scholarly journals Research on Traffic Characteristics and Traffic Conflicts of the One-Way-Closure Work Zone on Freeway

2012 ◽  
Vol 5 ◽  
pp. 26-31
Author(s):  
Lai Zheng ◽  
Xiang Hai Meng
Keyword(s):  
Negative Binomial ◽  
Work Zone ◽  
Distribution Model ◽  
Erlang Distribution ◽  
Work Zones ◽  
Traffic Conditions ◽  
Traffic Characteristics ◽  
Traffic Conflicts ◽  
The One ◽  
Conditions Of Work

By analyzing the traffic characteristics and traffic conflicts of the typical one-way-closure work zone on four-lane freeway, the queuing characteristics of vehicles are determined, and the Erlang distribution model which can describe the distribution of time headway is calibrated. The speed distribution characteristics of each component of the work zone are concluded, and the speed limit scales for these components are put forward based on the statistic analysis. The types of traffic conflicts are firstly concluded, and then the identification method of the rear-end conflicts’ severity degree based on TTC technique as well as the prediction model of rear-end conflicts based on Negative Binomial distribution are put forward. The research results are useful to the analysis of traffic conditions of work zones, and they can also be used to evaluate the safety situations of freeway work zones

Traffic impact assessment and mitigation strategies for disruptions

2018 ◽  
Author(s):  
◽  
Yohan Chang
Keyword(s):  
Prediction Models ◽  
Management Strategies ◽  
Mitigation Strategies ◽  
Work Zone ◽  
Learning Approaches ◽  
Work Zones ◽  
Work Activity ◽  
Traffic Conditions ◽  
Traffic Impact ◽  
The Impact

[ACCESS RESTRICTED TO THE UNIVERSITY OF MISSOURI AT AUTHOR'S REQUEST.] This dissertation research focuses on modeling traffic conditions affected by disruptive events such as work zones, incidents, and hurricanes. Using a combination of field data and simulation experiments, this research tried to address the relationship between disruptive events and their impact on traffic conditions and driver behavior. The first half of the dissertation assesses the impact of work zones. First, a data-driven assessment of the traffic impact of work zones using different data sources was conducted. A tool was developed for practitioners to estimate the delay and travel times of planned work zones. Second, traffic flow and speed prediction models were developed for work zones in order to assist with the better scheduling of work activity. Machine learning approaches were used to develop the prediction models. In addition to work zone effects, the effects of another special event, baseball gameday conditions, were also studied and traffic prediction models were developed. Third, using naturalistic driving study data, classification algorithms categorized work zone events into crashes, nearcrashes, and baseline conditions. In the second half of the dissertation, the focus shifts to the effect of emergency on evacuation. Two chapters in this section present the results of different traffic management strategies -- 1) contraflow crossover and ramp closure optimization and 2) reservation-based intersection control in connected and autonomous vehicle environment.

scholarly journals TIME HEADWAY ANALYSIS TO DETERMINE THE ROAD CAPACITY

2016 ◽  
Vol 4 (2) ◽  
Author(s):  
I Wayan Suweda
Keyword(s):  
Developed Countries ◽  
Distribution Model ◽  
Analysis Model ◽  
Time Headway ◽  
The Road ◽  
Traffic Conditions ◽  
Traffic Characteristics ◽  
Road Capacity ◽  
Headway Distribution ◽  
The City

ABSTRACT: In developed countries, road capacity values derived from time headway is in accordance to their local traffic characteristics. In theory, time headway standards are developed using statistics models. These standards however, are not necessarily relevant to use in Indonesia. This is because of the differences in traffic conditions and motorists behaviours between those in developed countries and Indonesia. This study is to develop the time headway distribution model and subsequently to determine lionk-road capacity in the city of Denpasar, Bali Province. The study consists of time headway data analysis, model calibration and validation and road capacity values??determination. The study found that normal distribution model fitted the local traffic conditions. Road capacity values are of  2,466 pcus/hour and 2,900 pcus/hour obtained from time headway model and the Indonesian Road Capacity Manual (MKJI) respectively.

scholarly journals Extensions to the halo occupation distribution model for more accurate clustering predictions

2019 ◽  
Vol 490 (3) ◽  
pp. 3532-3544 ◽  
Author(s):  
Esteban Jiménez ◽  
Sergio Contreras ◽  
Nelson Padilla ◽  
Idit Zehavi ◽  
Carlton M Baugh ◽  
...  
Keyword(s):  
Negative Binomial ◽  
Formation Rate ◽  
Stellar Mass ◽  
Fixed Number ◽  
Distribution Model ◽  
Additional Parameter ◽  
Galaxy Surveys ◽  
Point Correlation ◽  
The One ◽  
Halo Occupation Distribution

