Weaving is defined as the crossing of two or more traffic streams traveling in the same direction along a significant length of the highway without the aid of traffic control devices. The traditional methods used for the design and operational analysis of a highway is the Highway Capacity Manual (HCM). These traditional methods in the manual use road geometry and traffic volumes as input and provide an estimate of the speed as an output. TRANSIMS is a new computer simulation package in transportation that can be used as an analysis as well as a planning tool. The Microsimulator in TRANSIMS deals with the actual simulation of traffic on roadways. The intent of this research is to evaluate TRANSIMS Microsimulator and compare it with the traditional Highway Capacity Manual in modeling the weaving sections on a freeway and make recommendations. This research will also compare the modeling strategy and provide analysis of the output. / Master of Science

TRANSIMS (Transportation Analysis and Simulation System) developed at the Los Alamos National Laboratory, is an integrated system of travel forecasting models designed to give transportation planners accurate and complete information on traffic impacts, congestion, and pollution. TRANSIMS is a micro-simulation model which uses census data to generate a synthetic population and assigns activities using activity survey data to each person of every household of the synthetic population. The synthetic households generated from the census data are matched with the survey households based on their demographic characteristics. The activities of the survey household individuals are then assigned to the individuals of the matched synthetic households. The CART algorithm is used to match the households. With the use of CART algorithm a classification tree is built for the activity survey households based on some dependent and independent variables from the demographic data. The TRANSIMS model assumes activity times as dependent variables for building the classification tree. The topic of this research is to compare the TRANSIMS approach of using times spent in executing the activities as dependent variables, compared to match the alternative of using travel times for trips between activities as dependent variables i.e. to use the travel time pattern instead of activity time pattern to match the persons in the survey households with the synthetic households. Thus assuming that if the travel time patterns are the same then we can match the survey households to the synthetic population i.e. people with similar demographic characteristics tend to have similar travel time patterns. The algorithm of the Activity Generator module along with the original set of dependent variables, were first used to generate a base case scenario. Further tests were carried out using an alternative set of dependent variables in the algorithm. A sensitivity analysis was also carried out to test the affect of different sets of dependent variables in generating activities using the algorithm of the Activity Generator. The thesis also includes a detailed documentation of the results from all the tests. / Master of Science

TRANSIMS is a disaggregate, behavioral transportation planning package developed under US DOT's and EPA funding at the Los Alamos National Laboratory (LANL). It is an integrated system of travel forecasting models designed to give transportation planners accurate, complete information on traffic impacts, congestion, and pollution by simulating second-by-second movements of every person and every vehicle through the transportation network of a large metropolitan area. There is no built-in module for travellers' mode choices In TRANSIMS. The modes going with the shortest path are always taken. In Portland Study, a mode choice methodology implemented by a series of feedback processes is proposed. However, it uses aggregate, deterministic mode choice model. There is little solid theoretic ground for the format and coefficients of the generalized costs used in the calibration process. The accessibility to a mode, especially to Transit, was also not included in the model. In the thesis, a disaggregate and deterministic mode choice methodology in TRANSIMS is developed. The accessibility to each mode is analyzed and included in the model. The methodology is then implemented on the Blacksburg transportation planning study, namely Blacksburg_Lite. The analysis of the result is based on the indicator of mode choice, mode split between Transit and Auto. The indicator is close to that in survey data and converged fast. Therefore, this mode choice methodology could be used within TRANSIMS framework. / Master of Science

Traffic simulation is a powerful tool that provides transportation engineers with the ability to test the feasibility and performance of a system before it is implemented and also helps in optimizing the proposed system. Over the past twenty years significant amount of work has been conducted on improving the quality and accuracy of transportation simulation models. Much of this work has been concentrated on microscopic simulation models because they provide traffic engineers greater opportunity to examine the inherently complex, stochastic, and dynamic nature of transportation systems when compared to traditional macroscopic models. In order to test the performance of some of the simulation models, a study is conducted on freeway weaving sections, which are considered to be one of the most complex regions to be modeled and analyzed. The intent of the research is to evaluate TRANSIMS, CORSIM, VISSIM and INTEGRATION and compare them with Highway Capacity Manual, which adopts a traditional methodology for carrying out the operational analysis of a highway system. The statistics collected for the simulation runs include weaving speeds, non-weaving speeds and density of the weaving section. / Master of Science

