Estimating the Safety Effects of Congestion Warning Systems using Carriageway Aggregate Data

Is it possible to use just aggregate carriageway data for the evaluation of congestion warning systems (CWS) in large networks—or any system affecting traffic safety for that matter? In this paper, two hypotheses related to this question are tested. The first hypothesis is that it can be done by comparing large-scale congestion patterns on road stretches with and without CWS. The underlying rationale is that heterogeneous congestion patterns with many disturbances, frequent wide moving jams, and large speed differences result in more potentially unsafe traffic conditions than more homogeneous congestion patterns. The second hypothesis is that it is possible to compare differences in average (maximum) deceleration distributions into congestion waves between road stretches with and without CWS. Both hypotheses have been tested for similar bottlenecks with similar demand patterns and the results suggest the first hypothesis must be rejected. Although the idea seems plausible (CWS result in more homogeneous congestion patterns) there were too many confounding factors in the data to make the case. However, persuasive evidence was found for the second hypothesis. Statistically significant differences were found between (maximum) deceleration distributions on road stretches with and without CWS that suggest CWS do—as expected—contribute positively to traffic safety. It thus seems to be possible to monitor safety effects using just average speeds. However, the method is limited to providing relative comparisons. Furthermore, to fully rule out the effects of unobserved factors, more evidence and validation with microscopic data are needed.

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Constrained Urban Airspace Design for Large-Scale Drone-Based Delivery Traffic

Aerospace ◽

10.3390/aerospace8020038 ◽

2021 ◽

Vol 8 (2) ◽

pp. 38

Author(s):

Malik Doole ◽

Joost Ellerbroek ◽

Victor L. Knoop ◽

Jacco M. Hoekstra

Keyword(s):

Traffic Congestion ◽

Urban Areas ◽

Large Scale ◽

Cost Savings ◽

Future Research ◽

Fast Time ◽

Potential Cost ◽

Horizontal Structure ◽

Traffic Demand ◽

Demand Patterns

Large-scale adoption of drone-based delivery in urban areas promise societal benefits with respect to emissions and on-ground traffic congestion, as well as potential cost savings for drone-based logistic companies. However, for this to materialise, the ability of accommodating high volumes of drone traffic in an urban airspace is one of the biggest challenges. For unconstrained airspace, it has been shown that traffic alignment and segmentation can be used to mitigate conflict probability. The current study investigates the application of these principles to a highly constrained airspace. We propose two urban airspace concepts, applying road-based analogies of two-way and one-way streets by imposing horizontal structure. Both of the airspace concepts employ heading-altitude rules to vertically segment cruising traffic according to their travel direction. These airspace configurations also feature transition altitudes to accommodate turning flights that need to decrease the flight speed in order to make safe turns at intersections. While using fast-time simulation experiments, the performance of these airspace concepts is compared and evaluated for multiple traffic demand densities in terms of safety, stability, and efficiency. The results reveal that an effective way to structure drone traffic in a constrained urban area is to have vertically segmented altitude layers with respect to travel direction as well as horizontal constraints imposed to the flow of traffic. The study also makes recommendations for areas of future research, which are aimed at supporting dynamic traffic demand patterns.

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Vehicular Crowdsourcing for Congestion Support in Smart Cities

Smart Cities ◽

10.3390/smartcities4020034 ◽

2021 ◽

Vol 4 (2) ◽

pp. 662-685

Author(s):

Stephan Olariu

Keyword(s):

Smart City ◽

Large Scale ◽

Smart Cities ◽

Traffic Signal Control ◽

Signal Timing ◽

Adaptive Traffic Signal Control ◽

Traffic Conditions ◽

Direct Benefits ◽

Traffic Signal Control Systems ◽

Computational Resources

Under present-day practices, the vehicles on our roadways and city streets are mere spectators that witness traffic-related events without being able to participate in the mitigation of their effect. This paper lays the theoretical foundations of a framework for harnessing the on-board computational resources in vehicles stuck in urban congestion in order to assist transportation agencies with preventing or dissipating congestion through large-scale signal re-timing. Our framework is called VACCS: Vehicular Crowdsourcing for Congestion Support in Smart Cities. What makes this framework unique is that we suggest that in such situations the vehicles have the potential to cooperate with various transportation authorities to solve problems that otherwise would either take an inordinate amount of time to solve or cannot be solved for lack for adequate municipal resources. VACCS offers direct benefits to both the driving public and the Smart City. By developing timing plans that respond to current traffic conditions, overall traffic flow will improve, carbon emissions will be reduced, and economic impacts of congestion on citizens and businesses will be lessened. It is expected that drivers will be willing to donate under-utilized on-board computing resources in their vehicles to develop improved signal timing plans in return for the direct benefits of time savings and reduced fuel consumption costs. VACCS allows the Smart City to dynamically respond to traffic conditions while simultaneously reducing investments in the computational resources that would be required for traditional adaptive traffic signal control systems.

