20120315 impact of weather on driver behavior-yang

Impact of Weather on Driver Behavior & Travel Demand:

FHWA’s Activities

March 15, 2012

C. Y. David Yang, Ph.D.Office of Operations R&D

Roemer M. Alfelor, Ph.D.Office of Operations

,

Impacts of Weather on Transportation

o Safety• 1.5 million weather-related crashes/year resulting

in more than 7 000 fatalitiesin more than 7,000 fatalitieso Mobility

• 25% of non-recurring delays on freeways is weather-related

o Productivity• Weather affects 1/3 of the national GDP

o Environment• Chemical anti-icing & deicing account for roughly

1/3 of expenditures for snow & ice control

FHWA Peer Exchange Meeting on Transportation Systems Management during Inclement Weather

Presentation 05 1 Buffalo, NY | March 15, 2012

FHWA’s Road Weather Management Program

Goalso Better understand the impacts of weather

(e.g., snow, rain, fog, wind, etc.) on traffic flow and operations

o Develop, promote, and implement strategies & tools to mitigate those impacts Weather g pResponsive Traffic Management (WRTM)

WRTM Success Measures

o Agencies use current and forecast weather-traffic conditions to manage traffic flow and ghighway operations

o Motorists receive and respond to road weather and traffic information

o Weather impacts incorporated in traffic o eat e pacts co po ated t a canalysis models



Safety, Mobility and Performance

Evaluation

WRTM Framework

Behavioral/Human Factors Analysis

Traffic and Weather Data Collection and

Integration

WRTM STRATEGIES

AdvisoryControl

Treatment

Evaluation

Traffic Analysis and Modeling

Types of Traffic Analysis & Modeling

o Macroscopic• Analysis of flow, speed, and density on a

segment-by-segment basiso Mesoscopic

• Dynamic analysis of individual vehicles based on average segment speeds

o Microscopic • Individual movement of vehicles on the

transportation network



Macroscopic Analysis of Weather & Traffic (2004-2006)

o Traffic data• Speed, Volume, Density

o Weather data• Rain, Snow, Visibility

o Collection devices• Loop detectors • Weather Stations

o Analysis SitesASOS/AWOSRWIS

NEXRADLoop

Detector

o Analysis Sites• Minneapolis, Seattle, Baltimore

o Traffic Model• Free Flow Speed• Speed at Capacity• Capacity

0

20

40

60

80

100

120

0 500 1000 1500 2000 2500Flow (veh/h/lane)

Spee

d (k

m/h

)

Macroscopic Analysis of Weather & Traffic (cont.)

Traffic Parameter Weather Condition Range of Impact

Free-Flow Speed • Light Rain (<0.01 cm/h) - 2 % to - 3.6%• Rain (~1.6 cm/h)• Light snow (<0.01 cm/h)• Snow (~0.3 cm/h)

- 6% to - 9%- 5% to - 16%- 5% to - 19%

Speed at Capacity • Light Rain (<0.01 cm/h)• Rain (~1.6 cm/h)• Light snow (<0.01 cm/h)• Snow (~0 3 cm/h)

- 8% to - 10%- 8% to - 14%- 5% to - 16%- 5% to - 19%Snow ( 0.3 cm/h) - 5% to - 19%

Capacity • Light Rain (<0.01 cm/h) & Rain (~1.6 cm/h)

• Light snow (<0.01 cm/h)

- 10% to - 11%

- 12% to - 20%



Macroscopic Analysis of Weather & Traffic (cont.)

o Snow has more impact on free-flow speed and capacity than rain

o Low visibility with snow has higher impact on free-flow speed and capacity compared to low visibility with rain

o Snow causes more variable traffic flow than dry and rainy conditionsPrecipitation impacts in Minneapolis iso Precipitation impacts in Minneapolis is greater than Baltimore

Reference: Empirical Studies on Traffic Flow in Inclement Weather (October 2006), Publication No. FHWA-HOP-07-073.

o Car following • Acceleration, deceleration, headways,

Microscopic Analysis of Weather & Traffic (2007-2011)

Acceleration, deceleration, headways, perception reaction time

• Developed models, calibrated for arterialso Gap acceptance

• Intersections, ramps• Developed models for intersection

o Lane changing • Theoretical models exist, no data for

calibration



Car-Following Analysis

o Quantify impact of icy roadway surface conditions on car-following behavior gusing controlled field data (Japan)

o Factors affecting driver car-following behavior• Roadway surface condition

Pl t iti• Platoon positiono Studied typical variability in driver

behavior

Effect of Roadway Surface Conditions: Dry vs. Icy

0.2

0.25(a) Capacity

DryIcy 0.6

0.8(b) Jam Density

0.3

0.4(c) Speed at Capacity

0 1000 2000 30000

0.05

0.1

0.15

Capacity (veh/hr)

