1. Name of the Course课程名称
Chinese Name:海事运输网络分析
English Name: Maritime Transportation Network Analysis
2. Overview of the Course课程概况
Category课程类别：Major Degree Courses Class hours学时数：32 Credit学分数：2
Profession适用专业：Transportation Planning and Management Semester开课学期：The 2nd Semester
College开课单位：College of Transport and Communications
3. The Writer大纲编写人：Visiting Professor
4. The Objective and Requirement of the Course教学目的及要求
This short course will prepare students to engage more fully in transport planning, with a clear understanding of the methods used to model transport systems, so to analyse their operation more effectively and ultimately to design them better. The broad coverage will also prepare students for future developments in this important area of transport studies.
After completing this course the students will be able to:
· Understand the four-stage approach to transport planning
· Formulate network models of travel
· Distinguish among different traffic assignment principles
· Compare network performance under different route choice principles
· Identify the need for combined transport models
· Understand the importance of statistical modelling approaches
· Be able to specify, estimate and interpret appropriate statistical models
· Represent transport and traffic management policies within the four-stage framework
· Interpret differences between model runs with different specifications
· Choose among different assignment principles according to the policy to be evaluated
· Incorporate value of time as a motivation for departure time choice
· Adopt dynamic transport models where appropriate
5. Main Content of the Course and Pre-course课程主要内容及先修课程
Equilibrium network models
The purpose of these lectures is to familiarize students with the structure of the four-stage transport planning model and the way in which it represents travelers' dimensions of choice. The focus is on the role of road traffic assignment and equilibrium modeling within this.
Optimisation
The purpose of these lectures is to introduce to students the concepts of using unconstrained and constrained optimisation as equivalent formulations to equilibrium transport models, and interpret their results in terms of travel behaviour.
Combined transport model
The purpose of these lectures is to introduce to students ways in which stages of the transport planning process can be combined to achieve mutual consistency between travel behaviour and the associated costs.
Trip matrix estimation
The purpose of this lecture is to familiarize students with a range of approaches to using low-cost abundant traffic data to estimate travel demand trip matrices for use in road traffic assignment.
Dynamic traffic assignment
The purpose of this lecture is to extend static transport model to dynamic ones that can represent peak-period congestion and travelers' response to this explicitly. This treatment includes choice of departure time.
6. Teaching Methods课程教学方法
The course in Transport Network Analysis will explore the role of this quantitative approach in the transport planning process. The framework for this is the 4-stage transport planning model comprising Trip generation, Trip distribution, Mode split and Traffic assignment. Within this framework, the focus of network analysis is in the traffic assignment stage, which takes an origin-destination trip matrix as a representation of travel demand and a transport network as a representation of supply. The relationship between supply and demand is resolved by adopting an assignment principle that represents the route choice of individuals. This course will explore the relationships among supply, demand and assignment principle, and will show how the resulting model for the 4th stage of the transport planning process integrates with other parts of it. Attention will be paid to each of equilibrium, stochastic equilibrium and system optimal assignment principles. Combined transport models will also be explored that represent the integration of the assignment process together travel demand as represented by mode choice and by trip distribution to achieve mutual consistency between these elements of the transport planning process. Integration of the assignment process with network design will be introduced as a way of anticipating travelers' response to changes in transport provision: this will be illustrated with examples to show the importance for strategic investment in transport facilities. The topic of dynamic traffic assignment will also be introduced, including the choice of travelers' departure times.
Composition of activities
· Classroom activities: Lecture presentations by internet for class teaching: 60%
· Case study presentations: 20%
· In-class activities with set exercises and use of provided software: 20%
· Additional out of class activities: supplementary reading and study in order to become familiar with the methods presented and sources of data described.
7. Methods of Examination课程考核方式
Assessment will be in the form of a take-home assessment that will be set to the students at the end of the course. This will exercise and test the students in their understanding of the whole range of material that has been presented, and will provide them with an opportunity to show how they see the techniques being applied in novel ways.
8. Textbook课程使用教材
9. Main References课程主要参考资料
Bar Gera, H (2002) Origin-based algorithm for the traffic assignment problem. Transportation Science, 36(4), 398-417.
