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Traffic Analysis Toolbox Volume XII: Work Zone Traffic Analysis – Applications and Decision Framework Chapter 4. Key Considerations for Modeling Approach 4.1 Introduction After a suitable analysis tool is selected, the next step is to use the tool to determine the impacts of a work zone. This chapter describes the key considerations when applying the modeling tools for work zone traffic analysis. Before proceeding to discuss each category of the modeling tools, it is important to have an understanding of the following key items, as they play a significant role in work zone analysis when using any of the modeling tools. Study Network;. Work Zone Capacity;.
Capacity versus Discharge Rate;. Variability of Capacity and Time-of-Day Models;.
Analysis Period;. Change in Traffic Pattern;. Common Data Collection;.
Model Development Application Process;. Error Checking; and. Level of Effort. Study Network In preparation for the data collection required for work zone analysis, it is necessary to determine the limits of the network to be studied. The study network should consider both the work zone boundaries and the surrounding area where the traffic is affected by the work zone. For longer duration work zones, it is recommended that interim analysis be performed to better reflect varying capacities, if resources and data are available.
In addition, different analysis tools may accommodate various time periods; some can analyze longer time periods, while others cannot. For instance, some sketch-planning analysis tools can analyze longer time periods, such as multiple days, months, or even years, which is typically beyond the capability of other analysis tools such as macro-, meso-, and microscopic simulation models. The analysis period should be long enough to include no queue at the beginning, queue buildup, and queue dissipation at the end of the analysis period.
Changes in Traffic Pattern Drivers obtain roadway information through various means to select their preferred route(s). These means include dynamic message signs (DMS), highway advisory radio (HAR), public information and outreach, incident management systems or other traveler information systems, etc.
Some tools, such as DynusT, have the ability to directly model roadway information system, such as DMS. In DynusT, DMS can be set to provide multiple types of messages, such as speed advisory, mandatory detour, and congestion warning. DynusT permits users to specify a percentage of vehicles that respond to the DMS and make detour decisions. According to Horowitz et al., many drivers are responsive to warnings that they might encounter excessive delays along their current route. (Horowitz, A.J., I. Weisser, and T. Accessed January 11, 2012.) However, a much larger percentage of drivers would not divert, even though it is to their advantage to do so.
This study suggested that a 10 percent alternative route selection rate during peak periods is achievable when accurate, up-to-the-minute information about delay through a work zone is provided and there is an attractive set of alternative routes. This study was conducted on a rural freeway. For drivers using lower classification or urban highways with attractive alternative routes, the diversion rate could be higher. The FHWA conducted a study that examined the use of ITS for work zone traffic management with a purpose to highlight “before and after” or “with and without” analyses that quantify the mobility and safety benefits.
(Luttrell, T., M. Benekohal, J. Comparative Analysis Report: The Benefits of Using Intelligent Transportation Systems in Work Zones. Publication FHWA- HOP-09-002, Federal Highway Administration, U.S. Department of Transportation, Washington, D.C., October 2008.) According to this study, significant traffic diversion was observed in response to appropriate messages displayed during congested conditions.
In Texas, an average of 10 percent diversion (range of 1 to 28 percent) was observed, while in the District of Columbia (D.C.) an average of 52 percent (range of 3 to 90 percent) lower mainline volume (combination of diversion, demand reduction, and congestion) was observed. The study noted that in Texas, during major incidents or high construction impact periods combined with high demand, the system diverted an average of 10 percent of mainline traffic to alternate routes and traffic diversion was as high as 28 percent. When congestion occurs on the mainline due to a work zone, motorists may choose alternate routes to bypass the congested segment. Subsequently, travel time on the alternate routes will increase, and the route choice between the mainline and an alternate route may vary over time. Dynamic traffic assignment (DTA)-based tools can take this into account. In the case of long-term work zones, generally traffic reaches equilibrium after a few weeks, especially in urban areas with commuter traffic. Travelers typically choose the available route having the least travel time between their origin and destination (O-D).
Due to congestion effects, the travel time of a route between an origin and destination also depends on the choices made by other travelers, who are themselves also trying to choose the least travel time route between their own origin and destination. When every traveler succeeds in finding such a route, every used route has the minimum time or cost between its origin and destination. This condition is known as equilibrium.
The collection of local data is encouraged in order to create a more robust analysis network that captures the effects of changes in traffic pattern. Besides finding alternate routes, some motorists may change their trip departure times or even cancel their trips, especially in the case of long-term work zones with heavy congestion. Common Data Collection Once the size of the study network has been determined, it is necessary to collect data that will be needed to model work zone operations.
The data collection effort may be considerably reduced by obtaining information using aerial imagery, or by downloading the traffic signal plans from agency web sites, and/or by obtaining the roadway design plans (if available). If needed, these data should be confirmed with a field visit. It should be noted that the required data accuracy may vary during different project stages ( e.g., project planning, preliminary engineering, and final design).
It is not appropriate to use planning-level data to make engineering design decisions. Included in Table 29 are the common data that should be collected for all work zone traffic analysis, no matter which method or tool is selected. Additional data for specific modeling tools will be discussed in each tool category.
Depending on the complexity of the study network and of the analysis needed, different types of data may be required and may broadly be classified into four categories: general, geometric, traffic, and construction.
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