PhD research on evacuation optimization (Huibregtse)

Masterclass T&P/TIL, 29-9-2011

Challenge the future

DelftUniversity ofTechnology

PhD research & reporting tips

Olga Huibregtse

2PhD research & reporting tips | 10

PhD Project

• Typical for evacuations:• Demand• Behavior• High congestion level

• Measures• Demand: departure time instructions, etc.• Supply: reversing lanes, etc.

• Uncertainty:• The impact of the hazard• The behavior of the people• Etc.

Robust optimization of evacuation measures


Part of the PhD project

• Method to optimize route instructions considering uncertainty and compliance behavior

• Computationally heavy when considering uncertainty and behavior

• Can we develop a more efficient method?

• Research is carried out together with:• Gunnar Flötteröd & Michel Bierlaire (EPFL)• Andreas Hegyi & Serge Hoogendoorn (TU Delft)

That I will present today


Optimization of route guidance

• Discussion: System-optimal (SO) or user-equilibrium (UE)• SO: unrealistic, results in non-compliance• UE: low effectiveness from system point of view• Importance of system optimality and behavior of people

• Considering route choice behavior:• usual approach: modeled on node level (compliance rate)• In reality, route decision depends on total trip, thus behavior should be

considered on route level but this is computationally expensive

State-of-the-art


Considering behavior on route level

• High number of routes, thus high number of decision variables

• An efficient method is needed to solve the problem

Relatively complex problem

• 3X3 square:• 16 turning fractions• 6 routes

• 10X10 square:• 324 turning fractions• 48,620 routes


Efficient approach

• Optimization of route guidance, constrained by:• Traffic flow simulation model• Behavior model describing route choice

• Fixed-Point Approach: decomposing the problem into simpler problems which are iteratively solved

To optimize route guidance


Fixed-point approachSub-problems and their simplifications

Sub-problems Decision variable: route advice

Constraint: traffic flow model

Constraint:behavioural model

1. Optimization of turning fractions

Turning fractions Full compliance

2. Optimizationof route advice

Fixed time-dependent link travel times

3. Approximation of behaviour: adapting bounds on turning fractions


Case study

• 120,000 residents• 6 hours to evacuate

• Route choice model• Traffic flow model • Optimization method

• Undecomposed approach• Fixed-Point Approach

Hypothetical flood of Walcheren


ResultsThe FPA is substantially faster, while maintaining the quality of the solution

0 50 100 150 200 250 300

1

2

3

Computational time (hours)

Test

Fixed-Point ApproachUndecomposed Approach

Performance: -0.05%

Performance: +4.92%

Performance: -0.30%


And finally

• Tips in general:• Follow the usual setup from introduction to conclusions• Think about the motivation• Compact• Audience• Etc.

• How my writing skills improved over the years:• Practice• Reviewing other papers

Tip: carefully read reports or papers from other people

Some reporting tips

PhD research on evacuation optimization (Huibregtse)

Education

Transcript of PhD research on evacuation optimization (Huibregtse)