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High-Resolution Pixel LED Headlamps: Functional Requirement Analysis and Research Progress

Applied Sciences ◽

10.3390/app11083368 ◽

2021 ◽

Vol 11 (8) ◽

pp. 3368

Author(s):

Liping Wang ◽

Jianshe Ma ◽

Ping Su ◽

Jianwei Huang

Keyword(s):

High Resolution ◽

Functional Diversity ◽

Traffic Safety ◽

New Technologies ◽

Light Distribution ◽

Research Progress ◽

Requirement Analysis ◽

Functional Requirement ◽

Traffic Conditions ◽

The Subject

High-resolution pixel LED headlamps are lighting devices that can produce high-resolution light distribution to adapt to road and traffic conditions, intelligently illuminate traffic areas, and assist drivers. Due to the complexity of roads and traffic conditions, the functional diversity of high-resolution pixel LEDs headlamps and traffic safety has come into question and is the subject of in-depth research conducted by car manufacturers and regulators. We summarize the current possible functions of high-resolution pixel LED headlamps and analyze ways in which they could be improved. This paper also discusses the prospect of new technologies in the future.

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Automated Visual Recognizability Evaluation of Traffic Sign Based on 3D LiDAR Point Clouds

Remote Sensing ◽

10.3390/rs11121453 ◽

2019 ◽

Vol 11 (12) ◽

pp. 1453 ◽

Cited By ~ 5

Author(s):

Shanxin Zhang ◽

Cheng Wang ◽

Lili Lin ◽

Chenglu Wen ◽

Chenhui Yang ◽

...

Keyword(s):

Traffic Safety ◽

Laser Scanning ◽

Large Scale ◽

Evaluation Method ◽

Evaluation Model ◽

Point Clouds ◽

Traffic Sign ◽

Traffic Signs ◽

3D Point Clouds ◽

Traffic Environment

Maintaining the high visual recognizability of traffic signs for traffic safety is a key matter for road network management. Mobile Laser Scanning (MLS) systems provide efficient way of 3D measurement over large-scale traffic environment. This paper presents a quantitative visual recognizability evaluation method for traffic signs in large-scale traffic environment based on traffic recognition theory and MLS 3D point clouds. We first propose the Visibility Evaluation Model (VEM) to quantitatively describe the visibility of traffic sign from any given viewpoint, then we proposed the concept of visual recognizability field and Traffic Sign Visual Recognizability Evaluation Model (TSVREM) to measure the visual recognizability of a traffic sign. Finally, we present an automatic TSVREM calculation algorithm for MLS 3D point clouds. Experimental results on real MLS 3D point clouds show that the proposed method is feasible and efficient.

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The challenge of forecasting high streamflows 1–3 months in advance with lagged climate indices in southeast Australia

Natural Hazards and Earth System Science ◽

10.5194/nhess-14-219-2014 ◽

2014 ◽

Vol 14 (2) ◽

pp. 219-233 ◽

Cited By ~ 18

Author(s):

J. C. Bennett ◽

Q. J. Wang ◽

P. Pokhrel ◽

D. E. Robertson

Keyword(s):

Large Scale ◽

Bayesian Model Averaging ◽

Emergency Services ◽

Joint Probability ◽

Model Averaging ◽

Climate Indices ◽

Warning Systems ◽

Forecast Period ◽

Considerable Benefit ◽

Probability Modelling

Abstract. Skilful forecasts of high streamflows a month or more in advance are likely to be of considerable benefit to emergency services and the broader community. This is particularly true for mesoscale catchments (< 2000 km2) with little or no seasonal snowmelt, where real-time warning systems are only able to give short notice of impending floods. In this study, we generate forecasts of high streamflows for the coming 1-month and coming 3-month periods using large-scale ocean–atmosphere climate indices and catchment wetness as predictors. Forecasts are generated with a combination of Bayesian joint probability modelling and Bayesian model averaging. High streamflows are defined as maximum single-day streamflows and maximum 5-day streamflows that occur during each 1-month or 3-month forecast period. Skill is clearly evident in the 1-month forecasts of high streamflows. Surprisingly, in several catchments positive skill is also evident in forecasts of large threshold events (exceedance probabilities of 25%) over the next month. Little skill is evident in forecasts of high streamflows for the 3-month period. We show that including lagged climate indices as predictors adds little skill to the forecasts, and thus catchment wetness is by far the most important predictor. Accordingly, we recommend that forecasts may be improved by using accurate estimates of catchment wetness.

