Module Catalogue 2024/25

Pre Requisite Comment

N/A

Co Requisite Comment

N/A

Aims

The main aim of this module is to introduce essential methods and tools used in transport modelling and analysis, to better understand the demands that drive transport behaviour. By equipping students with knowledge and skills of a range of modelling methods and tools, this module enables student to select and implement an appropriate method to model the consequences of transport engineering, planning and policy decisions, including a geospatial perspective. Core aspects of transport demand forecasting, geospatial data science and modelling, and transport simulation will be covered, and allow the student to understand and have hands-on experience with simulation and modelling exercises.


The specific aims of the module are:
-       To provide an understanding of transport demand models for predicting overall travel patterns;
-       To enable students to develop a working knowledge of transport simulation models;
-       To introduce students to the fundamentals of Geographic Information Systems (GIS) and geospatial data handling;
-       To enable students to perform modelling and analysis using appropriate tools.

Outline Of Syllabus

Topics will cover advanced and cutting-edge transport and geospatial analysis and simulation technique, such as:

Transport Demand Forecasting:
-       Introduction to transport planning
-       trip generation techniques
-       trip distribution modelling
-       modal choice modelling
-       Assignment and Route Choice Models

Transport Simulation:
-       Basics of transport simulation
-       Network and demand modelling
-       introduction to traveller behaviour models
-       Model calibration and evaluation metrics
-       Transport simulation software

GIS and Geospatial data handling:
-       Introduction to GIS including basic concepts, cartographic basics, e.g., making a map visualisation, choropleth mapping, thematic mapping.
-       Network analysis in GIS, including different types of analysis, e.g., shortest route, least cost, OD matrix, service area
-       Sources of transport-related data
-       Data analysis in Python
-       Obtaining basic GIS data, data manipulation, mapping.
-       Accessing transport network data from Digimap, network analysis
-       Python analysis, e.g., assessing traffic counter data

Intended Knowledge Outcomes

The mapping of certain AHEPv4 learning outcomes to each intended knowledge outcome is
indicated in each point. By the end of the module a student will be able to:

1.       Understand and apply core principles and models in four-stage travel demand forecasting
for transport planning (M6)
2.       Understand essential techniques and skills in transport simulation, and apply software to conduct transport simulation and analyse implications (M3)
3.       A grounding in the basic concepts that underpin GIS and geographical analysis in a practical transport setting (M12)
4.       An understanding of the geospatial data types that enable transport analysis (M13)
5.       An introduction to the types of outputs that GIS can produce (M17)

Intended Skill Outcomes

The mapping of certain AHEPv4 learning outcomes to each intended skills outcome is
indicated in each point. By the end of the module a student will be able to:

1.       Identify appropriate model types for a range of transport situations (M13)
2.       Create models to represent a range of transport situations (M12)
3.       Present and interpret the results from transport modelling models (M17)
4.       The ability to confidently navigate GIS software, access data, and work with different data formats (M12)
5.       identify and process appropriate transport-related geospatial to provide insight on travel behaviour (M6)
6.       produce and present map outputs using appropriate cartographic principles (M17)

Teaching Rationale And Relationship

Teaching and learning of this module is done by a combination of lectures, labs and practical work, guest lectures, coursework and reading materials. This is in line with the learning outcomes. Lectures, guest lectures and coursework are intended to provide the theoretical background, labs allow students to learn the software and the codes to build the modelling model. Practical work allows students to learn how to link the theory with the practice help developing problem solving skills. Reading materials helps developing critical, independent and innovative thinking.

Assessment Rationale And Relationship

The two assessments are intended to serve two purposes:
(1)       Assignment 1 assesses skills with GIS tools with the submission based on practical outputs
(2)       Assignment 2 assesses knowledge in applying transport modelling theory

General Notes

N/A