| Language of instruction : English |
| Exam contract: not possible |
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Sequentiality
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No sequentiality
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| Degree programme | | Study hours | Credits | P1 SBU | P1 SP | 2nd Chance Exam1 | Tolerance2 | Final grade3 | |
 | 1st year Master of Transportation Sciences (incl ICP) | Compulsory | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical |  |
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| | | Learning outcomes |
- EC
| EC2: The holder of the degree has in-depth knowledge and understanding of the concepts, methods, and (research) techniques of transportation sciences. He/she is able to apply the concepts, methods and (research) techniques in the field of transportation sciences adequately and autonomously. | - EC
| EC4: The holder of the degree considers the society as a whole as an important stakeholder and reflects on the social relevance and consequences of recommendations/solutions and projects/assignments in a critical manner. In doing so, the holder of the degree strives, among other things, to have a sustainable impact on the region. | - EC
| EC5: The holder of the degree is made aware of and has insight into the regional and international policy framework, similarities and differences with respect to transport policies. The holder of the degree is encouraged to get in touch with various (inter)national stakeholders active in the field of transportation. |
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| | EC = learning outcomes DC = partial outcomes BC = evaluation criteria |
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The students should have a basic knowledge of traffic science terminologies. The students should have good analytical skills and critical thinking to interpret various transportation-related issues. It is also advisable to have some basic IT knowledge.
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Description:
This courses enables transportation sciences students from various backgrounds to intelligent and smart transportation solutions that influence technological advancements. Traditional methods such as advanced traveler information and dynamic message signs are now part of a broader landscape that features deployments of connected, automated, and autonomous vehicle technologies with infinite possibilities. The effective utilization of current emerging technologies requires an interdisciplinary approach with focus on the benefits, operating characteristics, deployment considerations, and potential shortcomings of the deployed solutions in various transport scenarios. Some of the key topics will focus on hands-on case studies that encourage critical thinking to assess opportunities for the continuous improvement of deployed and new solutions, tailored to the local context.
Objectives:
The end-competences of this course include (but not limited to):
- A conceptual understanding of the most common intelligent solutions in transportation with their anticipated benefits, and their shortcomings.
- A basic understanding of how emerging technological developments would transform the transportation system in the near future.
- Knowledge to plan for the practical deployment of such solutions.
- Insights into the vast potential of possible approaches to apply current technologies in ways that would facilitate useful interactions between transportation supply and demand, performance measures, planning, and policy making.
- Experience with some simualtion systems will be explained during the self-learning tasks. Will be discussed further in the class!
Content:
- Traveler information and advisory systems (such as dynamic signage, onboard equipment, CCTV, smartphone applications)
- Traffic flow control (including adaptive signaling, ramp metering, variable speed limits/warnings, transit priority
- Automatic electronic payments (such as toll tags, transit cards, RFID, smartphones)
- Pre-clearance systems (including vehicle classification, high-speed weigh-in-motion, roadside inspection, freight scanners)
- Technologies for managed facilities (such as HOV and other dedicated lanes)
- Smart parking solutions (occupancy sensors, parking reservation systems, metering technologies, etc.)
- Security and privacy impacts of technology deployments
- Connected vehicles technologies and architectures
- Major applications of connected vehicle technologies (information, ride sharing, crash avoidance, driver assist, platoons, etc.)
- Automated and autonomous vehicles
- Cloud computing (advisory systems: security threats, weather, work zones, incidents, detours, traffic)
- Big Data (travel time forecasting, maintenance decision-support, flow optimization, parking availability)
- Remote sensing (surveillance, satellites, UAV technology, emergency response incident management)
- Smart solutions in transportation for improving environment
- Sustainable mobility solutions in a cross-sectoral context (e.g. tourism)
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Lecture ✔
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Project ✔
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Response lecture ✔
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Small group session ✔
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Demonstration ✔
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Discussion/debate ✔
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Exercises ✔
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Presentation ✔
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Period 1 Credits 4,00
| Evaluation method | |
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| Written evaluaton during teaching periode | 0 % |
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| Oral evaluation during teaching period | 20 % |
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| Evaluation method in consultation with student during teaching period | 10 % |
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| Transfer of partial marks within the academic year | ✔ |
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| Conditions transfer of partial marks within the academic year | These scores will be kept the same for the 2nd chance. |
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| Explanation (English) | Class Interaction & Peer Feedback |
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| Other evaluation method during teaching period | 10 % |
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| Other | Participation in the self-learning session/task |
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| Transfer of partial marks within the academic year | ✔ |
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| Conditions transfer of partial marks within the academic year | These scores will be kept the same for the 2nd chance. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
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| Explanation (English) | New Written (open-book) exam. Other scores will be kept from the 1st chance. |
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| Recommended reading |
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Intelligent Transport Systems in Europe: Opportunities for Future Research,Mike Mcdonald; Hartmut Keller; Job Klijnhout; Vito Mauro; Richard Hall; Angela Spence; Christoph Hecht; Oliver Fakler,World Scientific Publishing Company,Available as e-book: https://ebookcentral.proquest.com/lib/ubhasselt/detail.action?docID=1214471&pq-origsite=summon |
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| Recommended course material |
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- No handbook required.
- The course will be composed on lecture notes & slides from the professors/lecturers.
- For the interactive self-learning part you will be provided with video links + some guided talks.
