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Special subject Travel Time Variability & Modeling Road Traffic

Travel Time Variability & Modeling Road Traffic

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Page 1: Travel Time Variability & Modeling Road Traffic

Special subject

Travel Time Variability & Modeling Road Traffic

Page 2: Travel Time Variability & Modeling Road Traffic

Travel Time Variability

Page 3: Travel Time Variability & Modeling Road Traffic

Introduction

•  What is Travel Time Variability? – TTV is an indicator of the variability of

travel time from an origin to destination in the transportation network (including any model transfer or en-route stops).

Page 4: Travel Time Variability & Modeling Road Traffic

Introduction

•  Objective –  Investigate the measurement of travel

time variability and reliability with floating car data (FCD).

– We will consider that VTT is mobility performance metrics.

Page 5: Travel Time Variability & Modeling Road Traffic

Statistical Indices

•  Indicator: – Mean Travel Time (MTT) – Standard Deviation of Travel Time

(SDTT) – The 95th Percentile Travel Time (95th

PTT) – Buffer Index (BI) – Planning Time Index (PTI)

Page 6: Travel Time Variability & Modeling Road Traffic

Statistical Indices

•  Mean Travel Time: –  is equal to the sum of the travel times

collected by a number of floating cars (n), traveling on link “l”.

Tl =1n

tlii=1

n

Tl

Page 7: Travel Time Variability & Modeling Road Traffic

Statistical Indices

•  Standard Deviation of Travel Time –  Is the measure of the dispersion of travel

times which can formulated as follows:

σ l =(tli −Tl )

2

i=1

n

∑n−1

Page 8: Travel Time Variability & Modeling Road Traffic

Statistical Indices

•  The 95th Percentile Travel Time –  It measures the reliability of travel time,

which indicates the delay on a particular link.

– The 95th PTT is the travel time of which 95% of sample travel time are at or below this amount.

– The difference between the 95th PTT and MTT is called buffer time denoted as

TBl

Page 9: Travel Time Variability & Modeling Road Traffic

Statistical Indices •  Buffer Index

– BI is the extra time that a travelers should add to the MTT to ensure on-time or earlier arrivals.

– Other percentile: 85th, 90th, 99th

Bl =T95%l −Tl

Tl

"

#$

%

&'(100%)

Page 10: Travel Time Variability & Modeling Road Traffic

Statistical Indices

•  Planning Time Index – The planning time index compares the

longest travel time against a travel time incurred by free-flow traffic.

Pl =T95%lTFl

!

"#

$

%&(100%)

Page 11: Travel Time Variability & Modeling Road Traffic

•  Start with Delays: –  Travel times longer than a reference ”ideal”

travel time –  Something can be done to reduce these travel

times

Case study

Page 12: Travel Time Variability & Modeling Road Traffic

•  Travel Time: –  Freeflow Travel Time

Case study

Page 13: Travel Time Variability & Modeling Road Traffic

•  Travel Time: –  Freeflow Travel Time –  Delay:

•  Recurring Delay

Case study

Page 14: Travel Time Variability & Modeling Road Traffic

•  Travel Time: –  Freeflow Travel Time –  Delay:

•  Recurring Delay •  Non-Recurring Delay:

–  ”Normal” Delay

Case study

Page 15: Travel Time Variability & Modeling Road Traffic

•  Travel Time: –  Freeflow Travel Time –  Delay:

•  Recurring Delay •  Non-Recurring Delay:

–  ”Normal” Delay –  ”Abnormal” Delay

Case study

Page 16: Travel Time Variability & Modeling Road Traffic

Case study

Page 17: Travel Time Variability & Modeling Road Traffic

Case study

Page 18: Travel Time Variability & Modeling Road Traffic

Case study

Page 19: Travel Time Variability & Modeling Road Traffic

Case study

Page 20: Travel Time Variability & Modeling Road Traffic

Modeling Road Traffic

Page 21: Travel Time Variability & Modeling Road Traffic

Traffic Models

Traffic Flow Models

Level of Details Operationalisation

Micro Meso Macro Analytical Simulation

Page 22: Travel Time Variability & Modeling Road Traffic

Limitations of traffic simulations

•  Simulations are resource limited – Resolution: Level of detail – Fidelity: Degree of realism – System size: The network size to be

covered – Simulation speed: Speed of simulation

compared to real time – Resources: Computational resources,

programming time

Page 23: Travel Time Variability & Modeling Road Traffic

Road model definition

•  Microscopic models •  Mezoscopic models •  Macroscopic models

Page 24: Travel Time Variability & Modeling Road Traffic

Popularity

Type of Simulation Number of Packages

Microscopic 65

Mesoscopic 3

Macroscopic 16

Page 25: Travel Time Variability & Modeling Road Traffic

Microscopic models

•  Each vehicle consideration – system entities are objects with specific

decision-making – detailed entities interactions simulation

•  Advantages and disadvantages – difficult implementation and tune – most realistic

Page 26: Travel Time Variability & Modeling Road Traffic

Mesoscopic models

•  No specific vehicle consideration – vehicles making decision itself but like

pattern (no objects) –  interactions are on characteristic level

•  Advantages and disadvantages – better interactions tunning – attributes of vehicle not consider

Page 27: Travel Time Variability & Modeling Road Traffic

Macroscopic models

•  Vehicle flow consideration – vehicle distribution function –  flow equation

•  Advantages and disadvantages – microscopic details not included – Lot of calculations but fast – only for global traffic network

Page 28: Travel Time Variability & Modeling Road Traffic

Popular microsimulation models

Page 29: Travel Time Variability & Modeling Road Traffic
Page 30: Travel Time Variability & Modeling Road Traffic

Classification based on traffic conditions

Page 31: Travel Time Variability & Modeling Road Traffic

Objects modelled

Page 32: Travel Time Variability & Modeling Road Traffic

Modelling Techniques •  Weather conditions are modelled by the speed-acceleration

behaviour (changes in the driver behaviour parameters) or by the free flow speed of vehicles.

•  Parked vehicles are modelled by a particular destination node, side parking on links, temporary incidents or by a particular state of vehicle.

•  Commercial vehicles are modelled by parameters such as power, mass, length, privilege on certain lanes.

•  Pedestrians are taken into account when turning flows interact with pedestrian areas or in extending intersection all red periods to simulate walk periods.

Page 33: Travel Time Variability & Modeling Road Traffic

Modelling Techniques •  Incidents are modelled by lane closure signs, blocked lanes, "scheduled

vehicles" and slow vehicles.

•  Public transport, essentially buses, are modelled by vehicles with fixed routes.

•  Traffic calming measures are modelled by local speed limits, yield sign objects, Variable Message Signs and route guidance.

•  Queue spill back is modelled by space constraint in car-following and in link changing.

•  Weaving is modelled by forced lane changing, special lane changing behaviour, decision rules or lane changing logic.

•  Roundabouts are modelled by lane segments and yield sign objects.