Comparison of reactive algorithms for

controlling of variable speed limits

Ellen Grumert

Andreas Tapani

Transport Forum, Linköping

January 8-9, 2014

Variable speed limit system

• VSLS (Variable Speed Limit System)

• Connected variable speed limit signs

• Detectors, measuring the conditions on the road such as flow and/or mean

speed

• Decision algorithm based on flow or mean speed or both

Source: Foto taken 2010 by Holger Ellgaard, publiced at www.wikipedia.org (accessed 2011-04-13)

Source: Description of MTM, Automatic Incident Detection in the Motorway Control System MTM, March 1999

Problem to investigate

• Many of the algorithms in use in real systems are based on

simple control strategies

• May not necessary reflect the flow on the road accurately

• Many of the proposed control strategies in literature have

problems with

• Computational complexity

• Uncertainty in robustness

• Tuning difficulties of parameters – many parameters or

interpretation issues

• High data demand

1 Mainstream Traffic Flow Control (Carlson et. al. 2011)

• Aim:

• Maximize throughput at potential

bottlenecks

• Avoid congestion

• Avoid capacity drop

• How?

• Find critical density (or occupancy)

(corresponding to the maximum throughput)

• Control the inflow by lowering the speed limits

- Idea

Source: Carlson et. al. (2011)

• VSLS functionality is dependent of:

• Finding critical occupancy

• Finding suitable acceleration area

• Finding suitable application area

- Algorithm design

VSLS application area Acceleration area

1 Mainstream Traffic Flow Control (Carlson et. al. 2011)

2 Specialist (SPEed Controlling AlgorIthm using

Shockwave Theory) (Hegyi et. al. 2008, 2010)

• Based on shockwave resolution

• Tuning parameters have physical interpretation

𝒒 < 𝒒𝒄

• Idea:

• Identify the traffic states – Detect chock waves

• Predict their future evolution

• Resolve the shockwave with suitable speed limits

• Lowering speed+same density lower flow

Source: Hegyi, A. and Hoogendoorn, S.P., Dynamic speed limit control to resolve shock waves on freeways – Field test results of the SPECIALIST algorithm

2 Specialist (SPEed Controlling AlgorIthm using

Shockwave Theory) (Hegyi et. al. 2008, 2010)

3 Reducing crash potential (Lee et. al. 2003, 2006)

• Log-linear model (analouge to linear regression)

• Crash potential = crash rate

• Crash potential based on crash precursors and external

control factors

• Thresholds for lowering the speed based on crash potential

• Model calibration

• Actual crash and traffic data collected from a 10-km stretch of the

Gardiner Expressway in Toronto, Canada

• 13-month period from January 1998 to January 1999

• 234 crash cases and 234 non-crash cases.

• Crash precursors:

• Temporal variation of speed: standard deviation of speed divided by

average speed (over all lanes)

• Spatial variation of speed: difference in speed between upstream

and downstream locations

• Lane changing behavior: covariance of volume difference between

upstream and downstream locations on adjacent lanes

• External factors

• Road geometry

• Peak- or off-peak pattern

3 Reducing crash potential (Lee et. al. 2003, 2006)

Microscopic traffic simulation

• How to model congestion?

• On-ramp

• Lanedrop

• Lowering speed on one section or for a few vehicles for some time

• Potential problems

• Models vs. reality

• Calibration – data

• How realistic is each senario?

- Modeling approach

Detector area

150m

Microscopic traffic simulation

• Choice: Lanedrop

• Realistic flow levels

• Modelling of capacity drop reflects reality (based on empirical

studies from litterature)

For VSLS modelling approach 1 and 2: Find critical occupancy!

- Base case modelled in SUMO

Preliminary results – Mainstream Traffic Flow

Control

Conclusions

• Careful consideration needs to be taken regarding modelling

congestion when evaluating the algorithms.

− In SUMO a lanedrop seems to be most suitable to model congestion

• Preliminary results from Mainstream Traffic Flow Control (MTFC)

shows:

− Improved results with respect to congestion (comparing basecase with MTFC).

− Higher mean speed for MTFC compared to basecase.

• Further work:

− Investigation of two more algorithms and comparisons between the three.

• Expecations

− Different algorithms might have different advantages

− The different algorithms might be more beneficial in some specific situations

(not necessary the same)