Intersection Safety Research Articles

A surrogate safety assessment of scrambled phase intersections

Traffic safety remains a top priority for policymakers and researchers, prompting numerous investigations to enhance safety for all road users, particularly pedestrians. This paper evaluates the safety impact of implementing scramble phases at intersections with a high concentration of vulnerable road users in Edmonton, Canada. The study spans three periods: prior to the scramble phase installation, immediately post-installation, and 6 months post-installation. The evaluation employs two key methodologies. Firstly, it observes the frequency of right-turn-on-red violations to assess driver behaviour. Secondly, the study investigates the frequency of serious conflicts, utilizing safety indicators such as time to collision, time difference to point of intersection, and distance between stop position and pedestrian. The findings suggest that introducing scramble phases positively impacts intersection safety, notably reducing severe conflicts and total right-turn-on-red violations. These results offer valuable insights for policymakers and researchers working towards safer urban traffic environments.

Enhancing safety and efficiency of signal intersections: A part-time protected right-turn signal control for straight-right lane in connected environment

Enhancing safety and efficiency of signal intersections: A part-time protected right-turn signal control for straight-right lane in connected environment

Improving urban intersection safety insights from simulation analysis

This research explores enhancing intersection safety, a critical aspect of urban traffic management, by analyzing the effects of infrastructure modifications and understanding driver behavior. Centered on a critical junction near Sichon Municipality, the study evaluates three proposed redesign scenarios using the VISSIM simulation tool and the Safety Surrogate Assessment Model (SSAM). These scenarios include the implementation of a roundabout with guidance feature (Model 2), the introduction of a dumbbell-shaped roundabout (Model 3), and the construction of a roundabout without turning points (Model 4). Findings suggest that Models 2 and 4, which incorporate roundabouts, can reduce conflict points, potentially decreasing traffic collisions. However, these models also indicate possible increases in travel times and queue lengths, highlighting the trade-offs between enhancing safety and maintaining traffic efficiency. An in-depth analysis of Deltas (ΔS) values through Optimized Hot Spot Analysis reveals areas with high and low collision severity, providing direction for targeted safety measures. The study demonstrates the complex effects of intersection redesigns on safety and traffic flow. For instance, Model 3 shows increased conflict points, emphasizing the need for specific design considerations to counteract potential negative impacts. Conversely, Model 4 achieves streamlined traffic flow but necessitates careful design to prevent new safety risks. This research underscores the need for a comprehensive approach to intersection safety that combines infrastructure improvements with insights into driver behavior. By utilizing advanced simulation tools and analyzing driving behavior, the study contributes valuable insights towards designing and assessing traffic safety interventions, aiming for safer and more efficient urban traffic environments.

Enhancing intersection safety: Testing measures to reduce law violations in Loja (Ecuador)

This study evaluates the effectiveness of measures aimed at reducing traffic violations, specifically focusing on wrong-way driving, at intersections in Loja, Ecuador. The high incidence of accidents at these intersections, often resulting from wrong-way driving and non-compliance with traffic regulations, underscores the critical need for effective strategies to enhance road safety. To address this issue, we adopted a multidisciplinary approach to assess the impact of two specific interventions: the implementation of official warnings and the presence of traffic officers at a selected intersection. Data collection involved recording instances of traffic violations, administering road safety surveys, and monitoring the implementation of these interventions. The post-implementation analysis sought to determine the effect of these measures on driver behavior and overall traffic safety. Our findings indicate that while the interventions succeeded in increasing awareness about traffic violations, they did not produce a significant reduction in undesirable driving behaviors. This suggests that, although the presence of warnings and traffic officers is beneficial in raising awareness, these measures alone may not be sufficient to effect substantial behavioral changes. The research provides valuable insights for the development of more comprehensive road safety strategies and emphasizes the need for further studies to explore and address the underlying causes of traffic violations.

A novel approach for safety assessment at unsignalized intersections: Integrating spatial metrics into postencroachment time analysis under heterogeneous traffic conditions

