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intersections in the Twin Lakes Area and identified potential mitigation measures. Cut -Through Traffic Cut -through traffic, while affecting most parts of the city, is particularly problematic for the areas adjacent to TH 36 and I -35W. The entire city lacks good east -west roadway connectivity, which accentuates the impact of cut -through traffic on the limited east -west routes that exist in the community. Aside from TH 36, the only other roadways that fully traverse the city are County Roads B, B2 , and C and Larpenteur Avenue. As TH 36 has become more congested, local residents have become concerned over the increase in traffic on these and other east -west roadways such as Roselawn Avenue located south of TH 36. It is hoped that the planned addition of travel lanes on TH 36 will help alleviate some of this traffic Other measures that could assist in alleviating traffic include the addition of more park-and-ride lots, particularly east of Roseville. With the addition of these lots, as well as increased transit in general, more commuters will use transit as part of their trip, which will reduce peak hour travel through the city. Future Transportation System Future Roadway Needs Traffic forecasts are estimated using a computerized travel demand model. The Metropolitan Council Travel Model was used to estimate future travel conditions on Roseville roadways by dividing the metropolitan area into 1,201 Transportation Analysis Zones (TAZs) and estimating the socioeconomic and demographic characteristics of the residents of each TAZ. The Metropolitan Council Travel Model was calibrated to year 2000 average daily trips (ADT) volumes and subsequently used to predict 2030 travel conditions.The travel demand forecasting model estimates the amount of travel that can be expected in a future scenario. Modeling provides the analyst with the ability to test multiple scenarios and estimate the future impacts of transportation and land -use policies and network modifications. Four -Step Modeling Process Traditional transportation demand modeling involves four steps: trip generation, trip distribution, mode choice, and traffic assignment. The four -step modeling process is described in the following sections: Trip Generation. The first step in forecasting travel is trip generation. In this step, information about land -use, population, and economic forecasts are used to estimate how many person -trips will be made to and from each TAZ. Trip generation is estimated by applying complex equations involving land -use, economic, and demographic data for each TAZ. For example, the model estimates the number of trips expected to begin within a TAZ using data such as the average household size and the number of vehicles available. Similarly, the number of trips estimated to end in each TAZ is estimated using expected employment levels. Trip Distribution.The second step, trip distribution, links the trips generated in each TAZ during step one with an appropriate destination TAZ. These linked trip ends form an origin -destination trip matrix summarizing how many trips begin in each TAZ, and where the trips end. Trip distribution is based on the idea that the number of trips between two points is dependent upon their attractiveness for a given trip purpose and the separation (in terms of distance or travel time) between the points. The number of trips between a given origin -destination zone pair decreases with increasing travel time be- tween the origin zone and the destination zone. Mode Choice. The third step, mode choice, is the step where trips between a given origin and desti- nation are separated into different modes of travel including public transit and personal vehicles. The attractiveness of travel by different modes based on various characteristics are estimated to determine their relative usage. Traffic Assignment. The fourth step, traffic assignment, uses an iterative process to assign trips to specific roadways. The particular routes used to travel from each origin to each destination are first determined based on the shortest travel times. Because travel time varies greatly depending on congestion levels, the assigned trip volumes are then compared to the capacity of each link to see which links, if any, are congested. If a roadway is congested, the travel speed will decrease, resulting in increased travel time on that roadway. During the next iteration, trips in the model shift to less congested links as drivers seek to minimize travel time. This process continues until there is a balance between travel demand and travel supply on the network and each driver is utilizing the quickest path between their origin and destination. 2030 Land Use Future year land use requires the allocation ofpopulation and employment data to individual TAZs. Discussions with the City regarding future land -use plans and development proposals were used to assign future 2030 Comprehensive Plan Adopted: October 26, 2009 Transportation I 5-29