Cross-cutting Issues

This paper brings technical light and an innovative approach to a specific application that can utilize the existing infrastructure of RWIS data and Adaptive Traffic Signal Control (ATSC) to create more efficient signal phasing and safer intersection conditions during inclement weather.  It defines in general adaptive signal control applications and current atmospheric and pavement condition data assets. The paper then presents ideas on how to combine those two to create system applications that adapt to current traffic conditions and the associated changes in driver behavior, with the goal of creating safer, more efficient weather based adaptive signal phasing systems.  For example, if a sensor senses that the friction coefficient of the pavement at an intersection is significantly reduced so that the stopping distance of  a vehicle is increased by 50%,  the signal controller can take that data and modify the signal timing to increase yellow lights or increase the delay between red and green light phasing.  This will allow vehicles more time to clear the intersection, reducing collisions caused by vehicles unable to stop in their normal time because of reduced friction.  This is just one example of the many applications that could be developed by integrating these two existing ITS systems.

The paper concludes that by utilizing existing ITS infrastructure to develop new advanced applications without significant increase in costs, we can increase the return on investment and effectiveness of Intelligent Transportation Systems. It also demonstrates that by developing systems that have multiple applications we can increase the resolution of data derived from these systems, thus increasing the overall effectiveness of Intelligent Transportation Systems throughout the world.

 Author: Antony C. Coventry

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

During the 2008-2009 winter season, the Indiana Department of Transportation (INDOT)
conducted a state-wide deployment of a Maintenance Decision Support System (MDSS) into
their winter operations strategy. Similar to other agencies, INDOT was looking for the
opportunity to bring a research project into operations and provide tangible cost savings for their winter maintenance budgets. MDSS was poised to fill this need; so, with the support from upper management, the state embarked on a full deployment of the MDSS technology as a cost saving package and a cornerstone of their winter maintenance philosophy.

Large amounts of road and weather data are collected for the MDSS to perform optimally and
the resulting answers from MDSS could be used in an agency’s TMC as well. The information in
MDSS would provide known areas where weather is impacting the roads, current status of an
agency’s snow fighting vehicles, and forecasted locations of where hazardous road conditions
may be encountered by the traveling public. This information could and should be used to inform the travelling public of: locations of snow fighting equipment (including a specific lane and direction), locations where weather (especially winter weather) may be impacting traffic, and actual road conditions (icy, wet, dry, etc.).

This paper will address the lessons learned during the Indiana MDSS Implementation, and how
those lessons can be applied to other system implementations within an agency. The paper also addresses the possible uses of data within MDSS for the ITS arena, including suggestions on how to integrate the information available from MDSS into TMC operations.

Authors: Anthony McClellan, Benjamin Hershey

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

This paper illustrates the potential of using cellular phone positioning techniques in tracking

cross-region traffic and deriving dynamic transit demand data. A traffic corridor between Topeka,

Lawrence, and Kansas City, Kansas was used to test and demonstrate the application and

operational process of the proposed cellular phone tracking algorithms. The experimental test

found that the cellular phone data provided by the vendor can capture about 14 percent of the

average traffic data in the study area. About 49 percent of the total traffic was identified as

commuting traffic, which had a round trip between two regions (cities). Assuming the

commuters among these regions are the potential transit users, the expected values of dynamic

transit demand data by various time intervals were derived based on the commuting traffic O-D

data, the possible staying and commuting times. These data can be used for transit schedule

assignment and to assess traffic impacts along the traffic corridor by the time-of-day.

KU Transportation Research Institute

Department of Civil, Environmental, and Architectural Engineering, The University of Kansas

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

One solution for mitigating the adverse impacts of weather on the transportation system is to provide improved road and atmospheric hazard products to road maintenance operators and the travelling public. With funding and support from the U.S. Department of Transportation’s (USDOT) Research and Innovative Technology Administration (RITA) Connected Vehicles initiative and direction from the Federal Highway Administration’s (FHWA) Road Weather Management Program, the National Center for Atmospheric Research (NCAR) is conducting research to develop a Vehicle Data Translator (VDT) that incorporates vehicle-based measurements of the road and surrounding atmosphere with other, more traditional weather data sources, and creates road and atmospheric hazard products for a variety of users.

 Authors: Sheldon D. Drobot, Michael Chapman, Paul A. Pisano, Gabriel Guevara

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida

Winter road maintenance is one of the biggest challenges for agencies responsible with providing safe environments for the public, and it has been a major growth area for ITS systems in the past few years. At the same time, budget issues have forced agencies to do ‘more with less’ and the use of smarter, more intelligent systems such as mobile data collectors have contributed to address these issues. Manufacturers of these systems are staying on the cutting edge of technology and adapting their systems to the needs and requirements of states and other winter road maintenance agencies, both in terms of increased capabilities and reduced costs.

The Maintenance Decision Support System (MDSS), adopted by the majority of states with
severe winter weather, has introduced a more scientific approach to the management and
direction of snow plows, by utilizing expert weather service providers to give route specific
weather reports and more precise application rate recommendations tailored to the specific
weather conditions being experienced.

Author: Michael Howarth

Presented at the 18th World Congress on ITS, October 2011, Orlando, Florida