# Presentation: 206889

## Traffic Impacts of Short Term Interstate Work Zone Lane Closures:  The South Carolina Experience

- Wayne Sarasua, Ph.D., P.E.
- sarasua@clemson.edu

## Overall Goals

- Develop a means to determine an actual volume of vehicles per hour per lane to be used to determine when lane closures may be permitted.
- Develop a means to estimate speeds, delays, and queue lengths due to short-term lane closures in work zones

## Overall Goals (Cont’d)

- Analyze the effects of roadway grades, truck percentages, and lane widths on work zone traffic characteristics when lane closures are present

## Research Participants

- Clemson University
- Wayne Sarasua
- David Clarke
- Several GRAs
- The Citadel
- William J. Davis

## Knowledge Acquisition and Literature Review

- Strategy sessions
- Comprehensive Literature Review
- Survey of State DOTs

## Classical Traffic flow Theory

## Capacity Measurement

- Maximum rate of flow (HCM)
- Mean queue discharge rate
- Hourly rate of flow under congested conditions
- Flow rate at which traffic changes from uncongested to queued conditions

## Traffic Measurement Techniques

- Traffic Volume/Headway
- Video surveillance
- Inductive loops with counters
- Road tubes with counters
- Inductive counters
- Speed measurement
- Road tubes
- Radar or Laser

## Factors Influencing Freeway Work Zone Capacity

- Work zone configuration
- Highway grade
- Presence of freeway ramps
- Traffic stream make-up
- Weather conditions
- Intensity/duration of construction activities
- Lighting

## Volume Thresholds

## Instrumentation and Field Data Collection

- Design the surveillance setup, acquire hardware, and implement design
- Field test and make adjustments
- Field test at an actual interstate work zone
- Collect data at various rural and urban work zone sites

## Wind Research Tower

##  Surveillance Setup

- Tall tripods from SkyEye  Corporation

## Roadside Setup

## Base of Tripod

## Connecting Cables

## Autoscope camera and pan/tilt unit

## Raising the tripod

## Tie-down and Ground Anchor

## Raised Tripod

## Tripod Setup on a Bridge

## Great Perspective View

## Peripherals

## Surveillance Setup Summary

- Tripods are of adequate (not optimal) height
- Stable, even in windy conditions.
- Very flexible
- Enhanced safety
- Little or no effect on traffic operations
- Need about an hour to setup completely
- Breakdown takes about 1/2 hour

## Projects

- Collected data at 22 locations
- First data collection on 9/12/01
- Summary:
- I-85:  13 Projects
- I-26:  6 Projects
- I-77:  1 Project
- I-385:  2 Projects

## Data Collection Findings

- Night time data collection not ideal
- Autoscope not as effective
- Volumes generally low except I-85
- Difficult to obtain specific information on location of closure in advance
- Setup and procedures adequate for providing data to meet project objectives

## Data Analysis

- Graph and analyze data
- Develop predictive model as a function of known model parameters
- Traffic and truck volumes
- Length of lane closure
- Lane widths
- Shoulder characteristics
- Roadway grades

## Underlying Concepts

*	**	**k=q/s  **	**	**	**	**(1)*
- where:
*	**k = *density (veh/mi*)*
*	**q = *flow (veh/hr*)*
*	**s = *speed.(mph)
- Can also be expressed in terms of average vehicle spacing:
- 		*k=5280/spacing  **	**	**(2)*

## An Example of Capacity

- _Given_:
- Speed limit for short term work zone projects in South Carolina is 45 mph.
- Average spacing in saturated conditions for a speed of 45 mph is 150 feet per vehicle.
- Using eq. 2, *k * =  5280/*spacing * =  35.2 veh/mi.
- From eq. 1, *q = ks* = 35.1 * 45 = 1584 veh/hr.

## More Examples

- From eq. 1, for flow to stay constant, the density of the road must increase in proportion to the decrease in speed.
- This indicates that at lower speeds, there is willingness for cars to travel at closer intervals.