Bazaraa, MS, Sherali, HD and Shetty, CM (2006) Nonlinear programming: theory and applications, 3rd edition. Chichester: Wiley.
Bell, MGH (1983) The estimation of an origin-destination matrix from traffic counts. Transportation Science, 17, 198-217.
Ben-Akiva, M and Lerman, SR (1985) Discrete choice analysis: theory and application to travel demand. London: MIT Press.
Brenninger-Göthe, M Jörnsten, Ko and Lundgren, J (1989) Estimation of origin-destination matrices from traffic counts using multiobjective programming formulations. Transportation Research (Part B), 23B(4), 257-69.
Bureau of Public Roads (1964) Traffic assignment manual. Washington DC: Department of Commerce.
Burrell, JE (1969) Multiple route assignment and its application to capacity restraint. Proceedings of the 4th International Symposium on the Theory of Traffic Flow. Karlsruhe, 210-9.
Dafermos, SC and Sparrow, FT (1968) The traffic assignment problem for a general network. National Bureau of Standards Journal of Research, 73B, 91-118.
Daganzo, CF and Sheffi, Y (1977) On stochastic models of traffic assignment. Transportation Science, 11(3), 243-74.
Dial, RB (1971) A probabilistic multipath traffic assignment model which obviates path enumeration. Transportation Research, 5(2), 83-111.
Evans, SP (1976) Derivation and analysis of some models for combining trip distribution and assignment. Transportation Research, 10(1), 37-57.
Fisk, CS (1980) Some developments in equilibrium traffic assignment. Transportation Research, 14B(3), 243-55.
Frank M and Wolfe, P (1956) An algorithm for quadratic programming. Naval Research Logistic Quarterly, 3, 95-110.
Heydecker, BG (1986) On the definition of traffic equilibrium. Transportation Research, 20B(6), 435-40.
Heydecker, BG and Addison, JD (2005) Analysis of dynamic traffic equilibrium with departure time choice. Transportation Science, 39(1), 39-57.
Law, AM (2015) Simulation modeling and analysis (5th edition). London: McGraw-Hill.
Luenberger, DG and Ye, Y (2008) Linear and nonlinear programming (3rd edition). International Series in Operations Research and Management Science 116. New York: Springer.
Marcotte, P and Patriksson, M (2007) Traffic equilibrium. In: Transportation, Volume 14 of Handbooks in OR and Management Science (Eds C Barnhart and G Laporte), Elsevier, 623–713. (See also:
http://www.math.chalmers.se/~mipat/LATEX/traffic_equilibrium.ps )
Matzoros, A, Van Vliet, D, Randle, J and Weston, B (1987) A validation of the SATURN and ME2 models using before-and-after survey data from Manchester. Traffic Engineering and Control, 28(12), 641-3.
Murchland, JD (1970) Braess's paradox of traffic flow. Transportation Research, 4(4), 391-4.
Powell, WB and Sheffi, Y (1982) The convergence of equilibrium algorithms with predetermined step sizes. Transportation Science, 16, 45-56.
Smith, MJ (1979) The existence, uniqueness and stability of traffic equilibria. Transportation Research, 13B(4), 295-304.
Smith, MJ (1984) Two alternative definitions of traffic equilibrium. Transportation Research, 18B(1), 63-5.
Van Vliet, D (1978) Improved shortest path algorithms for assignment methods. Transportation Research, 12(1), 7-20.
Van Vliet, D (1979b) Capacity-restrained road assignment - 1. The convergence of stochastic methods. Traffic Engineering and Control, 20(6), 296-9.
Van Vliet, D (1987) The Frank-Wolfe algorithm for equilibrium traffic assignment viewed as a variational inequality. Transportation Research, 21B(1), 87-9.
Van Zuylen, HJ and Willumsen, LG (1980) The most likely trip matrix estimated from traffic counts. Transportation Research (Part B), 14B(3), 281-93.
Williams, HCWL (1977) On the formation of travel demand models and economic evaluation measures of user benefit. Environment and Planning, 9A, 285-344.
Willumsen, LG (2019) Mobile phone trip matrices are not all born the same. Local Transport Today, 787, 20-1.