Urban travel demand forecasting and traffic assignment models are important tools in developing transportation plans for a metropolitan area. These tools provide forecasts of urban travel patterns under various transportation supply conditions. The predicted travel patterns then provide useful information in planning the transportation system. Traffic assignment is the assignment of origin-destination flows to transportation routes, based on factors that affect route choice. The urban travel demand models, developed in the mid 1950s, provided accurate and precise answers to the planning and policy issues being addressed at that time, which mainly revolved around expansion of the highway system to meet the rapidly growing travel demand. However, the urban transportation planning and analysis have undergone changes over the years, while the structure of the travel demand models has remained largely unchanged except for the introduction of disaggregate choice models beginning in the mid-1970s. Legislative and analytical requirements that exceed the capabilities of these models and methodologies have driven new technical approaches such as TRANSIMS. The Transportation Analysis and Simulation System, or TRANSIMS, is an integrated system of travel forecasting models designed to give transportation planners accurate, and complete information on traffic impacts, congestion, and pollution. It was developed by the Los Alamos National Laboratory to address new transportation and air quality forecasting procedures required by the Clean Air Act, the Intermodal Surface Transportation Efficiency Act, and other regulations. TRANSIMS includes six different modules: Population Synthesizer, Activity Generator, Route Planner, Microsimulator, Emissions Estimator, and Feedback. This package has been under development since 1994 and needs significant improvements within some of its modules. This dissertation enhances the interaction between the Route Planner and the Microsimulator modules to improve the dynamic traffic assignment process in TRANSIMS, and the Emissions Estimator module. The traditional trip assignment is static in nature. Static assignment models assume that traffic is in a steady-state, link volumes are time invariant, the time to traverse a link depends only on the number of vehicles on that link, and that the vehicle queues are stacked vertically and do not traverse to the upstream links in the network. Thus, a matrix of steady-state origin-destination (O-D) trip rates is assigned simultaneously to shortest paths from each origin to a destination. To address the static traffic assignment problems, dynamic traffic assignment models are proposed. In dynamic traffic assignment models, the demand is allowed to be time varying so that the number of vehicles passing through a link and the corresponding link travel times become time-dependent. In contrast with the static case, the dynamic traffic assignment problem is still relatively unexplored and a precise formulation is not clearly established. Most models in the literature do not present a solution algorithm and among the presented methods, most of them are not suitable for large-scale networks. Among the suggested solution methodologies that claim to be applicable to large-scale networks, very few methods have been actually tested on such large-scale networks. Furthermore, most of these models have stability and convergence problem. A solution methodology for computing dynamic user equilibria in large-scale transportation networks is presented in this dissertation. This method, which stems from the convex simplex method, routes one traveler at a time on the network and updates the link volumes and link travel times after each routing. Therefore, this method is dynamic in two aspects: it is time-dependent, and it routes travelers based on the most updated link travel times. To guarantee finite termination, an additional stopping criterion is adopted. The proposed model is implemented within TRANSIMS, the Transportation Analysis and Simulation System, and is applied to a large-scale network. The current user equilibrium computation in TRANSIMS involves simply an iterative process between the Route Planner and the MicroSimulator modules. In the first run, the Route Planner uses free-flow speeds on each link to estimate the travel time to find the shortest paths, which is not accurate because there exist other vehicles on the link and so, the speed is not simply equal to the free-flow speed. Therefore, some paths might not be the shortest paths due to congestion. The Microsimulator produces the new travel times based on accurate vehicle speeds. These travel times are fed back to the Route Planner, and the new routes are determined as the shortest paths for selected travelers. This procedure does not necessarily lead to a user equilibrium solution. The existing problems in this procedure are addressed in our proposed algorithm as follows. TRANSIMS routes one person at a time but does not update link travel times. Therefore, each traveler is routed regardless of other travelers on the network. The current stopping criterion is based only on visualization and the procedure might oscillate. Also, the current traffic assignment spends a huge amount of time by iterating frequently between the Route Planner and the Microsimulator. For example in the Portland study, 21 iterations between the Route Planner and the Microsimulator were performed that took 33:29 hours using three 500-MHZ CPUs (parallel processing). These difficulties are addressed by distributing travelers on the network in a better manner from the beginning in the Route Planner to avoid the frequent iterations between the Route Planner and the Microsimulator that are required to redistribute them. By updating the link travel times using a link performance function, a near-equilibrium is obtained only in one iteration. Travelers are distributed in the network with regard to other travelers in the first iteration; therefore, there is no need to redistribute them using the time-consuming iterative process. To avoid problems caused by link performance function usage, an iterative procedure between the current Route Planner and the Microsimulator is performed and a user equilibrium is found after a few iterations. Using an appropriate descent-based stopping criterion, the finite termination of the procedure is guaranteed. An illustration using real-data pertaining to the transportation network of Portland, Oregon, is presented along with comparative analyses. TRANSIMS framework contains a vehicle emissions module that estimates tailpipe emissions for light and heavy duty vehicles and evaporative emissions for light duty vehicles. It uses as inputs the emissions arrays obtained the Comprehensive Modal Emissions Model (CMEM). This dissertation describes and validates the framework of TRANSIMS for modeling vehicle emissions. Specifically, it identifies an error in the model calculations and enhances the emission modeling formulation. Furthermore, the dissertation compares the TRANSIMS emission estimates to on-road emission-measurements and other state-of-the-art emission models including the VT-Micro and CMEM models. / Ph. D.

