Project Details
23-839, TPF-5(438)
03/01/23
06/30/24
Iowa Department of Transportation
Smart Work Zone Deployment Initiative
Researchers
About the research
Improving the accuracy of work zone data is a multi-layered problem of which a number of agencies have been working to address over the last several years. Connected temporary traffic control devices (cTTCDs) such as smart arrow boards and other connected devices have the capabilities to improve the accuracy of work zone data without a contractor or agency employee having to manually enter the information. As the number and types of devices have increased, little guidance has been developed on how to use information from these devices within an agency. This project will document and evaluate how cTTCDs can be used by an agency for both historical and real-time applications. The approach starts with an agency state-of-the-practice review to summarize how the data are currently being utilized. A number of integration methods will be evaluated with the goal of highlighting noteworthy practices and documenting agency considerations when integrating the data into their systems.
Project Details
23-834, TPF-5(438)
03/01/23
02/29/24
Iowa Department of Transportation
Smart Work Zone Deployment Initiative
Researchers
About the research
Recent advances in data collection technologies have made it increasingly possible to monitor traffic conditions with increasing levels of detail, facilitating the task of providing advance warning of work zone conditions to the traveling public. Today, a variety of such technologies exist, including automated vehicle identification (e.g., Bluetooth), automatic vehicle location (AVL) (e.g., average segment speeds), and trajectory data from connected vehicles. Different data sources provide different types of information, have different latency, varying spatial and temporal resolutions, and different requirements for use. There is a need to gather and synthesize available information about the effectiveness and limitations of alternative data sources for the application of real-time work zone monitoring and communicating information to the public. The possibility of integrating multiple data sources for monitoring and public information uses also needs to be investigated.
Researchers
Peter Savolainen
Timothy Gates
Praveen Edara
Henry Brown
About the research
This study sought to identify best practices for setting work zone speed limits by state departments of transportation (DOTs) and to evaluate select strategies for improving compliance with work zone speed limits. This was achieved by synthesizing information from a literature review, a state DOT survey, and field evaluations of select speed management strategies.
The state DOT survey found that work zone speed limits are typically established based on the characteristics and conditions of the site, including permanent speed limit, facility type, worker presence, positive protection, work duration, and type and location of work activity.
Work zone speed limit reductions of 10 mph are most frequently utilized on high-speed facility types, with further reductions provided based on worker presence in the absence of positive protection. While the 10 mph speed limit reduction is often viewed as effective, the use of a 45 mph work zone speed limit when workers are present may require the use of additional speed reduction countermeasures to be effective.
Research studies have generally shown several types of work zone speed management strategies, such as speed display signs, law enforcement, variable (dynamic) speed limits, temporary rumble strips, and portable changeable message sign (PCMS) messages, to be effective in reducing vehicle speeds in work zones.
The work zone speed management strategies most frequently implemented by state DOTs include higher fines for speeding in work zones and lights on contractor or maintenance vehicles. While DOTs generally view law enforcement with an officer present as the most effective strategy for managing work zone speeds, they also perceive the availability of law enforcement as the greatest challenge to managing work zone speeds, followed by driver indifference and distracted drivers.
Based on the findings from the literature review and DOT survey, a field study was performed to assess the effectiveness of two work zone speed management strategies, which included a speed feedback trailer (SFT) and law enforcement. In general, the magnitude of the speed reduction effects were greatest in the general proximity of the SFT. Accordingly, positioning the SFT near the end of the taper led to lower speeds for a more sustained distance into the work zone compared to when the SFT was positioned near the start of the taper.
A second field evaluation assessed the effectiveness of a specialized work zone enforcement strategy that included a covert speed measurement vehicle positioned near the end of the work zone along with four police cars positioned just beyond the end of the work zone to stop speeding drivers. The visible presence of law enforcement activities at this location reduced work zone speeds by approximately 5 to 7 mph.
Researchers
Timothy Gates
Peter Savolainen
About the research
Work zones that include a single lane closure on a two-lane, two-way roadway present unique traffic control challenges. In these situations, traffic regulators (i.e., flaggers or temporary traffic signals) are often utilized to regulate traffic such that only a single direction utilizes the open travel lane at any time. Recently, an experimental traffic control treatment, referred to as the driveway assistance device (DAD), was developed to help drivers safely enter a one-lane, bi-directional work zone from a driveway or minor side street by using alternating left and right flashing arrows along with a steady red indication. As the DAD is a relatively new and under-researched treatment, much is still unknown about the optimal designs of the signal display and auxiliary signage to provide the highest comprehension and compliance.