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PEDESTRIAN TRAFFIC CONDITIONS OF RURAL ROADS AND BUILT-UP AREAS: THE ANALYSIS OF THE EXISTING SITUATION AND POSSIBILITIES OF IMPROVING TRAFFIC CONDITIONS

Mokslas - Lietuvos ateitis ◽

10.3846/mla.2010.054 ◽

2010 ◽

Vol 2 (3) ◽

pp. 60-66

Author(s):

Nemunas Abukauskas ◽

Egidijus Skrodenis

Keyword(s):

Traffic Safety ◽

Road Safety ◽

Traffic Accidents ◽

Road Traffic ◽

Rural Roads ◽

Traffic Conditions ◽

Foreign Countries ◽

Pedestrian Traffic ◽

Main Activity

The results of lengthy thorough investigations into traffic safety situation show that the percentage of pedestrians getting involved in road traffic accidents on Lithuanian roads is significantly higher (more than 33 % of the total number of injury and fatal accidents) than that compared to the other European Union member-states. The article studies traffic safety problems and their factors causing the largest influence on the occurrence of these accidents. Considering valuable experience gained by foreign countries, investigation was carried out to establish general and main factors causing insufficient road safety conditions and significance of these factors to road safety. The article also shows the main activity improving road safety in Lithuania and discusses the effectiveness of strategic and local (temporary and long term) measures to improve conditions for pedestrian road safety.

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Overview of road performance on the tsunami evacuation road during the n-COVID19 pandemic

E3S Web of Conferences ◽

10.1051/e3sconf/202133106006 ◽

2021 ◽

Vol 331 ◽

pp. 06006

Author(s):

Yossyafra ◽

Anyta Ramadhani ◽

Vina Gusman ◽

Monica Herimarni

Keyword(s):

Large Scale ◽

New Normal ◽

Tsunami Disaster ◽

Traffic Conditions ◽

Normal Period ◽

Road Performance ◽

And Performance ◽

Traffic Disturbance ◽

The City ◽

Better Than

The COVID-19 pandemic has changed the world in various sectors and human activities. Limiting human activity and mobility also has an impact on transportation and traffic. This study aims to calculate the capacity and performance of roads under normal pandemic conditions before PSBB (Large-Scale Social Restrictions) in April 2020 and New Normal in July 2002, as well as predict traffic conditions if the Tsunami disaster hits the city during both periods. Tsunami Evacuation roads in Padang City were selected for analysis. The Indonesian Road Capacity Manual 1997 on urban roads is used as a reference for analyzing road performance indicators. The results showed that; road performance during the PSBB period was better than the New Normal period. The effect of volume and side traffic disturbance factors in the New Normal period makes a significant decrease in performance. Through prediction simulations, if a Tsunami occurs in the two study periods, the analyzed roads can relatively serve evacuation movements. However, the capacity needs to be increased for normal conditions.

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Application of Connected and Automated Vehicles in a Large-Scale Network by Considering Vehicle-to-Vehicle and Vehicle-to-Infrastructure Technology

Transportation Research Record Journal of the Transportation Research Board ◽

10.1177/0361198120963105 ◽

2020 ◽

pp. 036119812096310

Author(s):

Md Hasibur Rahman ◽

Mohamed Abdel-Aty

Keyword(s):

