|Transportation Systems Engineering Courses:||[ back to top ]|
CEE 220A Travel Demand Analysis I: Classical Approaches (3). Fundamentals of transportation systems analysis. Theoretical aspects of travel demand. Travel behavior. Modeling of performance characteristics and costs of transportation modes. In-depth presentation of travel demand modeling techniques. Development of travel choice models for mode, route, and destination choice. Equilibration. Prerequisite: knowledge of probability and statistics.
CEE 220B Travel Demand Analysis II: Discrete Choice Analysis (3). Methods of discrete choice analysis and their applications in the modeling of transportation systems. Emphasis on the development of a sound understanding of the theoretical aspects of discrete choice modeling that are useful in many applications in travel demand analysis. Prerequisite: CEE 220A.
CEE 220C Travel Demand Analysis III: Activity-Based Approaches (3). The methodological underpinnings of activity-based travel demand modeling. Presents methodologies within the context of a generalization of discrete choice modeling approaches, emphasizing the distinctions that separate these two approaches and presenting appropriate mathematical and statistical tools to address these distinctions.
CEE 221A Transportation Systems Analysis I (3). Introduction to mathematical methods and models to address logistics and urban transportation problems. Techniques include stochastic models, queuing theory, linear programming, and introductory non-linear optimization. Prerequisite: basic knowledge of probability theory.
CEE 221B Transportation Systems Analysis II (3). Advanced mathematical methods and models to address logistics and urban transportation problems. Topics include network flows, advanced optimization techniques, dynamic models, geometric models, and simulation. Prerequisites: CEE 221A; graduate standing or consent of instructor.
CEE 222 Transit Systems Planning (3). Planning methods for public transportation in urban areas. Technological and operational characteristics of vehicles, facilities, and systems. Short-range planning techniques: data collection and analysis, demand analysis, mode choice, operational strategies, financial analysis. Design of systems to improve performance.
CEE 223 Artificial Intelligence Techniques in Transportation (3). Concepts, characteristics and applications of selected artificial intelligence techniques in transportation engineering, including artificial neural networks, knowledged-based expert systems, and genetic algorithms. Prerequisite: graduate standing or consent of instructor.
CEE 224A Transportation Data Analysis I (3). Statistical analysis of transportation data sources. Analysis of categorical and ordinal data. Regression and advanced multivariate analysis methods such as discriminant analysis, canonical correlation, and factor analysis. Sampling techniques, sample error and bias, survey instrument design. Prerequisites: knowledge of probability and statistics; graduate standing or consent of instructor.
CEE 224B Transportation Data Analysis II (3). Advanced methods of statistical analysis of transportation data sources; causal modeling and structural equation models. Analysis of covariance structures involving discrete choice and ordinal scale variables. Prerequisite: CEE224A or equivalent.
CEE 225A Transportation Planning Models I (3). Analytical techniques for the study of interactions between transportation systems design and the spatial distribution of urban activities. Development of models of demographic and economic activity, land use, and facility location. Forecasting exogenous inputs to existing transportation models. Prerequisite: knowledge of introductory systems analysis.
CEE 225B Transportation Planning Models II (3). Design and application of comprehensive transportation models. Network development, demand modeling, and equilibrium assignment. Model calibration, validation, prediction, and evaluation. Regional modeling, site impact analysis, and circulation studies. Design of transportation alternatives. Prerequisites: CEE 123 or equivalent; graduate standing or consent of instructor.
CEE 226A Traffic Flow Theory I (3). Traffic measurement and fundamental speed-density-flow relationships. Kinematic models. Shock waves. Statistical-kinetic theory of traffic. Introductory car following principles and stability. Gap acceptance. Platoon dispersion. Two-fluid model. Queuing processes. Multi-regime and catastrophe models. Higher order continuum models. Microscopic and macroscopic simulation. Prerequisites: knowledge of basic probability and statistics; graduate standing or consent of instructor.
