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Graduate courses

Departments' graduate courses for PhD-students.


Syllabus for

Academic year
TME192 - Active safety  
Aktiv säkerhet
Syllabus adopted 2021-02-26 by Head of Programme (or corresponding)
Owner: MPAUT
7,5 Credits
Grading: TH - Pass with distinction (5), Pass with credit (4), Pass (3), Fail
Education cycle: Second-cycle
Main field of study: Automation and Mechatronics Engineering, Bioengineering, Computer Science and Engineering, Electrical Engineering, Software Engineering, Mechanical Engineering, Engineering Physics

Course round 1

Teaching language: English
Application code: 06114
Open for exchange students: Yes
Block schedule: C

Module   Credit distribution   Examination dates
Sp1 Sp2 Sp3 Sp4 Summer course No Sp
0113 Written and oral assignments 3,5 c Grading: TH   3,5 c    
0213 Examination 4,0 c Grading: TH   4,0 c   28 Oct 2021 pm DIST   03 Jan 2022 am J,  Contact examiner

In programs

MPMOB MOBILITY ENGINEERING, MSC PROGR, Year 1 (compulsory elective)


Marco Dozza

  Go to Course Homepage


General entry requirements for Master's level (second cycle)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Specific entry requirements

English 6 (or by other approved means with the equivalent proficiency level)
Applicants enrolled in a programme at Chalmers where the course is included in the study programme are exempted from fulfilling the requirements above.

Course specific prerequisites

BSc in Engineering, i.e. Mathematics, Physics and Matlab programming
Vehicle and Traffic safety recommended


The objective of this course is to provide the students with insights on the design and evaluation of active safety systems both from an industrial and from an academic point of view. In this course, the focus will be on the current challenges and evaluation methodologies for the development of active safety systems. This course consists of four parts: safety-relevant events, active safety systems, human factors in active safety, and active safety evaluation.

Learning outcomes (after completion of the course the student should be able to)

- Explain the role of accidentology in the development of active safety systems
- Identify constrains and trade-offs for the selection of sensors for the design of active safety systems
- Analyze and apply basic algorithms for signal processing and threat assessment
- Explain the role of human factors in the design of active safety and automated vehicles
- Describe the rationale, architecture, and challenges in the development of cooperative safety systems
- Compare the tools that are currently available  for the evaluation of active safety systems
- Identify the challenges in the analysis of real-traffic data from field-operational-tests or naturalistic studies
- Explain the new safety challenges introduced by automated driving


Safety-relevant events
- Crash analysis and crash data
- Analysis of crashes and near-crashes from field data

Active safety applications
- Sensors for active safety
- Data processing and threat assessment
- Wireless applications (cooperative systems)
- Automated vehicles

Human factors
- Road-user behavior
- Driver modeling

Active safety evaluation
- Driving simulators
- Naturalistic evaluation (e.g. field operational test)
- Counterfactual analysis and evaluation in virtual environments


- Lectures
- Short applied exercises
- Laboratory exercise
- Visits to automotive industries and traffic-research institutes


Handouts from the lectures, journal papers, datasheets, and data dictionaries.

Examination including compulsory elements

- Exam, 4 p, graded
- Laboratory exercise, 3.5p, graded

The course examiner may assess individual students in other ways than what is stated above if there are special reasons for doing so, for example if a student has a decision from Chalmers on educational support due to disability.

Page manager Published: Thu 04 Feb 2021.