## Combining Data to Facilitate Analysis

- No single project completely follows Greenshields’ generalized form
- Necessary to combine data
- Difficult to isolate the characteristics of individual projects
- Underlying assumption that all projects that were combined were homogeneous

## Project Characteristics

- Commonality:
- Rolling terrain except I-26 south of Columbia
- 12-foot lane widths
- Similar taper lengths
- Differences
- Type of maintenance activities
- Work zone length
- Number of lanes downstream

## Speed vs Flow  2 to 1-lane

- Discrete 5 minute flows

## Speed vs Flow  2 to 1-lane

- 12 consecutive 5 minute periods

## Considering Heavy Vehicles

- Research has shown that heavy vehicles have a significant effect on capacity
- Must be considered on a case by case basis
- Most common approach is applying passenger car equivalents (PCE)

## Methodology for Determining PCE

- Measured headways by analyzing video
- Used software developed for project (Satflo2) to record time and vehicle type
- Results are tabulated and graphed

## Headway Frequencies by Vehicle Type

## Slide 40

## Average PCEs Used in Analysis

## Speed vs Flow  2 to 1-lane

- Discrete 5 minute (PCE)

## Speed vs Flow  2 to 1-lane

- 12 consecutive 5 minute periods (PCE)

## Modeling Methodology

- Model Speed vs Density Relationship
- From the resulting linear model, substitute *k=q/s*
- Determine maximum Flow in PCE
- Adjust for other factors
- Formulate model for application to specific short-term work zones

## Speed vs Density  2 to 1-lane

- Discrete 5 minute (PCE)

## Speed vs Density  2 to 1-lane

- 12 consecutive 5 minute periods (PCE)

## Modeling Speed vs Flow

*s* = -0.395* k* + 52.54		(5-minute discrete data)
*s* = -0.493* k* + 54.11		(5-minute consecutive data)
*Substituting k=q/s  gives:*
*	**q*= -2.53 *s*2 + 133 *s**	** **	*(5-minute discrete data)
*	**q*= -2.03 *s*2 + 110.7 *s**	** **	*(5-minute consecutive data)
- 		where:		*q *= flow (pcphpl*)*
*	**	**	**s *= speed.(mph)

## Speed vs Flow  2 to 1-lane

- Discrete 5 minute (PCE)

## Speed vs Flow  2 to 1-lane

- 12 consecutive 5 minute periods (PCE)

## Estimating Capacity

- First derivative of the* s* vs *q* model is slope of the parabola
- d*q/*d*s *= -5.06 *s* + 133 *	**	*5-minute discrete data
- d*q/*d*s*= -4.06 *s* + 110.7 *	*5-minute consecutive data
- Slope of the parabola at maximum flow = 0.  Setting the above equations = 0 give the speeds at maximum flow.
- Substituting  into previous slide gives max flow (capacity):
- 	1748 pcphl		(5-minute discrete data)
- 	1483 pcphl		(5-minute consecutive data)

## Considering Grades

-  HCM considers grades in calculating PCEs
- We found little variation in PCEs
- Most projects had rolling terrain with moderate grades rarely extending more than a 1/2 mile
- We did do some stratification
- HCM individual grade sections applicable

## A Comparison of Stratified Data

## Considering Other Factors

- Work zone activity - used regression models with dummy variables.  Found no significance
- Ramps - ramp volumes at sites with nearby on-ramps were typically low
- Weather - adverse weather never experienced *during* data collection

## Formulating Final Model - fHV

- HCM heavy vehicle adjustment factor: 					       	      1
*f**HV*  = 		                                        *(3)*
- 		1*+*[*P**T*(*E*T-1) + *P**RV*(*E*RV-1)]
- where:
- 	*P**T  * *  *=  proportion of trucks,
- 	*P**RV  * * *=  proportion of  RV’s and cars with trailers,
*	**E*T    =  PCEs for  trucks and buses, and
*	**E*RV  =  PCEs for  RV’s and cars with trailers.
- A first estimate of capacity (veh/hr/lane):
- 		C' = 1480 ** f**HV*.