ABSTRACT We test different implementations of the halo occupation distribution (HOD) model to reconstruct the spatial distribution of galaxies as predicted by a version of the L-GALAXIES semi-analytical model (SAM). We compare the measured two-point correlation functions of the HOD mock catalogues and the SAM samples to quantify the fidelity of the reconstruction. We use fixed number density galaxy samples selected according to stellar mass or star formation rate (SFR). We develop three different schemes to populate haloes with galaxies with increasing complexity, considering the scatter of the satellite HOD as an additional parameter in the modelling. We modify the SAM output, removing assembly bias and using a standard Navarro–Frenk–White density profile for the satellite galaxies as the target to reproduce with our HOD mocks. We find that all models give similar reproductions of the two-halo contribution to the clustering signal, but there are differences in the one-halo term. In particular, the HOD mock reproductions work equally well using either the HOD of central and satellites separately or using a model that also accounts for whether or not the haloes contain a central galaxy. We find that the HOD scatter does not have an important impact on the clustering predictions for stellar mass-selected samples. For SFR selections, we obtain the most accurate results assuming a negative binomial distribution for the number of satellites in a halo. The scatter in the satellites HOD is a key consideration for HOD mock catalogues that mimic ELG or SFR-selected samples in future galaxy surveys.

scholarly journals Study on Traffic Conflict Prediction Model of Closed Lanes on the Outside of Expressway

Symmetry ◽  
2020 ◽  
Vol 12 (6) ◽  
pp. 926
Author(s):  
Huimin Ge ◽  
Mingyue Huang ◽  
Ying Lu ◽  
Yousen Yang
Keyword(s):  
Prediction Model ◽  
Traffic Accidents ◽  
Negative Binomial ◽  
Absolute Error ◽  
Vehicle Speed ◽  
Time To Collision ◽  
Traffic Characteristics ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
Conflict Prediction

Due to the randomness and weak symmetry of traffic accidents occurring in the expressway maintenance operation area, it is difficult to use the number of traffic accidents to evaluate the safety of maintenance operation areas. In this paper, the traffic characteristics and traffic conflicts of the maintenance operation area with the lane closed on the outside of the two-way four-lane expressway are studied. By using the statistical method, the distribution of vehicle speed and time headway in different areas of the maintenance operation area are analyzed, and the queuing characteristics of vehicles in the upstream transition zone of the expressway are determined. Based on improved time to collision (TTC) model, the traffic conflict severity of expressway maintenance operation area is divided. The negative binomial distribution is used to establish a traffic conflict prediction model for the enclosed maintenance area of the outer lane of the expressway, and the validity of the traffic conflict prediction model is verified based on the average absolute error percentage (MAPE). The research results show that: when the 0 < TTC < 1.3 s, the traffic conflict is serious conflict; when 1.3 s < TTC, the traffic conflict is non-serious conflict. Furthermore, the traffic conflict prediction model has high accuracy, the MAPE of the warning area and the upstream transition area are 10.8% and 5.0%, respectively.

scholarly journals Highway capacity in work zones – experiences in foreign conditions

2020 ◽  
Vol 66 (3) ◽  
pp. 49-58
Author(s):  
Stefan Andjelkovic ◽  
Vladan Tubić
Keyword(s):  
Traffic Management ◽  
Work Zone ◽  
Level Of Service ◽  
Work Zones ◽  
Highway Capacity ◽  
Traffic Demand ◽  
Traffic Conditions ◽  
Satisfactory Level ◽  
Road Capacity ◽  
Road Work

Traffic management in the highway work zones is a challenge for all traffic engineers. Road work zones are one of the most significant problems for the normal realization of traffic conditions, which can cause various consequences that will greatly reduce capacity and reduce the level of service. On the sections in the work zone, bottlenecks appear, which result in congestion, ie. lead to an imbalance of traffic demand and road capacity. This paper provides an overview of the literature and foreign experiences and ways of regulating traffic in the work zones on the highway. Bearing in mind that we are talking about roads of the highest rank, where are sections with work zones, it is necessary to maintain a satisfactory level of service by applying the concept of regulation that will minimally interfere the normal realization of traffic conditions.

