PowerPoint Presentation

Can we make traffic jams obsolete?Lina KattanAssociate Professor in Civil EngineeringSchulich School of Engineering

December 20, 2016

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Lina KattanAssociate professor of civil engineeringUrban Alliance professor in transportation systems optimization engineeringPhD from the University of TorontoResearch focused on the application of emerging technology to improve the transportation systemPublished in a variety of leading transportation journals and national and international conferences proceedings

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Presentation outline3Transportation systems and their functions

Interaction between the demand for travel and the transportation system

What causes congestion?

Solution strategies long term to shorter term solutions

Variable speed limits under connected/ autonomous vehicle environments

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Transportation systems and their functionsTransportation systems are a major component of the society and economy

Transportation systems move us from where we are to where we are going; connecting us to our institutions, our families, our lives

Transportation systems consist of complex interdependent systems/subsystems (road, rail, bus, freight, bike networks, etc.)

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Todays challengesToday more than 54% of the worlds population lives in cities

Canadas population is largely urban - more than 80% of Canadians live in cities

Increased urbanization results in increased pressure on our transportation systems:growing challenges of providing safe and efficient access to goods, services and opportunities

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Traffic congestion

Why congestion? 7

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Why congestion? Time of DayTraffic

Transport DemandTransport Capacity Morning Rush Hours Afternoon Rush Hours

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Solutions to traffic congestion:expanding the physical infrastructure

Not a sustainable long term solution to traffic congestion!

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Long- and short-term solutions

Now I am going to talk about some long and short tem solutions10

Source: http://www.busandcoach.travel

Congestion mainly caused by commuters in single-occupant vehicles11

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Expanding the infrastructure for sustainable travel modes (e.g. investment in transit, pedestrian and cycling related infrastructure)Land useimprovement

(e.g. smart growth and compact communities and transit and pedestrian oriented development)Solutions to traffic congestion:land use and transit investment

Long-term solutions12

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Solutions to traffic congestion13

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Demand managementCongestion is caused mainly by commuters travelling in single-occupant vehicles during the peak periodThe key is managing the demand and distributing it over space (different routes), time and across modes (car pooling, transit, biking, walking etc.)

Time of DayTraffic

Transport DemandTransport Capacity Morning Rush Hours Afternoon Rush Hours

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Solutions to traffic congestion15

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Causes of traffic congestion

Source: Federal Highway Administration (http://www.fhwa.dot.gov/)16

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What is an Intelligent Transportation System (ITS)?

comprehensive sensor and communication systems

Intelligent control:Real-time collection and analysisAutomated deployment of actionsE.g.: adaptive signal control, transit priority, freeway control, multimodal real time travel information and guidance, incident and emergency management

More efficient use of existing capacity through Information and Communication Technologies: 17

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Emerging vehicle technologies:autonomous/connected vehicle/transitSource: US DOT

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Also Autonomous and connected vehicles are also part of Intelligent Transportation Systems

Automated vehicle come with various levels of automation with level 5 being the driverless cars . The real driver behind these technologies is to achieve greater safety by removing the possibility of human error, relying on advanced information, communication and sensing capabilities.

Connected Vehicles are vehicles that are capable to have two-way communication with the infrastructure and among themselves, disseminating information on individual vehicular speed, acceleration, position, etc..

As we will see this data can be vital to improve traffic flow and coordinating vehicle speed.18

The faster you get in the slower you get out!19Videosource: Doug MacDonald - Rice and Traffic Congestion

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Flow (veh/hr/direction)Density (veh/km/direction)Capacity can drop between 10% and 30%Seiran Heshami , Lina Kattan and Zhengyi Gong (2016). Macroscopic Traffic Flow Model Calibration and Stochastic Capacity Analysis Based on Weather Condition. To be presented in the Annual Transportation Research Board Meeting, Washington DC, January 2017.Traffic Breakdown Uncongested capacity Congested capacityConcept of capacity drop20

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Phantom jam21VideoSource: PTV Vissim: Motorway Shockwave

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Phantom jam22Video

Source: Andrew Marr / BBC / January 2011: The Phantom Traffic Jam.