- There could be a number of guest lectures invited to this course with certain domain expertise.
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| Exchange Programme Transportation Sciences | Optional | 108 | 4,0 | 108 | 4,0 | Yes | Yes | Numerical | |
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| |
|
|
The students should have a basic knowledge of traffic science terminologies. The students should have good analytical skills and critical thinking to interpret various transportation-related issues. It is also advisable to have some basic IT knowledge.
|
|
|
|
Description:
This courses enables transportation sciences students from various backgrounds to intelligent and smart transportation solutions that influence technological advancements. Traditional methods such as advanced traveler information and dynamic message signs are now part of a broader landscape that features deployments of connected, automated, and autonomous vehicle technologies with infinite possibilities. The effective utilization of current emerging technologies requires an interdisciplinary approach with focus on the benefits, operating characteristics, deployment considerations, and potential shortcomings of the deployed solutions in various transport scenarios. Some of the key topics will focus on hands-on case studies that encourage critical thinking to assess opportunities for the continuous improvement of deployed and new solutions, tailored to the local context.
Objectives:
The end-competences of this course include (but not limited to):
- A conceptual understanding of the most common intelligent solutions in transportation with their anticipated benefits, and their shortcomings.
- A basic understanding of how emerging technological developments would transform the transportation system in the near future.
- Knowledge to plan for the practical deployment of such solutions.
- Insights into the vast potential of possible approaches to apply current technologies in ways that would facilitate useful interactions between transportation supply and demand, performance measures, planning, and policy making.
- Experience with some simualtion systems will be explained during the self-learning tasks. Will be discussed further in the class!
Content:
- Traveler information and advisory systems (such as dynamic signage, onboard equipment, CCTV, smartphone applications)
- Traffic flow control (including adaptive signaling, ramp metering, variable speed limits/warnings, transit priority
- Automatic electronic payments (such as toll tags, transit cards, RFID, smartphones)
- Pre-clearance systems (including vehicle classification, high-speed weigh-in-motion, roadside inspection, freight scanners)
- Technologies for managed facilities (such as HOV and other dedicated lanes)
- Smart parking solutions (occupancy sensors, parking reservation systems, metering technologies, etc.)
- Security and privacy impacts of technology deployments
- Connected vehicles technologies and architectures
- Major applications of connected vehicle technologies (information, ride sharing, crash avoidance, driver assist, platoons, etc.)
- Automated and autonomous vehicles
- Cloud computing (advisory systems: security threats, weather, work zones, incidents, detours, traffic)
- Big Data (travel time forecasting, maintenance decision-support, flow optimization, parking availability)
- Remote sensing (surveillance, satellites, UAV technology, emergency response incident management)
- Smart solutions in transportation for improving environment
- Sustainable mobility solutions in a cross-sectoral context (e.g. tourism)
|
|
|
|
|
|
|
|
|
Lecture ✔
|
|
|
|
Project ✔
|
|
|
|
Response lecture ✔
|
|
|
|
Small group session ✔
|
|
|
|
|
|
|
|
Demonstration ✔
|
|
|
|
Discussion/debate ✔
|
|
|
|
Exercises ✔
|
|
|
|
Presentation ✔
|
|
|
|
Period 1 Credits 4,00
| Evaluation method | |
|
| Written evaluaton during teaching periode | 0 % |
|
|
|
| Oral evaluation during teaching period | 20 % |
|
|
|
|
| Evaluation method in consultation with student during teaching period | 10 % |
|
| Transfer of partial marks within the academic year | ✔ |
|
| Conditions transfer of partial marks within the academic year | These scores will be kept the same for the 2nd chance. |
|
|
|
|
|
| Explanation (English) | Class Interaction & Peer Feedback |
|
|
|
|
|
| Other evaluation method during teaching period | 10 % |
|
| Other | Participation in the self-learning session/task |
|
|
|
| Transfer of partial marks within the academic year | ✔ |
|
| Conditions transfer of partial marks within the academic year | These scores will be kept the same for the 2nd chance. |
|
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|
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| Use of study material during evaluation | ✔ |
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| Explanation (English) | The students are allowed to use lectures slides during the written exam. |
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Second examination period
| Evaluation second examination opportunity different from first examination opprt | |
|
| Explanation (English) | New Written (open-book) exam. Other scores will be kept from the 1st chance. |
|
|
|
|
|
| Recommended reading |
| |
Intelligent Transport Systems in Europe: Opportunities for Future Research,Mike Mcdonald; Hartmut Keller; Job Klijnhout; Vito Mauro; Richard Hall; Angela Spence; Christoph Hecht; Oliver Fakler,World Scientific Publishing Company,Available as e-book: https://ebookcentral.proquest.com/lib/ubhasselt/detail.action?docID=1214471&pq-origsite=summon |
|
|
| Recommended course material |
| |
- No handbook required.
- The course will be composed on lecture notes & slides from the professors/lecturers.
- For the interactive self-learning part you will be provided with video links + some guided talks.
- There could be a number of guest lectures invited to this course with certain domain expertise.
|
|
|
|
|
|
1 Education, Examination and Legal Position Regulations art.12.2, section 2. |
| 2 Education, Examination and Legal Position Regulations art.16.9, section 2. |
3 Education, Examination and Legal Position Regulations art.15.1, section 3.
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| Legend |
| SBU : course load | SP : ECTS | N : Dutch | E : English |
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