New Insights into Freeway Capacity at Work Zones: Empirical Case Study

2000 ◽  
Vol 1710 (1) ◽  
pp. 154-160 ◽  
Author(s):  
Ahmed Al-Kaisy ◽  
Miao Zhou ◽  
Fred Hall
Keyword(s):  
Field Data ◽  
Weather Conditions ◽  
Work Zone ◽  
Work Zones ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Congested Traffic ◽  
Extensive Field ◽  
Freeway Capacity ◽  
Lane Closures

A construction project in Ontario, Canada, provided the opportunity to use field data to investigate freeway capacity at long-term lane closures due to rehabilitation work. Data from two lane closures at the same construction site (eastbound and westbound) were examined. The site is located on the Gardiner Expressway in the southern part of downtown Toronto. Data were collected during 4 days, totaling around 53 h of congested traffic operations. Results showed significant variation in freeway capacity in the work zones. Despite this variation, average capacity values are reasonably close to the corresponding values provided in the Highway Capacity Manual. Four intervening variables were investigated; all exhibited significant but different effects on freeway work-zone capacity. These variables included temporal variation (which is thought to relate to driver characteristics), grade, day of week, and weather conditions. The results confirmed the pressing need for more extensive field data that will allow better identification of the effect of various control variables on work-zone capacity.

Survey of Work Zone Practices and Validation of Highway Capacity Manual Work Zone Capacity Model

2021 ◽  
pp. 036119812110145
Author(s):  
Raju Thapa ◽  
Julius Codjoe ◽  
Amanua Osafo
Keyword(s):  
The United States ◽  
The State ◽  
Work Zone ◽  
Work Zones ◽  
Highway Capacity ◽  
Local Data ◽  
Highway Capacity Manual ◽  
Capacity Model ◽  
Minimum Capacity ◽  
Lane Closures

Capacity at work zones is one of the major factors affecting queueing at work zones. Different states within the United States use their own methodology in determining work zone capacities and when to implement lane closures at work zones. The objective of this study was two-fold: first, to provide a synthesis of work zone lane closure procedures practiced by the various Departments of Transportation (DOTs) nationwide; and secondly, to validate the Highway Capacity Manual 6th edition’s (HCM 6) work zone capacity model using field-collected data in the state of Louisiana. The first objective was met by administering a survey to DOTs nationwide. The survey revealed that half of the states that responded to the survey require minimum capacity for short-term work zone lane closures, with minimum capacity ranging from 1100 to 1900 passenger cars per hour per lane. In addition, most of the states reported implementing consistent policies across various district offices. The survey findings provide a good source of information on queue analysis and work zone lane closure policies adopted across different DOTs. The second objective was met by collecting traffic flow data from 10 work zone sites within the state of Louisiana and validating the capacity model in the HCM 6. Results showed the HCM 6 model slightly overestimating the average field-observed capacity by 6%. In the absence of local data, the HCM 6 model provides a great tool to estimate work zone capacities in Louisiana.

scholarly journals Predicting Freeway Work Zone Capacity Distribution Based on Logistic Speed-Density Models

2018 ◽  
Vol 2018 ◽  
pp. 1-15 ◽  
Author(s):  
Chaoru Lu ◽  
Jing Dong ◽  
Anuj Sharma ◽  
Tingting Huang ◽  
Skylar Knickerbocker
Keyword(s):  
Prediction Method ◽  
Volume Density ◽  
Lifetime Distribution ◽  
Work Zone ◽  
Work Zones ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Stop And Go ◽  
Stochastic Capacity ◽  
Density Relationship

Speed-volume-density relationship and capacity are key elements in modelling traffic operations, designing roadways, and evaluating facility performance. This paper uses a modified five-parameter logistic model to describe the speed-density relationship. The calibrated speed-density models show that the stop-and-go speed (Vb) and shape parameters (θ1 and θ2) are similar for work zones and the nonwork zone site. Accordingly, an operational capacity prediction method is proposed. To demonstrate the effectiveness of the proposed method, the predicted operational capacities are compared with the field data, Highway Capacity Manual method, the output of WorkZoneQ software, and the ensemble tree approach under different work zone scenarios. Furthermore, a lifetime distribution prediction framework for stochastic capacity of work zones is proposed. The predicted lifetime distribution can well capture the tendency of the observed work zone capacities.

