Abstract "Severe thunderstorms, such as tornadoes, pose a significant threat to the traveling public
Description "Task 1: Conducting a Comprehensive Literature Review on Existing Mobile Apps
In this task, a comprehensive literature review will be conducted to find what Mobile Apps
are available for drivers on the road to receive extreme weather warning, focusing on
tornado warning. This is to find the status of existing Mobile Apps, understanding what
information and what function the existing Mobile Apps provide? Besides weather
condition, does it provide the information on where to get off the highway? Does it provide
the information on tornado shelter? Does any App provide information on where to go for
drivers by protecting both their lives and their cars?
Through a preliminary literature review, the research team found the following
Mobile Apps. For instance, the App of “Drive Weather” is designed to enhance users’
driving experience by delivering personalized weather forecasts along their routes, such
as cloud cover, wind speed, and temperature, ensuring users stay informed before
embarking on your journey. Moreover, it keeps users updated with weather alerts,
prioritizing safety throughout the trip. Another noteworthy app in this category is “Weather
on the Way”. Building upon the features of “Drive Weather”, it takes things a step further
by predicting road conditions based on weather forecasts, such as “wet roads”. This
attention to details empowers users to make informed decisions during their travels,
promoting both convenience and safety. Although this App provides users with possible
weather conditions during their road trip, it does not address such aspects as avoiding
extreme weather or guiding users to nearby shelters.
At the beginning of this project, besides a comprehensive literature review, the
team will interview Kelsey Angel (Meteorologist in chief) of the NWS office in Springfield,
MO and Chris Engelbrecht (Assistant to the Chief Safety and Operations Officer of Safety
and Emergency Management) of MODoT to understand what they do for tornado hazard
mitigation for drivers and what functions they hope the App to have.
Task 2: Gathering Information on Weather Condition from NWS and on Road
To achieve route optimization for vehicle drivers, the server needs to gather different
types of information, as detailed below. This task will identify where to gather the related
information.
1) The server needs to gather the information on where the vehicle (vehicle driver) is
(longitude and latitude). It can be obtained from the GIS of the user’s cell phone.
2) The server needs to gather the information on the highway (GeoSpatial data) and
traffic conditions. A possible source is Highway Performance Monitoring System
(HPMS), which was compiled from the Federal Highway Administration (FHWA)
and is part of the U.S. Department of Transportation (USDOT)/Bureau of
Transportation Statistics (BTS) National Transportation Atlas Database (NTAD).
This geodatabase provides HPMS data for each state as an individual feature
class. The HPMS data reflects the extent, use, condition, and performance of the
public roads in the United States. Another option is to extract traffic data from other
Apps, such as Google Maps [1].
3) The server needs to gather the information on public shelters. It is important to
note that not all communities have such shelters, and the availability may vary from
state to state and even city to city. To obtain this information, possible sources
include the state government website [2] and the services provided by American
Red Cross services [3].
4) The server needs to receive the weather information from the NWS. The weather
information will include the predicted tornado path and intensity and available
weather radar information [4]. The research team will check with the NWS office
to see whether they can develop a more localized assessment of tornado risk; The
research team will also check with them whether they could provide the weather
information more frequently.
Task 3: Developing a Route Optimization Algorithm
Based the information gathered in Task 2, Task 3 is to develop a route optimization
algorithm to guide drivers on safe routes to a nearby public shelter. Assume that a number
of vehicles are on a road and all drivers have installed the mobile App developed by this
project. The App real-time sends the information on the vehicle’s location to the server.
At the same time, the NWS forecasting system real-time sends the server the location of
the tornado and the predicted path and moving speed. The optimization is to control the
speed of vehicles to try to leave the tornado as quickly as possible, for example, either
speed up or slow down; leave the road or not; or go to a shelter or not.
To optimize the route, a previous “customized route optimization algorithm” will be
adopted here. This algorithm was originally proposed to combine the criminological data
and regular map function to predict a safe route with lower security risk [5]. In the context
of this project, it will be the regular shortest route algorithm combined with a goal of
minimizing extreme weather risk, to provide the recommendations for the optimal route
for travelers on the road, including where to go, which lane to take, which exist to get off
the highway, what speed to drive, etc.
Task 4: Developing a Mobile App for Delivering Message
In this task, a Mobile App will be developed to facilitate in delivering the message on the
recommended optimal route to vehicle drivers. This App is called “Driving through
Extreme Weather” Mobile APP, short for “DEW App”. Some details for the App
development are provided below.
1) Platform Selection: Develop it on Android first and then make it cross-platform (iOS
& Android).
2) Design: Create wireframes and mockups to visualize the app’s layout and user
interface. A Trial-and-Error approach will be applied to ensure excellent user
experience and make the design intuitive and user-friendly.
3) Backend Development: As the proposed App needs server-side functionality as
well as databases, the backend infrastructure will be developed and constructed
at Missouri S&T."
Objective "This project will produce the following two products.
1) An advanced decision-making framework that provides the optimized route
for vehicle drivers under impending tornadoes to improve road safety. This system can
guide vehicle drivers at what speed they should drive, which lane they should drive,
whether the vehicles should leave the road, where the vehicles should get off the highway,
and where the vehicles should go for sheltering.
2) A mobile application (DEW App) to facilitate this risk communication for
vehicle drivers. By sending the timely collected information to the server, this decisionmaking
system not only provides protective action guidance to vehicles that are very close
to tornadoes, but also provides guidance to vehicles that are far away from tornadoes to
avoid traffic jam after tornado events, as tornadoes may cause tree damage and/or car
accidents, which may block the road."
Impacts/Benefits "The developed decision-making framework can provide an optimized route for vehicle
drivers during severe weather and the developed mobile app will facilitate in real-time
sending the optimized route to vehicle drivers (risk communication). This product will add
a layer of protection to those traveling, to ensure that they reach their destination safely.
The proposed ideas can be applied to improve the public safety under other extreme
weather conditions and in other locations through slight modification. The research
outcome will equip the Integrated Warning Team of Missouri with holistic thinking to
enhance public safety on the road under extreme weather.
In the future, the PI will collaborate with Google or Apple to embed the developed
framework in their Map Apps to make their functions more powerful. This will benefit a
diverse community, contributing to social equity. An adaptive communication strategy will
be developed to communicate the guidance to self-driving vehicles. In the adaptive
community strategy, the ideal communication technology (e.g., LTE, IEEE 802.11ad
WLAN at 60-GHz) will be selected adaptively depending on the situation (e.g., predicted
availability, camera, lidar, radar, and GPS signal quality)."