Quantifying non-recurrent traffic congestion caused by freeway work zones using archived work zone and ITS traffic data

2012 ◽  
Vol 8 (4) ◽  
pp. 307-320 ◽  
Author(s):  
Younshik Chung ◽  
Hyun Kim ◽  
Minyoung Park
Keyword(s):  
Traffic Congestion ◽  
Work Zone ◽  
Traffic Data ◽  
Work Zones ◽  
Freeway Work Zones

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.

Development of Breakdown Probability Models and Heavy Vehicle Passenger Car Equivalents for Rural Freeway Work Zones

2020 ◽  
Vol 2674 (12) ◽  
pp. 144-154
Author(s):  
Nicholas L. Jehn ◽  
Rod E. Turochy
Keyword(s):  
Discharge Rate ◽  
Risk Tolerance ◽  
Work Zone ◽  
Work Zones ◽  
Probability Models ◽  
Passenger Car ◽  
Breakdown Probability ◽  
Freeway Work Zones ◽  
The Impact ◽  
Lane Closures

With nearly nine million lane-miles of public roadway and an economy driven by the automobile, interruptions to normal traffic operations for construction and maintenance are inevitable in the U.S.A., but the substantial safety and mobility impacts associated with queueing at freeway lane closures are mitigable. The current freeway work zone capacity methodology in the 6th edition of the Highway Capacity Manual is a vast improvement over historical guidance but still approaches the issue differently than research suggests agencies and practitioners should. Namely, a capacity defined by the mean queue discharge rate is deterministic and fails to account for the stochastic nature of traffic flow and breakdown. These core issues were addressed in this research by developing a methodology for obtaining probabilistic estimates of rural freeway work zone capacity from simulated data in PTV Vissim. Results for a two-to-one lane closure were presented as a series of breakdown probability distributions to demonstrate the viability of this methodology. The data indicated that the impact of trucks on freeway capacity is exacerbated in the presence of lane closures and led to the development of work zone capacity-based passenger car equivalents. Such a procedure may be extended to freeway facilities exhibiting different geometric, traffic, and environmental characteristics and utilized by agencies to make data-driven, risk tolerance-based planning, design, and operations decisions at freeway work zones.

Review of Methods for Estimating Construction Work Zone Capacity

2021 ◽  
pp. 036119812110022
Author(s):  
Ali H. Mashhadi ◽  
Mohammad Farhadmanesh ◽  
Abbas Rashidi ◽  
Nikola Marković
Keyword(s):  
Traffic Flow ◽  
Traffic Congestion ◽  
Flow Characteristics ◽  
Work Zone ◽  
Future Research ◽  
Construction Work ◽  
Work Zones ◽  
Speed Limits ◽  
Detailed Review ◽  
Traffic Flow Characteristics

Road reconstruction and the resulting work zones are considered as a major source of traffic congestion and delays on freeways. The roadway capacity is decreased as a result of a reduced number of traffic lanes, narrower lanes, and work zone speed limits. Accurate prediction of construction work zone capacity helps traffic engineers to have a better estimation of the traffic flow characteristics. To this end, multiple methodologies have been developed to quantify the impacts of work zones on traffic flow. This paper presents a critical review of the three types of approaches to estimating construction work zone capacities, including parametric, non-parametric, and simulation. Then the most commonly considered factors and their frequency are presented. It also performs a detailed review of the approaches, their objectives, and weaknesses. Lastly, it provides recommendations for future research. The presented work could help researchers in the area of work zone capacity estimation by presenting all the previous methodologies in one place.

scholarly journals On the impact of connected automated vehicles in freeway work zones: a cooperative cellular automata model based approach

2018 ◽  
Vol 1 (1) ◽  
pp. 1-14 ◽  
Author(s):  
Yun Zou ◽  
Xiaobo Qu
Keyword(s):  
Cellular Automata ◽  
Travel Time ◽  
Traffic Congestion ◽  
High Speed ◽  
Work Zones ◽  
Automated Vehicles ◽  
Cellular Automata Model ◽  
Content Type ◽  
Freeway Work Zones ◽  
The Impact

Purpose Freeway work zones have been traffic bottlenecks that lead to a series of problems, including long travel time, high-speed variation, driver’s dissatisfaction and traffic congestion. This research aims to develop a collaborative component of connected and automated vehicles (CAVs) to alleviate negative effects caused by work zones. Design/methodology/approach The proposed cooperative component is incorporated in a cellular automata model to examine how and to what scale CAVs can help in improving traffic operations. Findings Simulation results show that, with the proposed component and penetration of CAVs, the average performances (travel time, safety and emission) can all be improved and the stochasticity of performances will be minimized too. Originality/value To the best of the authors’ knowledge, this is the first research that develops a cooperative mechanism of CAVs to improve work zone performance.

scholarly journals Evaluation of the Applicability of the Ramp Metering to a Freeway Using Microsimulation: A Case Study in Riyadh, Saudi Arabia

2019 ◽  
Vol 9 (20) ◽  
pp. 4406
Author(s):  
Seongkwan Lee ◽  
Amr Shokri ◽  
Abdullah Al-Mansour
Keyword(s):  
Saudi Arabia ◽  
Traffic Congestion ◽  
Traffic Management ◽  
Fixed Time ◽  
Ramp Metering ◽  
Traffic Data ◽  
Geometrical Data ◽  
Overall Performance ◽  
Length Reduction

Riyadh, the capital of Saudi Arabia, suffers from traffic congestion like other modern societies, during peak hours but also all day long, even without any incidents. To solve this horrible traffic congestion problem, various efforts have been made from the Active Traffic Management (ATM) aspect. Ramp metering (RM) is one of the representative methods of the ATM and has already proven its value in many locations worldwide. Unfortunately, RM has not yet been fully implemented in Saudi Arabia. This research aimed to assess the applicability of RM to a freeway in Riyadh using microsimulation. The widely known software VISSIM (PTV Planung Transport Verkehr AG, Germany, 1992) was chosen to compare the performances of various RM operating scenarios, such as fixedtime operation with different sub-scenarios and traffic-responsive operation using ALINEA (Asservissement Lineaire d’entree Autoroutiere) algorithm. For the simulations, this study targeted Makkah Road, one of the major freeways in Riyadh, and collected geometrical data and traffic data from that freeway. Analysis of four main scenarios and eight sub-scenarios, proved that overall performance of the fixed-time RM operation is generally good. The sub-scenario 4V3R of the fixed-time RM operation was the best in average queue length reduction. However, the traffic-responsive operation was best in average speed improvement.

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.

scholarly journals Capacity of Freeway Work Zones in Germany

2016 ◽  
Vol 15 ◽  
pp. 233-244 ◽  
Author(s):  
Nina von der Heiden ◽  
Justin Geistefeldt
Keyword(s):  
Work Zones ◽  
Freeway Work Zones
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