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The in-depth accident study to evaluate the advanced automatic collision notification system in Japan
Institute of Traffic Accident Research and Data Analysis, Tokyo.
Nippon Medical University.
Nihon University.
HEM-Net.
2018 (Engelska)Konferensbidrag, Publicerat paper (Refereegranskat)
Abstract [en]

In Japan, an automatic collision notification service called “HELPNET” has been in operation since 2000. In addition to HELPNET, the pilot study on Advanced Automatic Collision Notification (AACN) and Helicopter Emergency Medical Service (HEMS) system, so-called D-Call Net, had started in several prefectures of Japan by the D-Call Net committee in affiliation with Emergency Medical Network of Helicopter and Hospital (HEM-Net) since November 2015.

Regarding D-Call Net pilot system, HELPNET infrastructures already developed for existing Japanese ACN service were used for sending vehicle data to HELPNET center. In the case of accident, Event Data Recorder (EDR) data was added on usual HELPNET data and transmitted from a vehicle to HELPNET server at HELPNET center. D-Call Net server got vehicle data such as Delta V and seatbelt status, etc. and input them to the algorithm. The algorithm result was transmitted to “iPad” at the Trauma Center nearby the crash spot. Simultaneously, an operator of HELPNET made Emergency Call to the fire department. In case of severe injury, “iPad” indicated the serious situation and a doctor rushed to the accident spot by a helicopter. After the helicopter with a doctor and a nurse took off, verbal communications between the helicopter pilot and the fire department were started to decide a rendezvous point nearby the crash spot. After landing, the doctor and the nurse contacted the injured occupant who was curried by an ambulance there. This system is operated at about 30 trauma centers with Helicopter Emergency Medical Service in Japan, as of 17 November 2017.

This paper is focusing on the in-depth accident study to evaluate the Advanced Automatic Collision Notification and Helicopter Emergency Medical Service system (D-Call Net) in Japan. For this system, the Occupant Injury Predict Algorithm newly developed by Nihon University was utilized. About 2.8 million of Japanese accident data, so called ITARDA Macro Data, were calculated to define logistic regression risk curves of fatal and severe injured drivers and front passengers. During the pilot study, accident cases should be collected and accident database should be established in order to evaluate D-Call Net algorithm and D-Call Net Helicopter Emergency Medical Service operation at both fire departments and trauma centers. The results will be feedback on the actual service planned to start in spring 2018.

Ort, förlag, år, upplaga, sidor
Linköping: Statens väg- och transportforskningsinstitut, 2018.
Nationell ämneskategori
Farkostteknik
Forskningsämne
X RSXC
Identifikatorer
URN: urn:nbn:se:vti:diva-12893OAI: oai:DiVA.org:vti-12893DiVA, id: diva2:1203789
Konferens
18th International Conference Road Safety on Five Continents (RS5C 2018), Jeju Island, South Korea, May 16-18, 2018
Tillgänglig från: 2018-05-16 Skapad: 2018-05-04 Senast uppdaterad: 2018-05-25Bibliografiskt granskad

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