Weather and Society Watch
Driving the Future
Mission Possible: Improving Driver Safety and Mobility with the Promise of Connected Vehicles
by Sheldon Drobot* and Michael Chapman**
For those of us working with Intelligent Transportation Systems, the recent Mission Impossible movie had a particularly alluring scene where Ethan Hunt and his passenger used a tactile heads-up display to route through traffic. Futuristic? Yes, but not as much as you might think. Since 2009, the University Corporation for Atmospheric Research's (UCAR) National Center for Atmospheric Research (NCAR) has worked with the U.S. Department of Transportation's (USDOT) Federal Highway Administration (FHWA) and Research and Innovative Technology Administration (RITA) to develop a Vehicle Data Translator (VDT) program that ingests, parses, processes, and quality checks mobile data observations (e.g., native and/or external) along with additional ancillary weather data (e.g., radar, satellite, fixed observations, and model data). The VDT then provides “road weather hazard” information, such as slick roads or reduced visibility, which could be combined with traffic information and other data in a decision support system such as the one shown in the film.
Conceptually, the use of vehicle data is relatively simple (See Figure 1). Many vehicles already sense ambient environmental conditions, such as air temperature and atmospheric pressure. Additionally, one can conceptualize how windshield wipers might be indicative of some type of precipitation condition, while anti-lock brake activation could suggest slippery roads. Our research is aimed at taking this suite of data, combining it with traditional atmospheric measurements from radar, satellite, and surface stations, and then providing road weather hazard information to a variety of users. Drobot et al. (2010) and Chapman et al. (2010) provide in-depth discussions on the VDT and the road hazard algorithms.
A critical component in developing these road weather hazard products is a better understanding of what the end user desires, and in what format they want that information. To address these questions, the American Meteorological Society (AMS) recently appointed an ad-hoc subcommittee with financial support from the FHWA Road Weather Management Program. The subcommittee subsequently developed a national driver preference survey targeted to approximately 1700 U.S. drivers. When provided with a list of new information types that are anticipated as being available in vehicles in the near future, respondents showed overwhelming support for most information types (Figure 2). Road closure information is marginally ahead of local weather conditions and local weather forecasts in terms of responses in the ‘very interested' and ‘extremely' interested categories. Interestingly, weather conditions do rate of higher interest than traffic conditions, accident information, and routing suggestions. Parking and points of interest are not highly desired by the respondents. Moreover, when looking at the responses for ‘not at all interested', local weather conditions and local weather forecasts have the lowest totals, with only 8% of the respondents showing no interest. For more details on the survey and other responses, please see AMS in the reference section (2011).
When assessing safety and efficiency on the roads, the traveling public already has access to several resources (e.g., 511 systems, traveler and/or traffic information). Although access to this information is becoming easier with increasing coverage and speed of the Internet, smart phones, and in-vehicle telematics technology, the AMS survey results suggest travelers are not currently obtaining much weather information while on the road (AMS 2011). With the research and development of the VDT, practical road impact information will be generated and passed along to the traveling public through the various communications and telematics channels. The weather information (e.g., slickness, visibility, precipitation type/rate) will be specific to the road surface and can be directly pushed to communications infrastructure such as 511, in-vehicle communications, and smart phones (Figure 3). Outside content providers in the private sector can also use this information to provide tailored applications to the end-user including forecast traffic times, smart-routing, and forecasted road impacts and/or hazards.
How might this work in reality? Imagine the following scenario:
During an anticipated typical morning drive to work, Samantha embarks on her normal 30-minute commute. The morning is clear but cold. Along the commute, Samantha begins to encounter some light fog but the roads are dry and traffic is moving at usual speeds of 55-65 MPH. As she approaches a low river valley with a couple of small bridges spanning a river, an audible warning of “Slow Down—Slick Roads in approximately two miles” alerts Samantha from her radio warning system, and she begins to steadily slow down. A few seconds later another alert says, “Collision alert—1.3 miles… take next exit for re-routing,” and Samantha heeds the warning. She takes the exit and is advised to re-route to another set of roads. She is told her expected time to her final destination will be delayed by approximately 20 minutes. She calls her work and lets them know that she will be in a few minutes late due to a wreck. After taking the new route, Samantha tunes into the local radio station in order to satisfy her curiosity as to what might have happened on her normal route. During the traffic report, the reporter explains that due to frost on the road and foggy conditions, four cars were involved in an accident on the viaduct and it is anticipated that traffic will be delayed by 1.5 to 2 hours. She is hopeful that everyone is okay, and relieved to have the connected vehicle re-rerouting information.
Over the last few decades, technology has advanced greatly. Yet, the way we drive our car today has not changed dramatically. With the coming revolution in connected vehicles, that is about to change. Hollywood is becoming reality. Get ready.
* Sheldon Drobot (firstname.lastname@example.org) is the scientific program manager for the Weather Systems and Assessment Program (WSAP) within the National Center for Atmospheric Research (NCAR) Research Applications Lab (RAL).
** Mike Chapman (email@example.com)is a project manager for WSAP within NCAR RAL.
American Meteorological Society, 2011: Realizing the Potential of Vehicle-Based Observations. 87 pp.
Chapman, M., S. Drobot, T. Jensen, C. Johansen, W. Mahoney III, P. Pisano, and B. McKeever, 2010: Using Vehicle Probe Data to Diagnose Road Weather Conditions – Results from the Detroit IntelliDrive(SM) Field Study. Transportation Research Record: Journal of the Transportation Research Board , 2169 , 116-127
Drobot, S.D., M. Chapman, P.A. Pisano, and B.B. McKeever, 2010: Using vehicles as mobile weather platforms. Advances in Intelligent and Soft Computing , 81 , 203-214.
Figure 1. Sketch of the Connected Vehicle Concept
Figure 2. Interest level in various road and weather conditions for travelers
Figure 3. Flow diagram for information from connected vehicles and the VDT to the traveling public