Pro

porti

on

170 180 190 2000

0.2

0.4

Jam Density (veh/km)

Pro

porti

on

20 30 40 50 600

0.1

0.2

Speed at Capacity (km/h)

Pro

porti

on

0 2

0.25(d) Freeflow Speed

0 2

0.25(e) Reaction Time

40 60 80 100 1200

0.05

0.1

0.15

0.2

Freeflow Speed (km/h)

Pro

porti

on

0 2 4 60

0.05

0.1

0.15

0.2

Perception-Reaction Time (s)

Pro

porti

on



Car-Following Analysis Findings

o Impacts of icy roadway conditions • Mean free-flow speed 28%• Speed-at-capacity 13%• Speed-at-capacity 13%• Capacity 46%• Perception reaction time 13%

o Maximum differences between dry & icy• Volume: 1000 vphl• Speed: 15 mph

Reference: Microscopic Analysis of Traffic Flow in Inclement Weather – Part 2 (December 2010), Publication No. FHWA-JPO-11-020.

Gap Acceptance Analysis



Gap Acceptance – Data Collection Site

Quadrant 1 Quadrant 2

Quadrant 3 Quadrant 4

Traffic Simulation SoftwareWeather Parameters

VISSIM INTEGRATION CORSIM

Car Following Driving Behavior Parameter Sets

Link characteristics

Car following sensitivity factorsParameter Sets

• Wiedemann 74/99 parameters

characteristics • Free-flow speed, speed-at-capacity, and saturation flow

sensitivity factorsVariation of free flow speed

Acceleration “Base Data” • “Maximum acceleration”

“Max_acc.dat” file • Rolling/friction coefficients

Acceleration Lag

Deceleration “Base Data” “M i

“Max_acc.dat” file C ffi i t f

Deceleration Lag• “Maximum deceleration”

• Coefficient of friction

Gap Acceptance “Priority Rules” and “Conflict Areas”

Link characteristics • Critical gap

Acceptable gaps for turning vehicles

Reference: Zohdy, I., Rakha, H. A., Alfelor, R., Yang, C. Y. D., and Krechmer, D. (2011). Impact of Inclement Weather on Left-Turn Gap Acceptance Behavior of Drivers. Transportation Research Record: Journal of the Transportation Research Board, 2257, 51-61..



Findings

o Weather affects traffic flows at the microscopic & macroscopic levelsp

o Existing traffic simulation models and software can be modified to account for weather conditions

o Traffic & weather data exist to conduct analyses and develop weather-sensitive traffic a a yses a d de e op eat e se s t e t a cmodels

o Need more data, analyses, research to validate existing models

Traffic Estimation and Prediction System (TrEPS)

Reference: Incorporating Weather Impacts in Traffic Estimation and Prediction Systems (September 2009), Publication No. FHWA-JPO-09-065.



Incorporating Weather Impact in DYNASMART-X

o Objectives• Assessing the

impacts of adverseimpacts of adverse weather on networks

• Evaluating effectiveness of weather-related advisory/control strategies in alleviating traffic congestion due to adverse weather conditions

Snapshot of DYNASMART-X GUI

Current traffic conditions

Prediction (no intervention)

Prediction (with intervention)



Phase 2 of TrEPS Project

o Calibrate and validate weather sensiti e TrEPSsensitive TrEPS models using data (weather & traffic) from 3 Cities• Salt Lake City, UT• Long Island, NY• Chicago, IL

Phase 2 of TrEPS Project (cont.)o Implement and evaluate weather responsive

traffic management strategies using TrEPS Models



Phase 2 of TrEPS Project (cont.)

Implementation …

o Identify weather conditionsconditions

o Retrieve available WRTM strategies

o Simulate the effect of various scenarios using TrEPS

ho Integrate the knowledge from simulation outputs into deployment decision making

Phase 2 of TrEPS Project (cont.)Evaluation …

o Extract various performance pmeasures from resulting traffic states

o Evaluate benefits of WRTM strategies

o Update or modifyo Update or modify strategies



Contact Information

David [email protected](202) 93 328(202) 493-3284FHWA’s Office of Operations R&D (Turner-Fairbank Highway Research Center)

Roemer [email protected](202) 366-9242FHWA’s Office of Operations



20120315 impact of weather on driver behavior-yang

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