and Ranging (LIDAR) sensor for surrounding reconstruction and obstacle detection. When an obstacle is detected in the planned path, the planned route is modified in order to avoid the obstacle and continue its way to the end of the mission. On the demonstration day, a total of 196 attendees had the opportunity to get a ride on the vehicles. A total of 28 laps were successfully completed in full autonomous mode in a private circuit located in the National Institute for Aerospace Research (INTA), Spain. In other words, the system completed 20.3 km of driverless navigation and obstacle avoidance.