Careful selection and incorporation of smart technologies into emergency medical response protocols would not only benefit patients, but could also help convince the public that there are advantages to adopting advanced transportation technologies.
In the not too distant future, sensor-rich vehicles operating on smart roadways will automatically exchange safety information with other vehicles and with the roadway. Active sensing and ranging systems such as radar, laser scanners and ultrasonic sensors, will be fused with passive systems such as computer vision, to provide redundant sensing and prevent crashes, even in poor weather. If automation proceeds as expected, the changes will be revolutionary. The role of the driver will be modified (perhaps even eliminated) as in-vehicle and roadside technologies become more advanced. Motor vehicle crashes will be greatly reduced, longitudinal separation between vehicles will decrease and the capacity of roads will increase.
Yet, incidents which require time-critical emergency response will still occur. Smaller separations between vehicles could mean that if a crash did happen, it will likely involve more vehicles and lighter weight vehicles might provide less protection and/or result in different types of injuries. Occasional failures of sensors or technologies, unexpected maneuvers made by traditional vehicles, sensor performance lapses related to severe weather or unexpected interference with power or communications that in some way compromises system performance. Moreover, there will always be non-crash related personal injuries and illnesses which require ambulance transport. Emergency responders of all types will continue to operate on the nation’s roadways addressing injuries, illness and infrastructure disruptions.
This paper examines both the in-vehicle and infrastructure-based technologies which are emerging in the next five to eight years to assess how these technologies might impact emergency responders, particularly EMS. Technical aspects of various technologies developed by vehicle manufacturers and government programs are reviewed. A qualitative score was assigned as a way of ranking technologies to identify those which might be considered a priority for incorporating into emergency vehicles, as well as identifying those with marginal utility for EMS. Examples of technologies which were assigned a High priority included Forward Collision Warning, Intersection Movement Assistance, Do Not Pass Warnings and Emergency Vehicle Signal Preemption. Examples of those assigned a Low score included Stop and Go Cruise Control and Traffic Jam Assist, since ambulances intentionally violate many of the normal rules-of-the-road (and such violations would trigger repeated warnings to the driver). Still other technologies (Hard Shoulder Running, Lane Departure Warning), earned a mixed rating since their benefits for EMS were situation dependent.
The project also considered whether protocols need to be modified when EMS are responding to an emergency along a route where platoons or autonomous vehicles are operating and examined how the types of emergencies on the roadways may change in the future and describe event scenarios (or use cases) which may help guide planning.
The project provides transportation safety analysts with insights into potential sources of safety critical events and the frequency of their occurrence, and their relationship to property damage only, injury, and fatal crashes. Proper handling of emergency vehicles (and emergencies incidents on our roadways) is an important issue since it could be a key factor in giving the public the confidence needed to accept and support automation - and embrace the changes ahead. Continued investigation of these safety critical events could help to evaluate pre-crash and pre-near crash contributing factors, and the types of evasive maneuvers that make crashes avoidable.
Partners: New York State Depart of Transportation (NYSDOT), (NY) Governors Traffic Safety Committee (GTSC), Greater Buffalo Niagara Regional Transportation Council (GBNRTC)
Data Sources: SHRP 2 Naturalistic Driving Study (NDS), SHRP 2 Infrastructure and Supplemental Data, National Automotive Sampling System General Estimates System (NASS GES), Fatality Accident Reporting System (FARS), the Highway Safety Information System (HSIS), NY Safety Information Management System (SMS) and Accident Location Information System (ALIS)