Executive Summary
The Federal Highway Administration (FHWA) Road Weather Management Program (RWMP) weather-responsive traffic management (WRTM) initiative focuses on developing actionable strategies for system management and operations in challenging road weather conditions. Although the potential impacts of using WRTM strategies can be valuable, the strategies can be challenging to implement effectively. They require sufficient information on traffic and weather conditions; development of appropriate strategies, infrastructure, and information systems to support implementation of those strategies; agency operators supportive and knowledgeable of the strategies; and drivers who are aware and responsive. Over the years, the RWMP has addressed these challenges in a variety of programs directed at condition data gathering from fixed and connected vehicle (CV) sensors, strategy development, decision support system development, and support for agency implementations. Analysis, modeling, and simulation (AMS) tools have been used by FHWA and agencies to assess the effectiveness of these data sets, strategies, and methods in improving the operational response.
The objectives of this study are to: (1) evaluate existing AMS tools, (2) survey and partner with agencies that use or plan to use CV data for WRTM and want to be able to evaluate their existing and enhanced practices, (3) apply the AMS tools with those agencies to CV-enabled weather-responsive management strategies (WRMS) for traffic management and winter maintenance, and (4) summarize the results and provide recommendations on these uses of the AMS tools.
Several AMS tools can be used to study the traffic impacts of CV systems and data. Those tools include general-purpose commercially available AMS platforms, in addition to customized research models, developed to answer specific questions related to CV systems. Several studies have assessed the impacts of weather on traffic, depending on the severity of rain, snow, or other conditions, and researchers have already incorporated such weather impacts in analyses using traffic simulation modeling tools. Application of either mesoscopic or microscopic AMS tools requires additional adaptation of those tools. At the meso level, DYNASMART has had the most cumulative experience in road weather applications. Micro-level tools offer flexibility to implement such capabilities through application programming interfaces (API) and other mechanisms. These CV capabilities have been demonstrated with some tools, such as Aimsun® and Vissim®, two widely used platforms.
Site recommendations for assessing the benefits of applying AMS tools to WRMS using CV data depend on the availability of CV data, WRMS in use, and calibrated AMS tools for those sites. Agencies and sites must currently be implementing WRMS, collecting CV or mobile data, and using or interested in using an AMS tool for evaluating their applications. AMS for WRMS analysis must be applicable to those particular strategies and fully implementable on the agency’s transportation network. Given these considerations, sites selected in this project for the application of AMS tools using CV data to simulate WRMS are along the Interstate 80 (I–80) corridor in Wyoming, and on a portion of the road network in the City of Chicago.
The Wyoming case study evaluates three CV-enabled WRMS, including traveler information messages (TIM), CV-based variable speed limits (VSLs), and snowplow pre-positioning along the 402-mile I–80 corridor through the southern part of the State. To improve driver safety along the corridor, the Wyoming connected vehicle pilot (CVP) uses dedicated short-range communication-based (DSRC) applications that leverage vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) connectivity to support a range of services, such as advisories, roadside alerts, and dynamic travel guidance for freight and passenger travel. The three WRMS are evaluated using a framework consisting of a Vissim network module, a simulation manager module, and an API module that determines driver behavior under the CV application scenarios. The simulations demonstrate that CV-based WRMS applications can improve traffic safety performance, as measured by inverse time-to-collision (iTTC). The effectiveness is most dramatic under severe weather conditions. TIM can help improve the safety performance of the traffic system by reducing the risk of collisions and the occurrence of pileup crashes near the lane-closure event zones. VSL can provide suitable speed limit advisories under different weather scenarios to keep vehicles driving at safe speeds. Snowplow pre-positioning is an effective strategy for winter surface maintenance that helps to improve operation efficiency, reduce collision risks, and increase the mobility efficiency of the traffic system.
The Chicago case study assesses the potential of using CV data for optimizing snowplow operations to reduce impacts on traffic flow. The Chicago testbed network spans the Chicago Loop, O’Hare International Airport, and Evanston, Illinois, and includes the Kennedy Expressway on Interstate 90 (I–90), Edens Expressway on Interstate 94 (I–94), Eisenhower Expressway on Interstate 290 (I–290), and Lake Shore Drive along Lake Michigan. The snowplow routing optimization application was assessed using the DYNASMART AMS capabilities, with additional modules developed to estimate and predict conditions and capacities of road sections affected by snow accumulation. The network traffic states are estimated and predicted by processing data from simulated CVs operating throughout the network. The Snowplow Command module then uses the information to generate snowplow routes to minimize the weather impact on traffic. Performance of weather-related strategies was quantitatively evaluated with measurements of traffic speed and flow on the network. The performance measures were compared to the results under the two scenarios of (1) doing nothing, and (2) executing a predetermined plan extracted from global positioning system (GPS) data for simulated snowplow routes. Results support the potential benefit of two different types of CV technology in WRMS practice. First, the traffic estimation results verify that data from passenger vehicles with connectivity can be a source of timely disaggregated information on traffic conditions, even with low market penetration rates. Second, local agencies can monitor the current WRMS performance by tracking CVs acting as agents or probes, estimate road surface condition with the executed service plan, and generate real-time service plans for remaining road sections by using incoming information to maximize the WRMS performance.