To address these issues, research was performed to determine best practices related to the DAD design and to develop guidelines related to the use of DADs in one-lane, bi-directional work zones. First, a nationwide online survey of drivers was conducted to determine the DAD signal configurations and auxiliary sign messages that elicited the highest rates of compliance or most effectively communicated the proper driver action. The survey was supplemented by a field study performed in northern Michigan that evaluated the effects of five different auxiliary signs on driver compliance when utilized with a DAD. The conclusions and recommendations resulting from these efforts are summarized as follows. The auxiliary signs most effectively conveyed the proper driver action if the message included the word “Turn” as opposed to “Yield” and if a No Turn on Red Sign was included. Additional improvements were observed for signs that included a prominent “WAIT” message at the top of the sign. These findings were consistent between the survey and field study. Turning to the characteristics of the DAD signal indication, compared to yellow flashing arrows, red flashing arrows showed far fewer “Turn at any time” survey responses, although yellow flashing arrows showed considerably less uncertainty as to the proper action for drivers. Considering the DAD signal head configuration, the horizontal and doghouse configurations more effectively conveyed the proper driver action compared to the red-over-yellow arrows configuration in the driver survey. Based on the research findings, DADs are recommended for continued experimental use along with appropriate auxiliary signage at work zones that include one-lane, two-way traffic where it is not practical or feasible to provide a continuous flagger or temporary traffic signal operation.
Project Details
18-646
01/01/19
12/31/21
Smart Work Zone Deployment Initiative
Researchers
Carlos Sun
Praveen Edara
Yaw Adu-Gyamfi
About the research
It is anticipated that autonomous truck platooning could lead to many benefits, such as maximizing existing road capacity, decreasing fuel consumption through drafting, and reducing emissions. Despite the voluminous research on truck platooning, very little has been relevant to provide guidance to departments of transportation for operation in work zones.
This study is the first research project that examined truck platooning in work zones. A networked or federated simulator was used in which a vehicle driven by a human subject encountered a truck platoon with the lead truck driven by a human driver. The experiment involved 10 scenarios composed of differences in education, truck signage, and number of trucks in the platoon.
The results point to the importance of education as the post-education vehicle speeds increased between 8.6% and 12.9% across scenarios, and the distance headways decreased between 28.8% and 30%. The vehicles increased in efficiency while still staying under the work zone speed limit.
On the other hand, the use of truck signage changed driver behavior in an arguably undesirable way by increasing the percentage of platoon bypasses. As the post-simulator survey revealed, 94% of the subjects believed it was safer not to bypass the truck platoon and yet about 34% chose to do so.
This initial investigation into truck platooning near work zones is a beginning upon which further investigations on education, signage, and platoon size policies can continue.
Project Details
20-733
01/01/20
06/04/21
Smart Work Zone Deployment Initiative
Researchers
Natalia Ruiz-Juri
About the research
This project describes the implementation of machine learning (ML) models to the prediction of work-zone traffic impacts including local speed and traffic volume changes and corridor-level travel time increases. It also summarizes efforts to refine an existing tool that estimates work-zone-related delays and costs by providing consistent estimates of typical travel times that consider variations across days of the week and months of the year.
All of the models described in the report were estimated/trained and tested using data collected on I-35 through Austin, Texas, on a 20.4-mile section on which smart work-zone trailers (SWZTs) were placed. Predictive models combined SWZT point speed and volume data with INRIX segment-level speed data. The researchers implemented artificial neural networks (ANNs) to forecast speed and volume changes for planned closures.
Speed forecasting models performed well on average (root mean square error [RMSE] of 10.19 mph) but tended to underestimate speed reductions when the closures were significant. The latter was likely a result of having a small fraction of time steps exhibiting significant speed reductions in the dataset, which consisted mostly of nighttime closures.
Models used to forecast changes in traffic volumes had an average error (RMSE) of 57 vehicles per hour per lane (vphpl), which was comparable to that of linear regression models. Further training with a more balanced dataset that includes daytime and nighttime closures is required to support a broader set of applications.
The researchers also analyzed the performance of three short-term travel-time prediction (STTTP) methods, trained as part of a separate effort during work zones. The trained models, which included a time series approach and two types of ANNs, were very successful on average, outperforming traditional approaches by up to 50 percent during the peak period. While model performance was not as impressive for predicting travel times when work zones were present, preliminary results were promising with ML models consistently outperforming the traditional approaches.
Further model refinements to explicitly consider the presence of work zones and their characteristics are expected to improve model predictions. The efforts described in this project illustrate the potential value of emerging data sources and modeling techniques to support work-zone planning and management.
Researchers
John Shaw
jwshaw@iastate.edu email >Research Scientist, Public Science Collaborative
About the research
Highway work zones often have major safety and mobility impacts, which are made worse when travelers are unaware that they are approaching a work zone. To monitor and mitigate the mobility and safety impacts of road construction, transportation agencies, first responders, and the public require accurate information about the location, extent, and timing of construction-related closures.
This project reviewed various stakeholders’ current needs for pre-construction, real-time, and post-construction work zone information and compared these needs to the available work zone data sources and standards. The analysis identified a substantial mismatch between the roadway and lane closure data currently available and the data required to manage work zone traffic impacts effectively. To address this gap, the project developed a conceptual prototype for a tool that would facilitate self-reporting of closure details by contractors and maintenance crews.