CEE 226B Traffic Flow Theory II (3). Advanced mathematical analysis of vehicular flow. Detailed treatise on car following models. Fourier and Laplace analysis of stability problems. Perturbation analysis. Derivation of macroscopic traffic flow relationships from microscopic considerations. Advanced hydrodynamic theory. Prerequisites: CEE 226A; graduate standing or consent of instructor.
CEE 227A Transportation Logistics I: Introduction to Logistics and Supply-Chain Management (3). Logistic network configuration, inventory management and risk pooling, the value of information, distribution strategies, international supply chain management, coordinated product and supply chain management, customer value and supply chain management, information technology, decision support systems. Prerequisites: graduate standing or consent of instructor.
CEE 228A Urban Transportation Networks I (3). Analytical approaches and algorithms to the formulation and solution of the equilibrium assignment problem for transportation networks. Emphasis on user equilibrium, comparison with system-optimal, mathematical programming formulation, supply functions, estimation. Estimating origin-destination matrices, network design problems. Prerequisite: CEE 220A or equivalent.
CEE 228B Urban Transportation Networks II (3). Advanced analysis, optimization and modeling of transportation networks. Topics include advanced static and dynamic traffic assignment algorithms, linear and nonlinear multi-commodity network flow optimization, network simplex and network control problems. Prerequisites: CEE 221A, CEE 228A.
CEE 229A Traffic Systems Operation & Control I (3). Introduction to operation, control and analysis of arterial and freeway traffic systems. Control concepts, detectors, local controllers and system master, incident detection, advanced traffic measurement technologies, intelligent transportation systems, advanced transportation management systems, advanced traveler information systems. Prerequisites: CEE 122 or equivalent.
CEE 229B Traffic Systems Operation & Control II (3). Introduction to control theory. Control formulations for corridor and network systems with freeways and arterials. Real-time control and demand management. Development and application of microscopic and macroscopic simulation models for integrated traffic systems. Dynamic models of Intelligent Vehicle-Highway Systems. Prerequisites: CEE 229A; graduate standing or consent of instructor.
CEE 283 Mathematical Methods in Engineering Analysis (3). Tensors and matrices; eigenvalue problems; partial differential equations; boundary value problems; special functions; introduction to complex variables; calculus of variations and its applications.
CEE 295C Transportation Engineering Seminar (1). Seminars scheduled each quarter by individual faculty in major field of interest.
|Transportation Planning Courses:||[ back to top ]|
U 202 History of Urban Planning (4). Introduction to the historical roots and fundamental perspectives of urban and regional planning. Exploration of the significant historical phases and personalities that have shaped the profession. The roles, responsibilities, limitations and potential of urban planning are addressed. Prerequisite: graduate standing.
U 211 Urban Design and Behavior (4). Acquaints students with vocabulary, history, theories, process and trends in urban design. The local environment is used as a resource and a laboratory, providing a context for understanding urban design practices and products in Southern California and beyond. Prerequisite: graduate standing.
U 212 Transportation Planning (4). Introduces current topics in transportation planning. Includes an analysis of the economic role of transportation in urban areas, land-use impacts of transportation projects, traffic congestion, air quality, alternatives to the automobile and other transportation topics. Prerequisite: graduate standing.
U 223 Regional Analysis (4). Major concepts and techniques of regional analysis, with applications for urban and regional planning and public policy-making. Definition of regions, processes of economic change, regional structure, location of activities and analysis of selected policy issues. Emphasis on practical applications. Prerequisites: graduate standing or consent of instructor.
U 231 Transportation and the Environment (4). Explores environmental impacts of transportation from several perspectives, including planning, industrial ecology, and economics. The main focus is on motor vehicle transportation, especially cars. Prerequisites: graduate standing or consent of instructor.