## Accounting for Number Lanes

- Data indicates that using a simple factor based on the number of discharge lanes is appropriate.  The capacity estimate becomes:
- 			C''  =  1480 ** f**HV* * N
- where:
- 	C''  =  	C' adjusted based on the number of lanes open
- 	 	through the work zone (veh/hr), and
- 	N   =    number of lanes open through the work zone.

## Accounting for Work Zone Activity

- The HCM 2000 suggests adjusting base capacity up or down by 10% depending on whether or not the work zone activity is more or less than normal.   Thus, final form becomes:
- 	CWZ = (1480 + I) ** f**HV* * N		*(4)*
- where:
- 	CWZ =  is the estimated capacity of a short-term work
-  		zone (veh/hr),
- 	*f**HV  * =  heavy vehicle adjustment factor,
- 	  N  =  number of lanes open through the work zone, and

## Example

- Given: planned 2 to 1-lane typical short-term lane closure
- 	Peak volume of 1,100 veh/hour 18 % trucks, 2 % RVs
- Should the closure be moved to the evening?
- 1.  Calculate *f**HV*:*  *Using PCE table, the *E**T* and *E**RV* are 1.93
-      and 1.44 respectively.  Using equation 3,  *f**HV*  = 0.85.
- 2.  Calculate *C**WZ*:  Assuming *I *= 0 for a typical closure and
-      *N* = 1, using equation 4 yields *C**WZ** *= 1,258 veh/hr.
- 3.  Compare volume to capacity: the *V/C* ratio in this example
-      works out to be 0.87 based
- 	It is unlikely that the volume will reach capacity.

## Rate  of Queue Development

- 		 q2-q1
- sw = 			*(5)*
- 	 k2-k1
- where:
- 	*s**w* is the shock wave velocity (will be negative),
- 	*q**2* is the discharge flow,
- 	*q**1* demand flow (flow upstream of the work zone),
- 	*k**2* density of the flow of the moving queue, and
- 	*k**1* density of the flow before the queue.

## Queue Example

- Given: 2 to 1-lane short-term lane closure.  Before the closure, volume is 1,500 veh/hr and the density is approximately 25 veh/mi. Work zone causes the flow to reduce to 1,000 veh/hr and a queue density of 100 veh/mi. What would the queue length be from the bottleneck 5 minutes after the queue initially forms?
- Shock wave velocity = (1000-1500)/(100-25) = -6.7 mph.
- After 5 minutes:  -6.7mph * 5 min * 1hr/60 min = 0.56 miles.  At 100 veh/mi, this would equal 56 vehicles in the queue.

## Graphical Example

- Arrival Flow (1500 veh/hr)

- Queue Discharge Flow  (1000 veh/hr)

- Length of Queue at Time *t = *56 vehicles

*t = *5 minutes

- 0

- Number of
- Vehicles

- Time

## Queue/Delay Methodology

- If the volume is below capacity, no queue will form.
- If the volume exceeds capacity, two speeds are assumed:
- 	< 100 pcphpl over capacity, speed is 35 mph 	> 100 pcphpl over, speed drops to 15 mph
- The density for different speeds in PCEs/mile is given by:
- 		*k* = (*s*-54.1)/-0.493
- Thus, *k* = 80 PCEs per mile at a speed of 15 mph.  Because *q=k*s*, the discharge flow is 1200 pcphpl.  For a given work zone duration, length of the queue can be estimated in a similar fashion to the previous example.

## Conclusions

- Setup works well
- Not enough data for conclusive findings on effects of various factors
- Projects showed interesting traffic phenomena
- 800 vphpl equates to 1232 pcphpl in the absolute worst case 30 % trucks with a PCE of 2.8.  This is still more than 250 pcphpl less than the conservative base value (1480)