Safety Models for Rural Freeway Work Zones

2000 ◽  
Vol 1715 (1) ◽  
pp. 1-9 ◽  
Author(s):  
Shyam Venugopal ◽  
Andrzej Tarko
Keyword(s):  
Traffic Control ◽  
Traffic Management ◽  
Negative Binomial ◽  
Road Construction ◽  
Work Zone ◽  
Work Zones ◽  
Expected Number ◽  
Crash Data ◽  
Inappropriate Use ◽  
Road Work

Construction and maintenance work zones have traditionally been hazardous locations within the highway environment. Studies show that the accident rates during road construction are generally higher than during periods of regular traffic operations. The increase in the number of crashes may be attributed to ( a) general disruption to the flowing traffic due to sudden discontinuities caused by closed lanes, ( b) improper lane merging maneuvers, ( c) the presence of heavy construction equipment within the work area, ( d) inappropriate use of traffic control devices, and ( e) poor traffic management. Research was conducted to develop regression models predicting the expected number of crashes at work zones on rural, two-lane freeway segments. Crashes on approaches to work zones and those inside the work zones were analyzed separately. For developing these models, an extensive database was obtained, including freeway data, crash data, and work zone characteristics. Negative binomial models were developed with average daily traffic, the length of the work zones, and the duration of the work projects as exposure-to-risk variables. The cost of the various work projects was found to be a good substitute for some of the exposure-to-risk variables. The investigated variables included the number of on and off ramps, both on approaches and inside the work zones; the type of work; and the intensity of the road work involved. The models may be used to evaluate beforehand the expected number of crashes on the work zone, given the work zone characteristics.

scholarly journals Optimization of Work Zone Segments on Urban Roads Using Cellular Automata Model in Mixed Traffic

2018 ◽  
Vol 47 (1) ◽  
pp. 29-35
Author(s):  
Mohit Kumar Singh ◽  
Gaurav Pandey ◽  
K Ramachandra Rao
Keyword(s):  
Cellular Automata ◽  
Work Zone ◽  
Work Zones ◽  
Rational Form ◽  
Zone Length ◽  
Cellular Automata Model ◽  
The Road ◽  
Traffic Characteristics ◽  
On The Road ◽  
Using Data

Increased delays and reduced speeds in work zones leads to congestion. This can be improved by optimizing the work zone length. The focus of this study is to model work zones using cellular automata model and to find the effects of work zones on traffic flow. The methodology adopted in the study involved creating work-zone on the road by blocking some of the cells and then determining traffic characteristics such as delay and queue lengths for model validation. For this the lateral movement rules of the existing Cellular Automata model were modified in order to replicate the traffic movement near work zones. This model is calibrated and validated using data from work zone observed near a metro rail station in Delhi. From the analysis it was evident that the queue length increased with increase in the length of work zone. Several relationships were tried between delay and work zone length. Among them the rational form was found suitable.

Are Older Drivers Safe on Interchanges? Analyzing Driving Errors Causing Crashes

2021 ◽  
pp. 036119812110312
Author(s):  
Denis Elia Monyo ◽  
Henrick J. Haule ◽  
Angela E. Kitali ◽  
Thobias Sando
Keyword(s):  
Latent Class ◽  
Time Of Day ◽  
Older Drivers ◽  
Contributing Factors ◽  
Lighting Condition ◽  
Crash Data ◽  
Traffic Characteristics ◽  
Road Users ◽  
Traffic Conflicts ◽  
Penalized Logistic Regression

Older drivers are prone to driving errors that can lead to crashes. The risk of older drivers making errors increases in locations with complex roadway features and higher traffic conflicts. Interchanges are freeway locations with more driving challenges than other basic segments. Because of the growing population of older drivers, it is vital to understand driving errors that can lead to crashes on interchanges. This knowledge can assist in developing countermeasures that will ensure safety for all road users when navigating through interchanges. The goal of this study was to determine driver, environmental, roadway, and traffic characteristics that influence older drivers’ errors resulting in crashes along interchanges. The analysis was based on three years (2016–2018) of crash data from Florida. A two-step approach involving a latent class clustering analysis and the penalized logistic regression was used to investigate factors that influence driving errors made by older drivers on interchanges. This approach accounted for heterogeneity that exists in the crash data and enhanced the identification of contributing factors. The results revealed patterns that are not obvious without a two-step approach, including variables that were not significant in all crashes, but were significant in specific clusters. These factors included driver gender and interchange type. Results also showed that all other factors, including distracted driving, lighting condition, area type, speed limit, time of day, and horizontal alignment, were significant in all crashes and few specific clusters.

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