Study on the Day-Based Work Zone Scheduling Problem in Urban Road Networks Based on the Day-to-Day Traffic Assignment Model

2018 ◽  
Vol 2672 (16) ◽  
pp. 14-22 ◽  
Author(s):  
Da Yang ◽  
Xinpeng Zhao ◽  
Yuting Chen ◽  
Xi Zhang ◽  
Chongshuang Chen
Keyword(s):  
Equilibrium State ◽  
Negative Impact ◽  
Travel Cost ◽  
Work Zone ◽  
Scheduling Problem ◽  
Work Zones ◽  
Construction Period ◽  
Urban Road ◽  
Assignment Model ◽  
Optimal Construction

Many work zones exist in the urban road network and have a great negative impact on city traffic. Finding the optimal work zone schedule can minimize the negative impact of work zones on traffic. This paper focuses on the day-based work zone scheduling problem in the urban network. Existing studies on the day-based work zone scheduling problem do not consider the progression of day-to-day traffic from a non-equilibrium state to an equilibrium state during the construction period. For the first time, this paper proposes a model for day-based work zone scheduling by introducing a day-to-day traffic assignment model, in which the target of the optimization problem is minimizing the increase in travel cost caused by work zones. Numerical examples are presented to explore the variations of the optimal construction sequence for different work durations, crew numbers, and model parameter values. Some new findings are obtained in the paper. When the construction duration of each work zone is relatively short (for example, less than 20 days), the optimal scheduling will obviously change with the work duration; when all of the construction durations increase to a threshold (for example, 60 days), the optimal construction sequence will no longer change. An optimal crew number exists that can minimize the increment of travel cost caused by work zones. During the construction period, the total travel cost in the network can be decreased by guiding travelers to change their original travel habits.

Risk Analysis Techniques for Safety Evaluation of Highway Work Zones

2000 ◽  
Vol 1715 (1) ◽  
pp. 10-17 ◽  
Author(s):  
Ana Maria Elias ◽  
Zohar J. Herbsman
Keyword(s):  
Risk Analysis ◽  
Safety Evaluation ◽  
Highway Safety ◽  
Point Of View ◽  
Work Zone ◽  
Work Zones ◽  
Construction Sites ◽  
Work Zone Safety ◽  
Accident Data ◽  
Temporary Closure

Construction sites or work zones create serious disruptions in the normal flow of traffic, resulting in major inconveniences for the traveling public. Furthermore, these work zones create safety hazards that require special consideration. Current legislation and programs, at both state and national levels, emphasize the need for a better understanding of work zone problems to address work zone safety. This reality—coupled with the temporary closure of more miles of highway every year for rehabilitation and maintenance—makes the analysis of safety at construction sites a serious matter. A summary of a comprehensive study associated with the development of a new practical approach to address highway safety in construction zones is presented. Because empirical models require sample sizes that are not attainable due to the intrinsic scarcity of construction zone accident data, the problem was studied from the point of view of risk analysis. Monte Carlo simulations were used to develop risk factors. These factors are meant to be included in the calculations of additional user costs for work zones, or simply applied as risk measurements, to optimize the length and duration of closures for highway reconstruction and rehabilitation projects. In this way, it will be possible to assess the danger of work zones to the traveling public and minimize adverse effect of work zones on highway safety.

Model of Urban Road Congestion Pricing Based on Game Theory

2012 ◽  
Vol 253-255 ◽  
pp. 1895-1899 ◽  
Author(s):  
Li Li Ding ◽  
Zheng Wei Wang ◽  
Lu Yan Li
Keyword(s):  
Game Theory ◽  
Ride Comfort ◽  
Congestion Pricing ◽  
Travel Cost ◽  
Numerical Examples ◽  
Traffic System ◽  
Urban Road ◽  
Road Congestion ◽  
Charge Rate ◽  
The Government

This paper proposes a game-based model to conduct the issue of road congestion pricing. The ride comfort of travel modes, e.g., cars or buses, is introduced into the travel cost function of the traditional bottleneck model. Furthermore, based on different travel cost functions of various travel modes, the Nash equilibriums are achieved among the government and various travelers. The results can be employed to describe internality and externality of traffic system respectively. Finally, numerical examples are presented. The findings of our work indicate a relationship between the government’s goal and the charge rate and that the emergence of ride comfort obviously is a key determinant of travelers’ behavior.