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Freeway control and managementWhen everyone strives to get ahead of everyone else, we all fall behind! The price of anarchy: penalty we pay for not coordinating our action

How to coordinate our actions using emerging technologies?23

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Variable speed limits under connected/autonomous vehicles

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What are variable speed limits?Freeway speed limits are lowered whentraffic congestion increases at peak timesan accident occursadverse weather conditions

To ensure the freeway continues to move as smoothly as possible and ensure safety of travellers

Source: http://www.itv.com/news/central/topic/m42-motorway/25

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Advantages of variable speed limitsServing more vehicles

Less disturbance smoother flow

We are going to show that through computer simulation!26

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Evaluation tools: Microsimulation modelling

To create a realistic virtual replica of the network to be studied27

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R. Omrani and Lina Kattan: Simultaneous Calibration of Microscopic Traffic Simulation Model and Estimation of Origin/Destination (OD) Flows based on Genetic Algorithms in a High-Performance Computer. Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC 2013), The Hague, The Netherlands, October 6-9, 2013Calibration framework28Calibrate driver behaviour:Vehicle follows another carAggressivenessMerging and response timeRoute choiceResponse to information

Demand profile and loading levels

Route capacities and capacity drops

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Microsimulation calibration

R. Omrani and Lina Kattan: Simultaneous Calibration of Microscopic Traffic Simulation Model and Estimation of Origin/Destination (OD) Flows based on Genetic Algorithms in a High-Performance Computer. Proceedings of the 16th International IEEE Annual Conference on Intelligent Transportation Systems (ITSC 2013), The Hague, The Netherlands, October 6-9, 201329After calibration

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Study area in Calgary

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Freeway control using variable speed limit

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Source: http://www.continental-corporation.com/Source : Lina Kattan, Bidoura Khondakera, Olesya Derushkinaa, and Eswar Poosarlab (2014): Probe-Based Variable Speed Limit System - A Sensitivity Analysis. Journal of Intelligent Transportation Systems Technology, Planning, and Operations, Vol. 19, Iss 4.

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Traffic flow distributionAM traffic heading south from Deerfoot

Current fixed speed limit system Variable Speed limit systemSource : Lina Kattan, Bidoura Khondakera, Olesya Derushkinaa, and Eswar Poosarlab (2014): Probe-Based Variable Speed Limit System - A Sensitivity Analysis. Journal of Intelligent Transportation Systems Technology, Planning, and Operations, Volume 19, 2015 Issue 4. 32

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Anticipatory lane changing8 km1 km1 km1 km1 km1 km1 km1 km1 kmDefault Speed Limit = 100 km/hrVSL1VSL2VSL4VSL3VSL5VSL6Location of incidentBidoura Khondaker and Kattan (2015). Variable Speed Limit: A Microscopic Analysis in a Connected Vehicle Environment. in Transportation Research- Part C: Emerging Technologies, Volume 58, Part A, Pages 146159 33

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Connected vehicle performance results

Bidoura Khondaker and Kattan (2015). Variable Speed Limit: A Microscopic Analysis in a Connected Vehicle Environment. in Transportation Research- Part C: Emerging Technologies, Volume 58, Part A, Pages 146159

34No variable speedVariable speed

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Impact of congestion and % penetration of a connected vehicle

Bidoura Khondaker and Kattan (2015). Variable Speed Limit: A Microscopic Analysis in a Connected Vehicle Environment. in Transportation Research- Part C: Emerging Technologies, Volume 58, Part A, Pages 146159 35Current fixed speed limit system Variable Speed limit system120

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Speed in Km/hr120

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Speed in Km/hr

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Impact of % market penetration 36

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Key findings

Variable speed limits can provide safer and more efficient commute

If we coordinate the way we drive (e.g. slow down, change lanes less) we reach our destination faster!

Safety and travel time improvements are expected at higher % market penetration rates of connected/autonomous vehicles

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Summary

More roads do not necessarily mean better traffic

Long-term solutionsCompact and diverse communities with more transportation choices

Solutions that focus on the demand We are all traffic We all need to cooperate to make traffic congestion obsolete

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Summary

Municipalities and governmentDemand management strategies tolling, parking management, car pooling/sharing, etc.

Companies in downtownOffer employees transit passes instead of parking passesMore flexible work schedule and the option of working from home

Commuters Take transit, bike, walk or carpool and avoid rush hour traffic as much as possible

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Initialization (sets of dynamic ODs and supply parameters)

Simulator(PARAMICS)

Evaluation (Z)

Network (synthetic, large-scale)

GA Operators (simple/advanced)

Observed Data (count, speed)