SAINT+: Self-Adaptive Interactive Navigation Tool+ for Emergency Service Delivery Optimization

نویسندگان

  • Yiwen Shen
  • Jinho Lee
  • Hohyeon Jeong
  • Jaehoon Jeong
  • Eunseok Lee
  • David Hung-Chang Du
چکیده

This paper proposes an evolved Self-Adaptive Interactive Navigation Tool (SAINT+) to reduce the delivery time of emergency services and to improve navigation efficiency for the vehicles influenced by accidents. To the best of our knowledge, SAINT+ is the first attempt to optimize the delivery of emergency services as well as the navigation routes of vehicles around accident areas. Based on the congestion contribution model of SAINT and aggregated information from vehicles in the vehicular cloud, we propose a virtual path reservation strategy for emergency vehicles to guarantee a fast emergency service delivery. We also develop an accident area protection scheme based on an adjusted congestion contribution matrix and protection zones to evacuate vehicles in the accident area. To further reduce travel delay of neighbor vehicles in the accident area, we also present a dynamic traffic flow control model. Through extensive simulations with a real-world map, SAINT+ outperforms other state-of-the-art schemes for the travel delay of emergency vehicles. In scenarios with a high vehicle density, SAINT+ reduces the travel delay of emergency vehicles by 42.2%.

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عنوان ژورنال:
  • IEEE Trans. Intelligent Transportation Systems

دوره 19  شماره 

صفحات  -

تاریخ انتشار 2018