Researchers
About the research
Rear-end crashes are one of the primary crash types in work zones and frequently occur at the back-of-queue (BOQ). Some agencies have utilized back-of-queue warning systems (QWSs), where real-time sensors are located upstream of stopped or slowed traffic, either to actually detect BOQs or monitor conditions to predict BOQ locations. QWSs then provide notifications of traffic conditions to drivers, which ideally lead to lower speeds and drivers being prepared to react to the BOQ, resulting in fewer crashes and conflicts. However, a driver needs to be properly monitoring the roadway environment to receive the warning and, then, needs to be prepared to take the appropriate actions when necessary. In many cases, drivers are distracted and fail to recognize warnings, or they receive the warning but fail to comply with appropriate speeds. As a result, one of the main needs to address BOQ situations is to understand what drivers are doing so that a QWS can get a driver’s attention. Additionally, driver behavior may indicate that other countermeasures, such as speed management, may be as effective as formal QWSs. The research described in this report aims to address this knowledge gap through the following objectives:
- Identify common types of QWSs
- Summarize QWSs used in Smart Work Zone Deployment Initiative (SWZDI) states
- Identify driver behaviors in BOQ scenarios
- Make recommendations
- Summarize needs for connected vehicle applications
Safety critical events (SCEs) were evaluated for back-of-queue situations using two different datasets. The first was a set of BOQ SCEs that were reduced from camera image captures at BOQ locations in work zones in Iowa during the 2019 construction season. Analysis of these data indicated speeding, following too closely, and forced merges were the primary characteristics associated with BOQ. The second dataset was an analysis of BOQ events in the second Strategic Highway Research Program (SHRP2) Naturalistic Driving Study (NDS). Analysis of these data indicated that following too closely and glances away from the roadway task of 1 or more seconds were statistically significant.
Researchers
John Shaw
jwshaw@iastate.edu email >Research Scientist, Public Science Collaborative
About the research
In the Work Zone Activity Data Logging Phase I project, state transportation agencies in the SWZDI states and beyond expressed a strong need for better information about the location, extent, and timing of lane closures. More than a dozen use cases for detailed lane closure data were identified and prioritized, such as helping first-responders avoid closures, providing more accurate public information about closure locations and timing, and more efficiently conducing post-construction work zone traffic management effectiveness reviews. Phase I affirmed that the vast majority of state DOTs currently lack the ability to track lane closures at the level of temporal and spatial detail required for these uses. Among the very few agencies that have the technical ability to record this information, the data lacks reliability. Closures on county and municipal routes were seldom, if ever, tracked.
Phase I showed that existing data sources are not sufficient to support the high-priority use cases. For example, although underperforming work zones sometimes show up in traffic management center (TMC) delay data, it is difficult to distinguish work zone delays from delays caused by traffic crashes. Since the exact closure location, timing, and extent are seldom recorded, even agencies with lane closure permitting systems are experiencing great difficulty relating work zone performance to closure characteristics. Moreover, TMC databases provide almost no information about well-performing work zones, making it extraordinarily difficult to pinpoint factors of success.
To address these needs, the Phase I project gathered information about existing work zone data sources, identified relevant standards, and developed a series of sketches that lay out a vision for an easy-to-use lane closure data collection application or website. The goal of this project is to transform these conceptual sketches into a working prototype that generates data in a format that could eventually be integrated with TMC data and other existing data sources to provide a more complete picture of work zone performance.
Researchers
Madhav Chitturi
About the research
Back-of-queue crashes are a significant safety hazard in highway work zones—especially those with intermittent congestion. A number of intelligent transportation systems (ITS) have been developed to provide queue warning, but historically the cost and complexity of these systems have limited their use.
The objective of this project was to design a low-cost queue warning system (QWS) to reduce costs, simplify deployment, and test in the field. The developed low-cost QWS could allow back-of-queue warning signs to be installed wherever queuing is anticipated (even for short-term projects). Modular design of the low-cost QWS will allow the system to be extended as far upstream as necessary to provide ample driver notification in high-, medium-, and low-demand situations.
The sign support system for a low-cost QWS went through several iterations of design in order to find a design that has been crash tested and approved to the Manual for Assessing Safety Hardware (MASH) standards. The final design of the sign support system is based on a non-proprietary support system crash tested by the Texas A&M Transportation Institute. The proposed sign support design for the low-cost QWS has not been able to be field tested for several reasons. The most notable reason is highway agencies are strongly encouraged for safety and liability reasons to only use hardware systems that have successfully completed crash-testing protocols in accordance to the safety standards in the MASH. To date, only a select few sign support systems have been crash tested to MASH criteria, and none with the type of low-cost QWS hardware required for this prototype.
The second reason was the inability to find field test sites on conventional two-lane highways with 55 mph speed limits and the requirement that the equipment be located outside of a clear zone or shielded by protective barriers. Expressway and freeway facilities can’t be used for testing for this design because the Manual on Uniform Traffic Control Devices for Streets and Highways (MUTCD) requires larger size signs and font letter sizes for the message required on these types of facilities. Therefore, before field testing can be undertaken on highways open to traffic, an investment in funding for crash testing is strongly recommended.