Application of LiDAR and Connected Vehicle Data to Evaluate the Impact of Work Zone Geometry on Freeway Traffic Operations

2018 ◽  
Vol 2672 (16) ◽  
pp. 1-13 ◽  
Author(s):  
Michelle M. Mekker ◽  
Yun-Jou Lin ◽  
Magdy K. I. Elbahnasawy ◽  
Tamer S. A. Shamseldin ◽  
Howell Li ◽  
...  
Keyword(s):  
Case Studies ◽  
Work Zone ◽  
Extensive Literature ◽  
Vehicle Speed ◽  
Connected Vehicle ◽  
Traffic Operations ◽  
Work Zones ◽  
Geometric Data ◽  
Vehicle Data ◽  
The Impact

Extensive literature exists regarding recommendations for lane widths, merging tapers, and work zone geometry to provide safe and efficient traffic operations. However, it is often infeasible or unsafe for inspectors to check these geometric features in a freeway work zone. This paper discusses the integration of LiDAR (Light Detection And Ranging)-generated geometric data with connected vehicle speed data to evaluate the impact of work zone geometry on traffic operations. Connected vehicle speed data can be used at both a system-wide (statewide) or segment-level view to identify periods of congestion and queueing. Examples of regional trends, localized incidents, and recurring bottlenecks are shown in the data in this paper. A LiDAR-mounted vehicle was deployed to a variety of work zones where recurring bottlenecks were identified to collect geometric data. In total, 350 directional miles were covered, resulting in approximately 360 GB of data. Two case studies, where geometric anomalies were identified, are discussed in this paper: a short segment with a narrow lane width of 10–10.5 feet and a merging taper that was about 200 feet shorter than recommended by the Manual on Uniform Traffic Control Devices. In both case studies, these work zone features did not conform to project specifications but were difficult to assess safely by an inspector in the field because of the high volume of traffic. The paper concludes by recommending the use of connected vehicle data to systematically identify work zones with recurring congestion and the use of LiDAR to assess work zone geometrics.

scholarly journals Improved Road Safety at Work Zones using Advanced Traveler Information Systems

2020 ◽  
Author(s):  
Mustafa Suhail Almallah ◽  
Qinaat Hussain ◽  
Wael K. M Alhajyaseen ◽  
Tom Brijs
Keyword(s):  
Traffic Safety ◽  
Driving Simulator ◽  
Work Zone ◽  
Speed Limit ◽  
Work Zones ◽  
Treatment Scenario ◽  
Lane Changing ◽  
Variable Message Signs ◽  
Study Results ◽  
Message Signs

Work zones are road sections where road construction or maintenance activities take place. These work zones usually have different alignment and furniture than the original road and thus temporary lower speeds are adopted at these locations. However, drivers usually face difficulty in adopting the new speed limit and maneuvering safely due to the change in alignment. Therefore, work zones are commonly considered as hazardous locations with higher crash rates and severities as reported in the literature. This study aims to investigate the effectiveness of a variable message signs (VMSs) based system for work zone advance warning area. The proposed system aims at enhancing driver adaptation of the reduced speed limit, encourage early lane changing maneuvers and improve the cooperative driving behavior in the pre-work zone road section. The study was conducted using a driving simulator at the College of Engineering of Qatar University. Seventy volunteers holding a valid Qatari passenger car driving license participated in this study. In the simulator experiment, we have two scenarios (control and treatment). The control scenario was designed based on the Qatar Work Zone Traffic Management Guide (QWZTMG), where the length of the advance warning area is 1000 m. Meanwhile, the treatment scenario contains six newly designed variable message signs where two of them were animation-based. The VMSs were placed at the same locations of the static signs in the control scenario. Both scenarios were tested for two situations. In the first situation, the participants were asked to drive on the left lane while in the second situation, they were instructed to drive on the second lane. The study results showed that the proposed system was effective in motivating drivers to reduce their traveling speed in advance. Compared to the control scenario, drivers’ mean speed was significantly 6.3 and 11.1 kph lower in the VMS scenario in the first and second situations, respectively. Furthermore, the VMS scenario encouraged early lane changing maneuvers. In the VMS scenario, drivers changed their lanes in advance by 150 m compared to the control scenario. In addition, the proposed system was effective in motivating drivers to keep larger headways with the frontal merging vehicle. Taking into account the results from this study, we recommend the proposed VMS based system as a potentially effective treatment to improve traffic safety at work zones.

