Near-future traffic evaluation based navigation for automated driving vehicles considering traffic uncertainties

Kuen Wey Lin, Masanori Hashimoto, Yih-Lang Li

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Because it is difficult to find empty space in a developed city to accommodate more transportation infrastructures, the development of an effective navigation system is a low cost option for mitigating traffic jam. Regarding a future world where automated driving technologies have become mature and most vehicles follow the pre-scheduled route suggested by a navigation system, it is likely to predict the traffic jam accurately if the navigation system can know the pre-scheduled route of each vehicle. Recently, a navigation algorithm is presented for automated driving vehicles with the assumption that all the navigating query requests are processed by a single system. However, the aforementioned algorithm does not consider any kind of uncertainty originating from accidents and destination change. To get close to the real world, we propose a navigation algorithm with near-future evaluation capability that also allows some kinds of uncertainties. We compare our algorithm with a dynamic-update based conventional navigation algorithm without near-future evaluation capability. We download some metropolitan maps from OpenStreetMap and utilize the data of traffic flow from official statistics to randomly generate many sets queries. Experimental results show that the total cruising time is improved for each case.

Original languageEnglish
Title of host publication2018 19th International Symposium on Quality Electronic Design, ISQED 2018
PublisherIEEE Computer Society
Pages425-431
Number of pages7
ISBN (Electronic)9781538612149
DOIs
StatePublished - 9 May 2018
Event19th International Symposium on Quality Electronic Design, ISQED 2018 - Santa Clara, United States
Duration: 13 Mar 201814 Mar 2018

Publication series

NameProceedings - International Symposium on Quality Electronic Design, ISQED
Volume2018-March
ISSN (Print)1948-3287
ISSN (Electronic)1948-3295

Conference

Conference19th International Symposium on Quality Electronic Design, ISQED 2018
CountryUnited States
CitySanta Clara
Period13/03/1814/03/18

Keywords

  • Advanced Driver Assistance Systems
  • Planning and Decision
  • Self-Driving Vehicles

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