TRANSIMS (Transportation Analysis Simulation System) is part of a multi-track Travel Model Improvement Program sponsored by the U. S. Department of Transportation (DOT), and the Environmental Protection Agency (EPA). The main objective of this thesis is to enhance and implement a principal module in TRANSIMS, called the Route Planner Module. The purpose of the Route Planner Module is to find time-dependent label-constrained shortest paths for transportation activities performed by travelers in the system. There are several variations of shortest path problems and algorithms that vary by application, contexts, complexity, required data, and computer implementation techniques. In general, these variants require some combination of the following inputs: a network consisting of nodes and links, and a travel time function on each link, which could be a time-independent or a time-dependent function, where the time-dependent functions account for time-of-day delays resulting from actual travel conditions such as peak-hour congestion. The problem then seeks a shortest path between one or more origin-destination pairs. A new variant, introduced in the context of TRANSIMS and which is the focus of the present study, also specifies labels for each arc denoting particular modes of travel, along with strings of admissible labels that delineate the permissible travel mode sequences that could be adopted by the user in traveling from the origin to the destination of the trip. The technique adopted by TRANSIMS to identify a suitable travel route for any user is a variant of Dijkstra's procedure for finding shortest paths, which is suitably modified to accommodate time-dependent travel times and label sequence constraints. The underlying problem is referred to as a Time-Dependent Label-Constrained Shortest Path Problem. The main objective of this research is to improve upon this procedure and study its implementation in order to develop a more effective scheme for determining time-dependent label-constrained shortest paths as a practical routing tool in multimodal transportation networks. Specifically, we enhance the following features of this procedure: (a) We recommend a method to work implicitly with a certain composition graph G* that combines the transportation network with the admissible label-sequence graph. This graph G* captures all possible paths for a given single trip starting from the origin node and ending at the destination node, while conforming with the admissible mode string. (b) We use more modern partitioned shortest path algorithmic schemes to implement the time-dependent label-constrained procedure. (c) We introduce the notion of curtailing search based on various indicators of progress and projected travel times to complete the trip. Finally, computer programs in C++ are written to implement the proposed overall algorithm, and are applied to solve some real multimodal transportation network problems. The indicators used to evaluate the performance of the algorithm include (i) time taken for computation on the real network, (ii) quality of solution obtained, (iii) ease of implementation, and (iv) extensibility of the algorithm for solving other variants of the shortest path problem. The results exhibit that the proposed algorithm, even without the approximate curtailing of the search process, exhibits good performance in finding optimal routes for real multimodal transportation networks. Although the various heuristic curtailments result in only approximate solutions, typically, they run much faster than the exact algorithm for the intuitive reason that the shortest path tree developed grows more pointedly in the direction of the destination. Among the different strategies implemented, our results suggest that the scheme based on the geometric structure of the underlying network, using either a constant predictive term, or multiplying this term with a suitable exponential decay function, yields an attractive candidate for heuristically curtailing the search. / Master of Science