Validating the Performance of the FHWA Work Zone Model Version 1.0: A Case Study along I-91 in Springfield, Massachusetts

2018 ◽  
Vol 2672 (16) ◽  
pp. 46-56 ◽  
Author(s):  
Andrew Berthaume ◽  
Lauren Jackson ◽  
Ian Berg ◽  
Brian O’Donnell ◽  
Christopher L. Melson
Keyword(s):  
Performance Metrics ◽  
Near Field ◽  
Work Zone ◽  
Driver Model ◽  
Zone Model ◽  
Work Zones ◽  
Simulation Tools ◽  
Zone Management ◽  
Using Data ◽  
Model Components

Central to the effective design of work zones is being able to understand how drivers behave as they approach and enter a work zone area. States use simulation tools in modeling freeway work zones to predict work zone impacts and to select optimal design and deployment strategies. While simple and complex microscopic models have been used over the years to analyze driver behavior, most models were not designed for application in work zones. Using data collected from an instrumented research vehicle and model components from two PhD dissertations, FHWA created the Work Zone Driver Model and programed the Work Zone Driver Model DLL v1.0, a software that could override car-following in commercial microsimulation software packages so that practitioners can better predict work zone impacts. This paper demonstrates the capabilities of the FHWA Work Zone Driver Model DLL v1.0, interfaced with VISSIM and tested on an Interstate work zone in Springfield, Massachusetts. The dynamic link library’s (DLL’s) performance is compared with field data collected using an instrumented research vehicle and to Weidemann 99 in VISSIM. Performance metrics were selected to align with state department of transportation work zone management efforts. Results showed acceptable performance from the DLL, as it predicted queue locations and travel speeds that were near field observations. Limitations of the DLL and interface are discussed, and opportunities for improving version 2.0 are described.

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.

Capacity for North Carolina Freeway Work Zones

1996 ◽  
Vol 1529 (1) ◽  
pp. 27-34 ◽  
Author(s):  
Karen K. Dixon ◽  
Joseph E. Hummer ◽  
Ann R. Lorscheider
Keyword(s):  
North Carolina ◽  
Flow Behavior ◽  
Work Zone ◽  
Site Location ◽  
Work Zones ◽  
Work Activity ◽  
Rural And Urban ◽  
Speed Flow ◽  
Work Area ◽  
Rural Sites

Work zone capacity values for rural and urban freeways without continuous frontage roads were defined and determined. Data were collected using Nu-Metrics counters and classifiers at 24 work zones in North Carolina. The research included analysis of speed-flow behavior, evaluation of work zone sites based on lane configuration and site location, and determination of the location within the work zone where capacity is lowest. It was shown that the intensity of work activity and the type of study site (rural or urban) strongly affected work zone capacity. The data suggested that the location where capacity is reached is also variable based on the intensity of work. For heavy work in a two-lane to one-lane work zone configuration, the capacity values proposed at the active work area are approximately 1,200 vehicles per hour per lane for rural sites and 1,500 vehicles per hour per lane for urban sites. It is recommended that two distinct volumes be used when queue behavior in a freeway work zone is analyzed. The collapse from uninterrupted flow (designated work zone capacity) and the lower queue-discharge volume both should be considered.

Evaluation of Interstate Work Zone Mobility using Probe Vehicle Data and Machine Learning Techniques

2019 ◽  
Vol 2673 (2) ◽  
pp. 811-822 ◽  
Author(s):  
Mohsen Kamyab ◽  
Stephen Remias ◽  
Erfan Najmi ◽  
Kerrick Hood ◽  
Mustafa Al-Akshar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Machine Learning Algorithms ◽  
Work Zone ◽  
Third Party ◽  
Machine Learning Techniques ◽  
Work Zones ◽  
Vehicle Data ◽  
Gps Devices ◽  
Future Work ◽  
The Impact