Queue Analysis at Work Zones from Field-Collected Data

2021 ◽  
pp. 036119812110252
Author(s):  
Julius Codjoe ◽  
Raju Thapa ◽  
Elisabeta Mitran
Keyword(s):  
Flow Rate ◽  
Discharge Rate ◽  
Time Of Day ◽  
Work Zone ◽  
Speed Ratio ◽  
Work Zones ◽  
Highway Capacity ◽  
Local Data ◽  
Highway Capacity Manual ◽  
Annual Average Daily Traffic

Estimation of the capacity of work zones is vital to manage the possibility of traffic flows exceeding capacity and resulting in unbearable queues during work zone lane closures. A plethora of research papers have studied several ways to estimate work zone capacity, with the Highway Capacity Manual (HCM) having its own methodology to estimate capacity based on various site characteristics. However, HCM always recommends validating its model with local data to reflect the actual driving behavior of the region. This study considered work zone capacity as a function of queue discharge rate (QDR), defined as the 15-min average flow rate immediately after breakdown, also known as postbreakdown flow rate. By collecting data from 10 different work zones within the state of Louisiana, the study estimated QDR and its corresponding duration at breakdowns. An average QDR of 1,664 pcphpl and an associated queue of 120 min average duration was found. Analysis of variance showed that average QDRs across all sites were not significantly different. The QDR prediction model revealed that a closed right lane and a work zone on linear roadways significantly increased the discharge rate. However, the presence of nearby exit ramps, daytime scenarios, and an increase in the speed ratio and truck percentages were found to decrease the discharge rate. A separate model for the duration of queue or breakdown found the time of day, change in the speed ratio, presence of entry ramp, location of work zones, and annual average daily traffic of the roadway to be significant variables.

Validation Results for Four Models of Oversaturated Freeway Facilities

2000 ◽  
Vol 1710 (1) ◽  
pp. 161-170 ◽  
Author(s):  
Fred L. Hall ◽  
Loren Bloomberg ◽  
Nagui M. Rouphail ◽  
Brian Eads ◽  
Adolf D. May
Keyword(s):  
Field Data ◽  
Simulation Models ◽  
Highway Capacity ◽  
Highway Capacity Manual

Some researchers have noted that the current procedures in the Highway Capacity Manual (HCM) may not be appropriate for analyzing complex or oversaturated freeway facilities. The results of a comparison of an HCM-based procedure with field data from six such freeway sites are reported. Because simulation has often been suggested as an alternative to the HCM for oversaturated freeway facilities, three simulation models (CORSIM, FREQ, and INTEGRATION) were also used to analyze these same six sites. The results suggest that the HCM-based procedures do as well as the three simulation models in reproducing the average speeds across the freeway facilities.

Validation of Generalized Delay Model for Vehicle-Actuated Traffic Signals

1997 ◽  
Vol 1572 (1) ◽  
pp. 105-111 ◽  
Author(s):  
Nagui M. Rouphail ◽  
Mohammad Anwar ◽  
Daniel B. Fambro ◽  
Paul Sloup ◽  
Cesar E. Perez
Keyword(s):  
North Carolina ◽  
Field Data ◽  
Traffic Signals ◽  
Signalized Intersections ◽  
Delay Model ◽  
Highway Capacity ◽  
Generalized Model ◽  
Highway Capacity Manual ◽  
Traffic Volumes ◽  
Isolated Intersection

One limitation of the Highway Capacity Manual (HCM) model for estimating delay at signalized intersections is its inadequate treatment of vehicle-actuated traffic signals. For example, the current delay model uses a single adjustment for all types of actuated control and is not sensitive to changes in actuated controller settings. The objective in this paper was to use TRAF-NETSIM and field data to evaluate a generalized delay model developed to overcome some of these deficiencies. NETSIM was used to estimate delay at an isolated intersection under actuated control, and the delay values obtained from NETSIM were then compared with those estimated by the generalized delay model. In addition, field data were collected from sites in North Carolina, and delays observed in the field were compared with those estimated by the generalized delay model. The delays estimated by the generalized model were comparable with the delays estimated by NETSIM. The data compared favorably for degrees of saturation of less than 0.8. However, at higher degrees of saturation, the generalized model produced delays that were higher than NETSIM’s. Some possible explanations for this discrepancy are discussed. The delays estimated by the generalized model were comparable with delays observed in the field. Researchers have concluded that the generalized delay model is sensitive to changes in traffic volumes and vehicle-actuated controller settings and that the generalized delay model is much improved over the current HCM model in estimating delay at vehicle-actuated traffic signals.

Machine Learning Approach to Forecast Work Zone Mobility using Probe Vehicle Data

2020 ◽  
Vol 2674 (9) ◽  
pp. 157-167
Author(s):  
Mohsen Kamyab ◽  
Stephen Remias ◽  
Erfan Najmi ◽  
Sanaz Rabinia ◽  
Jonathan M. Waddell
Keyword(s):  
Machine Learning ◽  
Traffic Congestion ◽  
Learning Algorithms ◽  
Machine Learning Algorithms ◽  
Work Zone ◽  
Data Sources ◽  
Work Zones ◽  
Probe Vehicle ◽  
Vehicle Data ◽  
Lane Closures

The aim of deploying intelligent transportation systems (ITS) is often to help engineers and operators identify traffic congestion. The future of ITS-based traffic management is the prediction of traffic conditions using ubiquitous data sources. There are currently well-developed prediction models for recurrent traffic congestion such as during peak hour. However, there is a need to predict traffic congestion resulting from non-recurring events such as highway lane closures. As agencies begin to understand the value of collecting work zone data, rich data sets will emerge consisting of historical work zone information. In the era of big data, rich mobility data sources are becoming available that enable the application of machine learning to predict mobility for work zones. The purpose of this study is to utilize historical lane closure information with supervised machine learning algorithms to forecast spatio-temporal mobility for future lane closures. Various traffic data sources were collected from 1,160 work zones on Michigan interstates between 2014 and 2017. This study uses probe vehicle data to retrieve a mobility profile for these historical observations, and uses these profiles to apply random forest, XGBoost, and artificial neural network (ANN) classification algorithms. The mobility prediction results showed that the ANN model outperformed the other models by reaching up to 85% accuracy. The objective of this research was to show that machine learning algorithms can be used to capture patterns for non-recurrent traffic congestion even when hourly traffic volume is not available.