TRANSIMS is a disaggregate, behavioral, regional transportation planning package developed by Los Alamos National Laboratory (LANL) under funding from US DOT, EPA, and Department of Energy. It is an integrated system of travel forecasting models designed to give transportation planners accurate, complete information on traffic impacts, congestion, and pollution by simulating on a second-by-second basis the movements of every person and every vehicle through the transportation network of a large metropolitan area. This regional microsimulation approach provides a better assessment of the performance of a large network than the current link performance functions utilized in the current planning procedures. On the other hand, their microsimulation approach on a regional scale requires a lot of data that may not be readily available, and utilize a low fidelity microsimulation in order to make it operational. Some agencies may be interested in performing a more detailed investigation of traffic patterns within a sub area, such as the downtown area. The author implemented a subarea focusing methodology within TRANSIMS and also developed an interface that allows the investigator to use a high-fidelity, small-size network efficient traffic operational software package — CORSIM to perform sub area traffic operational analysis with demand and network extracted from applications of TRANSIMS. This methodology will allow TRANSIMS to take advantage of higher fidelity models for sub-network analysis and allow CORSIM to use planning inputs such as individual 24 hour travel activities and trip chains. An evacuation model is also built and applied to Virginia Tech main campus, Blacksburg, VA to evaluate this sub area focusing methodology. / Master of Science

The thesis develops and documents a workflow for applying TRANSIMS to the analysis of Developments of Regional Impact (DRI). The proposed workflow will consider perspectives of both the transportation agency responsible for the evaluating the DRI and the transportation engineer responsible for performing the analysis. TRANSIMS offers a comprehensive framework for managing inputs and outputs that follow a transportation planning workflow. Not a single, monolithic software application, TRANSIMS is a suite of 65 small, light-weight, single-task tools for creating and manipulating GIS shape files and SQL data base files, estimating the elements of a four-step transportation modeling process, and computing link and vehicle delays for a given transportation network. Current analysis techniques for developments of regional impact require that the analyst apply arbitrary or non-repeatible estimates for trip assignments at the regional level. Because of the modular nature of the TRANSIMS, implementing each DRI as a layer in the GIS data base will permit the mixing and matching of multiple DRI within a local area, permitting a risk-based approach to the evaluation of multiple DRI, any of which may or may not actually happen. This thesis focuses exclusively on the review of DRI analysis techniques, review of TRANSIMS modules, and development of a proposed DRI workflow within the TRANSIMS framework.

abstract: In the middle of the 20th century in the United States, transportation and infrastructure development became a priority on the national agenda, instigating the development of mathematical models that would predict transportation network performance. Approximately 40 years later, transportation planning models again became a national priority, this time instigating the development of highly disaggregate activity-based traffic models called microsimulations. These models predict the travel on a network at the level of the individual decision-maker, but do so with a large computational complexity and processing time requirement. The vast resources and steep learning curve required to integrate microsimulation models into the general transportation plan have deterred planning agencies from incorporating these tools. By researching the stochastic variability in the results of a microsimulation model with varying random number seeds, this paper evaluates the number of simulation trials necessary, and therefore the computational effort, for a planning agency to reach stable model outcomes. The microsimulation tool used to complete this research is the Transportation Analysis and Simulation System (TRANSIMS). The requirements for initiating a TRANSIMS simulation are described in the paper. Two analysis corridors are chosen in the Metropolitan Phoenix Area, and the roadway performance characteristics volume, vehicle-miles of travel, and vehicle-hours of travel are examined in each corridor under both congested and uncongested conditions. Both congested and uncongested simulations are completed in twenty trials, each with a unique random number seed. Performance measures are averaged for each trial, providing a distribution of average performance measures with which to test the stability of the system. The results of this research show that the variability in outcomes increases with increasing congestion. Although twenty trials are sufficient to achieve stable solutions for the uncongested state, convergence in the congested state is not achieved. These results indicate that a highly congested urban environment requires more than twenty simulation runs for each tested scenario before reaching a solution that can be assumed to be stable. The computational effort needed for this type of analysis is something that transportation planning agencies should take into consideration before beginning a traffic microsimulation program. / Dissertation/Thesis / M.S. Civil Engineering 2010

Traffic Congestion is a critical problem in large urban areas. In this thesis, six different control strategies aiming to alleviate congestion are performed through TRANSIMS simulation in the city of Alexandria. Main objective of this thesis is to study and explore the impacts of these control strategy in terms of system performance. Macroscopic Fundamental Diagrams has been used during research to present traffic movement and evaluate traffic performance. This thesis also look at the outcome of each strategy at different household income group in the city. The attention are drawn to the importance of taking socio-economic impact in traffic management decisions. Some of the control strategies presented in this thesis have different impacts on different income groups in the city, while other control strategies have similar impacts (negative, or inconclusive) on different groups in Alexandria city. The thesis gives the conclusions on the impact of selecting different signal control strategies. / Master of Science