According to the Federal Highway Administration (FHWA), US work zones on freeways account for nearly 24% of nonrecurring freeway delays and 10% of overall congestion. Historically, there have been limited scalable datasets to investigate the specific causes of congestion due to work zones or to improve work zone planning processes to characterize the impact of work zone congestion. In recent years, third-party data vendors have provided scalable speed data from Global Positioning System (GPS) devices and cell phones which can be used to characterize mobility on all roadways. Each work zone has unique characteristics and varying mobility impacts which are predicted during the planning and design phases, but can realistically be quite different from what is ultimately experienced by the traveling public. This paper uses these datasets to introduce a scalable Work Zone Mobility Audit (WZMA) template. Additionally, the paper uses metrics developed for individual work zones to characterize the impact of more than 250 work zones varying in length and duration from Southeast Michigan. The authors make recommendations to work zone engineers on useful data to collect for improving the WZMA. As more systematic work zone data are collected, improved analytical assessment techniques, such as machine learning processes, can be used to identify the factors that will predict future work zone impacts. The paper concludes by demonstrating two machine learning algorithms, Random Forest and XGBoost, which show historical speed variation is a critical component when predicting the mobility impact of work zones.

scholarly journals Risk Factors in Work Zone Safety Events: A Naturalistic Driving Study Analysis

2019 ◽  
Vol 2673 (1) ◽  
pp. 379-387 ◽  
Author(s):  
Nipjyoti Bharadwaj ◽  
Praveen Edara ◽  
Carlos Sun
Keyword(s):  
Risk Factors ◽  
Driver Behavior ◽  
Work Zone ◽  
Crash Risk ◽  
Work Zones ◽  
Binary Logistic Regression Model ◽  
Work Zone Safety ◽  
Naturalistic Driving Study ◽  
Naturalistic Driving ◽  
The Impact

Identification of crash risk factors and enhancing safety at work zones is a major priority for transportation agencies. There is a critical need for collecting comprehensive data related to work zone safety. The naturalistic driving study (NDS) data offers a rare opportunity for a first-hand view of crashes and near-crashes (CNC) that occur in and around work zones. NDS includes information related to driver behavior and various non-driving related tasks performed while driving. Thus, the impact of driver behavior on crash risk along with infrastructure and traffic variables can be assessed. This study: (1) investigated risk factors associated with safety critical events occurring in a work zone; (2) developed a binary logistic regression model to estimate crash risk in work zones; and (3) quantified risk for different factors using matched case-control design and odds ratios (OR). The predictive ability of the model was evaluated by developing receiver operating characteristic curves for training and validation datasets. The results indicate that performing a non-driving related secondary task for more than 6 seconds increases the CNC risk by 5.46 times. Driver inattention was found to be the most critical behavioral factor contributing to CNC risk with an odds ratio of 29.06. In addition, traffic conditions corresponding to Level of Service (LOS) D exhibited the highest level of CNC risk in work zones. This study represents one of the first efforts to closely examine work zone events in the Transportation Research Board’s second Strategic Highway Research Program (SHRP 2) NDS data to better understand factors contributing to increased crash risk in work zones.

Driver Behavior in Response to Flashing Lights

2019 ◽  
Vol 2673 (5) ◽  
pp. 703-708 ◽  
Author(s):  
Kristin Kersavage ◽  
Nicholas P. Skinner ◽  
John D. Bullough ◽  
Philip M. Garvey ◽  
Eric T. Donnell ◽  
...  
Keyword(s):  
Driver Behavior ◽  
Sequential Pattern ◽  
Work Zone ◽  
Lane Change ◽  
Work Zones ◽  
The Road ◽  
The Individual ◽  
The Right ◽  
Warning Lights ◽  
Current Standards

Flashing yellow warning lights notify drivers about the presence of work along the road. Current standards for these lights address performance of the individual light but not how lights should function when multiple lights are used. In the present study, warning lights were used to delineate a lane change taper in a simulated work zone. Lights flashed with varying intensities and either randomly or in sequence, with lights flashing in turn along the length of the lane change taper, either to the right or to the left. In half of the trials, a flashing police light bar was used on a vehicle located within the simulated work zone. Participants were asked to drive a vehicle approaching the work zone and to identify, as quickly as possible, in which direction the taper’s lane change was (either to the right or left). Drivers were able to correctly identify the taper from farther away when the lights flashed in a sequential pattern than when the flash pattern was random; and the presence of a police light bar resulted in shorter identification distances. The results, along with previous research, can inform standards for the use of flashing lights and police lights in work zones for the safety of drivers and workers.

Sign in / Sign up

Export Citation Format

Share Document