Intelligent Transportation (TLKK2500)

Intelligent Transportation, 5 cr - TLKK2500

Intelligent Transportation (TLKK2500-3010), 08.01.2024 – 30.04.2024,
5 cr (TLS21S1) — Face-to-face + -
Language of instruction

Finnish

Timing

08.01.2024 - 30.04.2024

Lecturer(s)

Juha Pesonen, Kimmo Lehtonen

Planned learning activities, teaching methods and guidance

Course contains learning tasks, lectures, lab exercises, group assignments and group learning tasks.

Learning materials and recommended literature

Described in learning environment.

Campus

Main Campus

Exam dates and re-exam possibilities

Assessment is based on learning assignments. This course doesn't have an exam.

Learning assignments and student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Enrollment

20.11.2023 - 04.01.2024
Groups
- TLS21S1
Alternative learning methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Seats

0 - 50

Assessment methods

Avoin AMK: no limits

Degree Programme

Bachelor's Degree Programme in Logistics

Mode of delivery

Face-to-face

Share of R&D studies

0.00 cr

Share of virtual studies

0.00 cr

Unit

School of Technology
Intelligent Transportation (TLKK2500-3011), 08.01.2024 – 30.04.2024,
5 cr (TLP21S1, ...) — Face-to-face + -
Language of instruction

English

Timing

08.01.2024 - 30.04.2024

Lecturer(s)

Juha Pesonen, Kimmo Lehtonen

Planned learning activities, teaching methods and guidance

Course contains lectures (30 h), lab exercises, group assignments and group learning tasks.

Learning materials and recommended literature

Described in learning environment.

Campus

Main Campus

Exam dates and re-exam possibilities

Assessment is based on learning assignments. This course doesn't have an exam.

Learning assignments and student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Enrollment

20.11.2023 - 04.01.2024
Groups
- TLP21S1
- TLP23VS
- TLP24VK
Alternative learning methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Seats

0 - 20

Assessment methods

Avoin AMK: no limits

Degree Programme

Bachelor's Degree Programme in Purchasing and Logistics Engineering

Mode of delivery

Face-to-face

Share of R&D studies

0.00 cr

Share of virtual studies

0.00 cr

Unit

School of Technology
Intelligent Transportation (TLKK2500-3012), 28.08.2023 – 19.12.2023,
5 cr (UTIVERKKO) — Online learning + -
Language of instruction

Finnish

Timing

28.08.2023 - 19.12.2023

Lecturer(s)

Juha Pesonen, Kimmo Lehtonen

Planned learning activities, teaching methods and guidance

The course contains learning tasks, group assignments and group learning tasks. The course doesn't include contact classes or webinars.

Learning materials and recommended literature

Described in learning environment

Campus

Main Campus

Exam dates and re-exam possibilities

Assessment is based on learning assignments. This course doesn't have an exam.

Learning assignments and student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Enrollment

01.08.2023 - 24.08.2023

Content scheduling

The course is completed online
Groups
- UTIVERKKO
Alternative learning methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Seats

0 - 15

Assessment methods

Avoin AMK: No limits

Degree Programme

Bachelor's Degree Programme in Logistics

Mode of delivery

Online learning

Share of R&D studies

0.00 cr

Share of virtual studies

5.00 cr

Unit

School of Technology
Intelligent Transportation (TLKK2500-3013), 08.01.2024 – 19.05.2024,
5 cr (UTIVERKKO) — Online learning + -
Language of instruction

Finnish

Timing

08.01.2024 - 19.05.2024

Lecturer(s)

Juha Pesonen, Kimmo Lehtonen

Planned learning activities, teaching methods and guidance

The course contains learning tasks, group assignments and group learning tasks. The course doesn't include contact classes or webinars.

Learning materials and recommended literature

Described in learning environment

Campus

Main Campus

Exam dates and re-exam possibilities

Assessment is based on learning assignments. This course doesn't have an exam.

Learning assignments and student workload

One credit corresponds to an average of 27 hours of work, which means that the load of five credits is approximately 135 hours. The load is distributed in different ways depending on the course implementation.

Enrollment

20.11.2023 - 04.01.2024

Content scheduling

The course is completed online
Groups
- UTIVERKKO
Alternative learning methods

The admission procedures are described in the degree rule and the study guide. The teacher of the course will give you more information on possible specific course practices.

Seats

0 - 15

Assessment methods

Avoin AMK: No limits

Degree Programme

Bachelor's Degree Programme in Logistics

Mode of delivery

Online learning

Share of R&D studies

0.00 cr

Share of virtual studies

5.00 cr

Unit

School of Technology
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The object of the course
More than a third of the supply chain costs are created by the last-mile delivery. Transport companies require excellent management to be able to reduce costs, deliver products on time and respond to rapid changes. After this course you will know how transport companies optimize fleet utilization and how to improve product distribution while acknowledging the environmental issues of logistics.

Course competences
This course develops and assesses the following knowhow: Transport Competence, Engineering practice (EA-EC), communication and teamwork.

The learning objectives of the course
The student can optimize routes and usage of transportation vehicles and can use the results of optimization in designing a transportation system. The student knows the methods of solving the last mile problem and understands their importance for the operation of a transport company. In addition, the student understands the environmental impact of the last-mile problem. The student is able to work in a group and produce a logical report.

In this course you will study the following topics:
- Ecommerce distribution systems
- Route planning of a transportation system
- Using of a optimization software in transport planning

- Logistiikan maailma
- Projektilogistiikka

0-5

1. The student is able to utilize optimization in the design of a transportation system. The student knows the methods for solving the last mile problem and understands how Transport Companies utilize them. The student is aware of the environmental impacts of distribution transport. The student is able to work in a group and produce a logical report.

2. The student is able to utilize optimization in the design of a transportation system. The student knows several methods for solving the last mile problem and understands how Transport Companies utilize them. The student understands the environmental impacts of distribution transport. The student is able to work in a group and produce a logical report.

3. The student is able to utilize optimization in designing a transportation system in a versatile manner. The student knows several methods for solving the last mile problem and understands their potential for Transport Companies. The student understands the environmental impacts of distribution transport. The student actively participates in group activities and is able to produce a logically progressive report.

4. The student is able to utilize and apply optimization in a versatile manner for the design of transportation systems. The student knows several methods for solving the last mile problem and understands the potential of their utilization for different industries. The student understands the environmental impact of transportation and storage options on last mile transport. The student actively participates in group activities and is able to produce a logically progressive report.

5. The student is able to utilize and apply optimization in a versatile manner for the design of transportation systems. The student knows several methods for solving the last mile problem and understands how they can be used to improve the efficiency of transportation in different industries. The student understands the environmental impact of transport and storage options on last mile transport and is able to make a sound comparison. The student is active in the group and is able to produce an extensive logically progressive report.

Intelligent Transportation, 5 cr - TLKK2500

Upcoming implementations