U 233 Transportation, Transit, and Land-Use Policy and Planning (4). Places students into a specific transportation public policy situation to devise real solutions, with the goal of helping students understand factors in land use, travel behavior, politics, and finance that shape transportation planning policy choices. Prerequisite: graduate standing or consent of instructor.
U 234 Environmental Analysis (4). Explores theory and methods for the analysis of environmental patterns and their linkage to policy. Involves discussions on fundamentals of theories for analysis, along with hands-on instruction on analytical methods. Topics include: spatial analysis, risk representation, and sustainability planning. Prerequisite: graduate standing or consent of instructor.
U 237 Introduction to Geographic Information Systems (4). Application of geographic information systems (GIS) to the field of urban and regional planning. Emphasizes current issues that occur in actual implementation settings. Lecture/discussion followed by laboratory demonstrations of the GIS topic discussed. Offers "hands-on" student use of GIS software.
U 238 Advanced Geographic Information Systems (4). Extends study of geographic information systems to more advanced issues including data sources, data conversion, relational database integration, software customization and spatial and three-dimensional analysis. Prerequisite: U237.
U 242 Regional Development Theory (4). Regional economic development concepts and studies, with applications for urban and regional planning and public policy-making. Roles and performance of economic sectors, technological innovation and communications in the process of development. Analysis of regional development policies and programs. Prerequisites: graduate standing or consent of instructor.
U 244 Land-Use Policy (4). Examination of the role of public policy in guiding growth and development in urban and suburban environments. Description of a wide-ranging set of growth policies, the rationale underlying their use, controversies and legal constraints and evaluation of their effectiveness. Prerequisite: graduate standing.
|Transportation Economics Courses:||[ back to top ]|
ECON 223A Discrete Choice Econometrics (4). Specification, estimation, and testing of discrete choice models, with emphasis on cross-section application. Qualitative choice, limited dependent variables, sample selection bias, and latent variables. Students use computer packages to apply models to real data. Prerequisites: ECON 220A-B-C-D.
ECON 281A-B: Urban Economics I, II (4-4). Theoretical and empirical analysis of the economic functioning of urban areas. Urban economic development, location of firms and households, housing markets, urban public finance. Econometric estimation of hedonic price functions for housing. Prerequisites: ECON 100B and 203A or equivalent.
ECON 282A Transportation Economics I (4). Economic analysis of intercity transportation. Cost measurement, applications of pricing principles, project evaluation, and economic regulation. Policy toward railroads, air passenger transport, and intercity highways.
ECON 282B Transportation Economics II (4). Travel demand analysis including discussion of econometric techniques. Pricing and investment in urban transportation, selected policy issues.
ECON 285A-B-C Colloquium for Transportation Science I, II, III (2-2-2). Selected perspectives on transportation based on the study of human behavior. Organized by the Interdisciplinary Program in Transportation Science. Research presentations by faculty, students, and visitors supplemented by class discussion. Prerequisite: graduate standing or consent of instructor.
ECON 289A-Z Special Topics in Urban and Transportation Economics (4). Prerequisites vary. May be repeated for credit as topics vary.
|Other Related Courses:||[ back to top ]|
ICS 243A Computer Networks (4). Discussion of various techniques to provide communication among processes in distributed environments. Topics covered include layering protocol architectures, packet switched networks, local area networks, interprocess communication, internetworking, high-speed networks, multi-media networks. Prerequisite: consent of instructor. Formerly ICS 243.
ICS 260 Fundamentals of the Design and Analysis of Algorithms (4). Covers fundamental concepts in the design and analysis of algorithms and is geared toward non-specialists in theoretical computer science. Topics include: deterministic and randomized graph algorithms, fundamental algorithmic techniques like divide-and-conquer strategies and dynamic programming, and NP-completeness. Prerequisite: ICS 161 or equivalent undergraduate algorithms course.