Traffic Safety ◽

Control Algorithm ◽

Large Scale ◽

Signal Control ◽

Market Penetration ◽

Automated Vehicles ◽

Large Scale Network ◽

Vehicle To Vehicle ◽

Scale Network ◽

Vehicle To Infrastructure

Application of connected and automated vehicles (CAVs) is expected to have a significant impact on traffic safety and mobility. Although several studies evaluated the effectiveness of CAVs in a small roadway segment, there is a lack of studies analyzing the impact of CAVs in a large-scale network by considering both freeways and arterials. Therefore, the objective of this study is to analyze the effectiveness of CAVs at the network level by utilizing both vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication technologies. Also, the study proposed a new signal control algorithm through V2I technology to elevate the performance of CAVs at intersections. A car-following model named cooperative adaptive cruise control was utilized to approximate the driving behavior of CAVs in the Aimsun Next microsimulation environment. For the testbed, the research team selected Orlando central business district area in Florida, U.S. To this end, the impacts of CAVs were evaluated based on traffic efficiency (e.g., travel time rate [TTR], speed, and average approach delay, etc.) and safety surrogates (e.g., standard deviation of speed, real-time crash-risk models for freeways and arterials, time exposed time-to-collision). The results showed that the application of CAVs reduced TTR significantly compared with the base condition even with the low market penetration level. Also, the proposed signal control algorithm reduced the approach delay for 94% of the total intersections present in the network. Moreover, safety evaluation results showed a significant improvement of traffic safety in the freeways and arterials under CAV conditions with different market penetration rates.

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Stiffness and Strength Improvement of Geosynthetic-Reinforced Pavement Foundation Using Large-Scale Wheel Test

Infrastructures ◽

10.3390/infrastructures5040033 ◽

2020 ◽

Vol 5 (4) ◽

pp. 33

Author(s):

Jason Wright ◽

S. Sonny Kim ◽

Bumjoo Kim

Keyword(s):

Stress Response ◽

Dynamic Load ◽

Large Scale ◽

Material Behavior ◽

Traffic Conditions ◽

Load Tests ◽

Wheel Loading ◽

Pavement Layers ◽

Rolling Wheel ◽

Pavement Foundation

Laboratory cyclic plate load tests are commonly used in the assessment of geosynthetic performance in pavement applications due to the repeatability of testing results and the smaller required testing areas than traditional Accelerated Pavement Testing facilities. While the objective of traditional plate load testing procedure is to closely replicate traffic conditions, the reality is that rolling wheel loads produce different stresses in pavement layers than traditional cyclic plate load tests. This two-fold study investigates the differences between the stress response of subgrade soil from a rolling wheel load (replicating rolling traffic conditions) and a unidirectional dynamic load (replicating traditional plate load test procedures) in order to obtain a more realistic stress response of pavement layers from rolling wheel traffic. Ultimately, results show that the testing specimens that experienced rolling wheel loading had an average of 17% higher pressure measurements in the top of the subgrade than vertically loaded (unidirectional dynamic load) specimens. The second segment of this study is used in conjunction with the first to analyze aggregate base material behavior when using a geosynthetic for reinforcement. The study aimed to determine the difference in the post-trafficked strength and stiffness of pavement foundation. A Dynamic Cone Penetrometer and Light Weight Deflectometer were utilized to determine material changes from this trafficking and revealed that all specimens that included a geosynthetic had a higher base stiffness and strength while the specimen with geotextile and geogrid in combination created the highest stiffness and strength after large-scale rolling wheel trafficking.

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Empirical Analysis on Time to Collision at Urban Expressway

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.505-506.1127 ◽

2014 ◽

Vol 505-506 ◽

pp. 1127-1132 ◽

Cited By ~ 2

Author(s):

Cheng Xu ◽

Zhao Wei Qu

Keyword(s):

Empirical Analysis ◽

Traffic Safety ◽

Traffic Volume ◽

T Test ◽

Descriptive Statistics ◽

Traffic Condition ◽

Time To Collision ◽

Traffic Conditions ◽

Urban Expressway ◽

Traffic Conflicts

Traffic safety is of great significance, especially at urban expressway where traffic volume is large and traffic conflicts are highlighted. But little research up to date has discussed in detail how these factors impact the TTC characteristics. In this paper, field Beijing expressway data were collected by video with different locations, lanes, traffic conditions and following vehicle types. Accordingly, some basic descriptive statistics of total TTC samples were shown and analyzed. We then used T-test to analyze the effect of road environments, traffic conditions, and vehicle types on TTC statistically. The results implied three main findings. Firstly, TTC was found to change according to road environments (i.e. TTC on weaving segment is smaller than other locations), secondly, some evidence supported this hypothesis that traffic conditions (especially uncongested traffic condition) affect TTC significantly, and lastly, little correlation was found between TTC means and vehicle types.

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