Safety evaluation at level crossings with the help of an automated - - PDF document

Safety evaluation at level crossings with the help of an automated measurement technique

Accidents at level crossings

General

• Funded by FFG and ÖBB
• In co-operation with Fraunhofer

IVI, Dresden

• Main goal:

– to establish automated measurement technique to evaluate the effects of traffic safety measures at railway crossings

What we already know

• Accidents at level crossings:

– seldom, but when they happen, then they are serious

• Involvement:

– often those are involved who are living nearby

• Reasons of accidents:

– „I know the schedule“ - „I know no train will come at that time“ – „I can still make it“ e.g. the red light is anyway activated too early

• What is needed:

– Reminder of the level crossing (traffic signs and rumble strips are not working so well, speed humps better)

What is a speed hump doing?

• Speeds are reduced – in our case to 10km/h
• With less speed the visual field is getting

broader one is seeing more at the periphery

• One is getting more aware of the signal and

approaching trains can be seen better

• Even if the line of sight is disturbed one

has more time to react

Study design

• Observations (original plan) before and after:

–9 days before (end of May) Implementation of speed hump –7 days immediately after –7 days in September –7 days in spring 2018

• Evaluation method:

–Video camera –Infrared camera

How do the cameras work

• Video camera

– wave lengths in the visible range for humans – records reflections of light from a light source on objects

• Infrared camera:

– working with longer wave length (between infrared and microwaves) – records the heat infrared radiation)

• f objects (no

light source needed)

LH10

Infrared camera

• Disadvantages:

– Measurement through glass (e.g. windscreen) is not possible – Other details e.g. registration plates can not be recorded

• Advantages

– Less problems with data protection – Possible to measure 24h

Installation

Kamera 1 Kamera 2

• Variables:

– Type of vehicle – Speeds and braking behaviour – Positions of road users – Looking behaviour – Red light violations – Trains – Conflicts

• Hypothesis (with and without speed hump)

– Speeds will be reduced – Less often driving against red – Better looking behaviour

Variables & Hypothesis

Folie 7 LH10 records the heat (infrared radiation) of objects (no light source needed)

Lukas Hartwig; 05.10.2017

Evaluation video camera

• Based on evaluation sheet

– Time – Type of vehicle – Speed – Braking behaviour – Looking behaviour – Red light violations – Trains – Conflicts

• Two level segmentation

– background: quick segmentation between objects – optical flow: high computing time, estimation of speed and direction

• Combination of both
• Calculated trajectories can be aggregated into

diagrams etc. for:

– Speeds – Braking behaviour – Position of the road user

Evaluation infrared camera Preliminary results – infrared camera Preliminary results – video observation

Sample Size Group Size

Preliminary results – video observation

Driving against red Reduction of speed before the level crossing Speed before the level crossing

Preliminary results – video observation

Looking in at least one direction Without 69,8% not recognisable With 68% not recognisable

Summary

• Method is working

– Speed, position can be evaluated very well – Some problems with evaluation of the looking behaviour

• Speed hump is working

– Speeds are reduced – Less groups no following effect – Based on P2W looking behaviour is better

• „Problems“

– Maintaining the system – Lots of data from both cameras

Next steps

• Finishing the data evaluation
• 3rd observation finished in

September base line comparison

• Introduction of 20 km/h speed limit
• 4th observation

Thank you!! Questions????