ICS 275A Network-Based Reasoning/Constraint Networks (4). Study of the theory and techniques of constraint network model. Covers techniques for solving constraint satisfaction problems: backtracking techniques, consistency algorithms, and structure-based techniques. Tractable subclasses. Extensions into applications such as temporal reasoning, diagnosis, and scheduling. Prerequisite: a basic course in algorithm design and analysis, or consent of instructor.
ICS 275B Network-Based Reasoning/Belief Networks (4). Focuses on reasoning with uncertainty using "Bayes Networks" that encode knowledge as probabilistic relations between variables, and the main task is, given some observations, to update the degree of belief in each proposition. Prerequisite: a basic course in probability or consent of instructor.
SS 201A Descriptive Multivariate Statistics I (4). Mathematical tools to organize and illuminate the multivariate methods. Multiple regression analysis, multi-dimensional scaling, and cluster analysis. Statistical computing via MDS(x), DMDP, and SPSS. Students must enroll in the laboratory section which meets on Wednesdays. Prerequisite: Social Science 100A-B-C or equivalent. Satisfactory/Unsatisfactory grading only. Same as Information and Computer Science 238A, Social Ecology 290A, and Management 290X.
201B Descriptive Multivariate Statistics II (4). Presentation of the principal methods of multivariate statistics including criteria for appropriate use and the interpretation of resulting measurements. Computer exercises are used to demonstrate concepts. Prerequisite: Social Science 201A. Same as Information and Computer Science 238B, Social Ecology 290B, and Management 290Y.
201C Sampling Techniques and Estimation Methods (4). A review of confidence interval estimates derived from simple random samples is followed by a representation of techniques for improving the precision of such estimates under the constraints of feasibility, cost, and time. Methods for dealing with bias and nonsampling errors are also considered. Outside speakers. Prerequisites: Social Science 100A-B-C or equivalent. Same as Social Ecology 290C and Management 290Z. Satisfactory/Unsatisfactory only.
|Undergraduate Transportation Courses:||[ back to top ]|
CEE 121 Transportation Systems I: Analysis and Design (4). Introduction to analysis and design of fundamental transportation system components, basic elements of geometric and pavement design, vehicle flow and elementary traffic, basic foundations of transportation planning and forecasting. Laboratory sessions. Prerequisites: CEE10, CEE81B. (Design units: 2)
CEE 122 Transportation Systems II: Operations and Control (4). Introduction to fundamentals of urban traffic engineering, including data collection, analysis, and design. Traffic engineering studies, traffic flow theory, traffic control devices, traffic signals, capacity and level of service analysis of freeways and urban streets. Laboratory sessions. Prerequisites: CEE11, CEE121. (Design units: 2)
CEE 123 Transportation Systems III: Planning and Forecasting (4). Theoretical foundations of transportation planning, design, and analysis methods. Theory and application of aggregate and disaggregate models for land use development, trip generation, and destination, mode, and route choice. Transportation network analysis. Planning, design, and evaluation of system alternatives. Laboratory sessions. Prerequisites: CEE121; co-requisite: CEE110. (Design units: 2)
CEE 124 Transportation Systems IV: Freeway Operations and Control (4). Fundamentals of traffic on urban freeways, including data collection, analysis, and design. Traffic engineering studies, traffic flow theory, freeway traffic control devices, capacity and level of service analysis of freeways and highways. Laboratory sessions. Prerequisite: CEE121. (Design units: 2)
CEE 125 Transportation and the Environment (4). (Design units: 0)
PPD 108 Cities and Transport (4). The relationship between urban areas and transportation systems. Economic analysis of cities, transportation and urban form, highway congestion, environmental impacts of transportation, public transit, land use and transportation, and political influences on transportation planning.
Econ 149 Introduction to Transportation Economics (4).
ICS 168 Network Optimization (4). Network modeling techniques and related algorithms for solving large-scale integer programming problems. Exact methods and heuristic techniques. Applications include computer and communication networks and transportation and logistic networks.
|UCI Transportation Courses:||[ back to top ]|