Accounting for Nonrandom Arrivals in Estimate of Delay at Signalized Intersections

1996 ◽  
Vol 1555 (1) ◽  
pp. 9-16 ◽  
Author(s):  
Janice Daniel ◽  
Daniel B. Fambro ◽  
Nagui M. Rouphail
Keyword(s):  
Field Data ◽  
Empirical Studies ◽  
Primary Objective ◽  
Signalized Intersections ◽  
Degree Of Saturation ◽  
Delay Model ◽  
Highway Capacity ◽  
Highway Capacity Manual ◽  
Research Show

The primary objective of this research was to determine the effect of nonrandom or platoon arrivals on the estimate of delay at signalized intersections. The delay model used in the 1994 Highway Capacity Manual (HCM) accounts for nonrandom arrivals through the variable m, which can be shown to be equal to 8kI, where k describes the arrival and service distributions at the intersection and I describes the variation in arrivals due to the upstream intersection. The 1994 HCM delay model m-values are a function of the arrival type, where the arrival type describes the quality of progression at the intersection. Although an improvement to the fixed k I-value used in the 1985 delay model, the 1994 m values are based on empirical studies from limited field data and do not account for the decrease in random arrivals as the volume approaches capacity at the downstream intersection. This research provides an estimate of the variable kI for arterial conditions. An analytical equation was developed as a function of the degree of saturation, and a separate equation was developed for each signal controller type. The results from this research show that the proposed kI's provide delay estimates closer to the measured delay compared with the delay estimates using the kI-values in the 1994 HCM delay model.

Field Evaluation of Late Merge Traffic Control in Work Zones

2005 ◽  
Vol 1911 (1) ◽  
pp. 33-41 ◽  
Author(s):  
Andrew G. Beacher ◽  
Michael D. Fontaine ◽  
Nicholas J. Garber
Keyword(s):  
Field Test ◽  
Traffic Control ◽  
Positive Response ◽  
Field Evaluation ◽  
Field Studies ◽  
Work Zone ◽  
Work Zones ◽  
Short Term ◽  
Term Field ◽  
Lane Closures

The traffic control strategy of the late merge in work zones was devised to improve flow and safety at work zone lane closures. Although some states have put the strategy into practice, only a handful of short-term field studies have formally evaluated its effectiveness. Additional field studies were necessary to assess the efficacy of the strategy and its proper deployment. This paper documents the results of a field test of the late merge traffic control conducted over several months. The late merge strategy was evaluated by comparing its effectiveness with that of traditional plans for work zone lane closures. The field test was conducted on a primary route in Tappahannock, Virginia, at a two-to-one lane closure. Results showed that throughput increased, but the increase was not statistically significant. Likewise, time in queue decreased, but the decrease was not statistically significant. These results were much less dramatic than those of other studies. Possible reasons for this disparity include different driver populations, road types, vehicle mixes, and site-specific characteristics. Despite limited improvements in throughput and time in queue, more drivers were in the closed lane, a positive response to the late merge signs.

Evaluation of Interstate Highway Capacity for Short-Term Work Zone Lane Closures

2004 ◽  
Vol 1877 (1) ◽  
pp. 85-94 ◽  
Author(s):  
Wayne A. Sarasua ◽  
William J. Davis ◽  
David B. Clarke ◽  
Jayaram Kottapally ◽  
Pawan Mulukutla
Keyword(s):  
Work Zone ◽  
Short Term ◽  
Highway Capacity ◽  
Interstate Highway ◽  
Lane Closures

Improved Speed-Flow Relationships for Planning Applications

1997 ◽  
Vol 1572 (1) ◽  
pp. 18-23 ◽  
Author(s):  
Alexander Skabardonis ◽  
Richard Dowling
Keyword(s):  
Field Data ◽  
Air Pollutant ◽  
Pollutant Emissions ◽  
Speed Estimation ◽  
Highway Capacity ◽  
Estimation Techniques ◽  
Highway Capacity Manual ◽  
Planning Models ◽  
Speed Flow ◽  
Simulation Results

Improved speed-estimation techniques for planning applications were developed and tested. Comparisons with field data and simulation results indicate that the recommended techniques provide better accuracy and consistency with the procedures contained in the 1994 update of the Highway Capacity Manual. These speed-estimation techniques will improve the accuracy of long-range transportation planning models for predicting travel time, delay, and air-pollutant emissions.

Sign in / Sign up

Export Citation Format

Share Document