Objective Evaluating the safety risks at unsignalized intersections becomes increasingly complex amid conditions of dense traffic flow, a heterogeneous mix of vehicles, nonadherence to lane demarcations, and reactive driving techniques. Understanding driver behavior under such varying circumstances is crucial for accurately assessing the potential hazards present at these intersections. The study aims to assess the safety of unsignalized intersections by incorporating both spatial and temporal variables under heterogeneous conditions. Methods The study presents a new safety indicator, dynamic postencroachment time (DPET), formulated to encapsulate both the spatial and temporal variables of heterogeneous traffic. Six unsignalized intersections were selected as the study areas in Assam, India, to assess the new indicator for merging and crossing conflicts. A videographic survey of the intersections was done to obtain vehicles’ trajectory data and capture their conflict behaviors based on their position, speed, and steering angle. The peak over threshold (POT) approach of extreme value theory (EVT) was used to examine the feasibility of the indicator, and the methodology was validated using 4 years of crash data. Results The result showed that a common threshold of 0.7 s from the POT approach is sufficient to identify severe conflicts. Furthermore, the threshold level yielded a shape parameter greater than −0.5, affirming that the maximum likelihood estimates retain the standard asymptotic attributes associated with EVT. The DPET approach estimated more crashes than observed fatal crashes, reflecting its ability to capture extreme events at a lower threshold. In comparison, the traditional PET approach estimated fewer crashes due to higher values influenced by evasive actions. Graphical analysis demonstrated a strong correlation between the observed crash data over 4 years and the estimated crashes derived from the EVT models. Conclusions: Integrating spatial variables in PET analysis provides a more robust measure for conflict analysis and assessment of potential traffic conflicts at unsignalized intersections. The subsequent validation of the model with actual crash data highlights its practical applicability in enhancing road safety. The findings from the study provide a promising direction for future research and the potential for widespread implementation in traffic management systems.

Characteristics analysis and safety evaluation of vehicles turning over long distances

In order to explore the motion and safety characteristics of the U-turn vehicles at long-range U-turn intersections, based on the measured data of the U-turn vehicles at typical locations, we analyzed the characteristics of the U-turn vehicle's trajectories and traffic parameters with the help of probability theory and statistical knowledge, and established the U-turn trajectory model. We used Traffic Conflict Technology (TCT) and take Post Encroachment Time (PET) as the indicator to study the feature of vehicles security of - turn vehicles. Three conclusions are drawn from this study. First, there is a significant difference in the headway between long-range -turn vehicles and those at intersections without opening: the stability of the headway of long-range -turn vehicles is weak, and the release of vehicles is seriously disturbed by the turning flow; Secondly, when turning around at a long interval u-turn intersection, the starting position of vehicle turning is dispersed and the distribution of U-turn trajectories is quadratic distribution. Third, the setting of long interval turning lanes will increase the interference between traffic flows at intersections, thus increasing the number of conflicts with vehicles in the opposite direction. Cross-conflict accounts for the majority of conflicts in long interval U-turn intersections, and rear-end collision is the main conflict type in U-turn intersections without opening. The above research conclusions are helpful to improve the safety of long interval U-turn intersections.

A conflict risk graph approach to modeling spatio-temporal dynamics of intersection safety

Intersections are among the most hazardous roadway spaces due to the complex and conflicting road users’ movements. Spatio-temporal modeling of conflict risks among road users can help to identify strategies to mitigate the exacerbation of safety risks and restore hazardous conditions to normal traffic situations. This paper proposes the 'Conflict Risk Graph' as a novel concept to infer real-time conflict risks at intersections at a fine-grained level by mapping conflict-prone locations to nodes within a network characterized by specific topological structures. A significant contribution of this work is the development of a Transformer-based Graph Convolutional Network (Trans-GCN), a model that synergistically combines the Transformer's proficiency in capturing global dependence with the GCN's ability to learn local correlations. The Trans-GCN adeptly models the complex evolution patterns of conflict risks at intersections. The evaluation in this paper against five common state-of-the-art deep learning approaches demonstrates the superior performance of the Trans-GCN in conflict risk inference and adaptability to node changes. Furthermore, extensive experiments with different node configurations reveal a correlation between node setup and model performance, showing that higher spatio-temporal resolution decreases inference accuracy. This insight informs the selection of an optimal node configuration that balances the detailed capture of spatio-temporal dynamics with modeling accuracy, enabling ideal conflict risk inferences at intersections. Ultimately, this work offers significant insights for the enhancement of proactive traffic safety management and the advancement of intelligent traffic systems.

Intersection Safety for All

Intersection Safety for All

Large Scale Evaluation of Normalized Hard-Braking Events Derived from Connected Vehicle Trajectory Data at Signalized Intersections, Roundabouts, and All-Way Stops

Intersection safety has been traditionally evaluated using three to five years of crash data. Recent literature suggests that connected vehicle (CV)-derived hard braking (HB) events can provide a surrogate for crashes with only a few weeks or months of data collection. This study used CV trajectories to derive HB events. Then, the HB events were normalized as the ratio of HB events to sampled CV trajectories. The normalized HB ratios were evaluated and compared at 435 signalized intersections, roundabouts, and all-way stops in Indiana. The analysis showed that signalized intersections and roundabouts had the highest counts of HB events, and all-way stops had the highest HB ratios. Through movements at signalized intersections showed the lowest HB ratios, whereas left turns at all-way stops had the highest ratios. A density analysis of the geospatial occurrence of HB events concluded that they tend to occur closest to the intersection center at all-way stops, but are more evenly distributed at signalized intersections. Additionally, a speed analysis indicated that HB events at signalized intersection through movements tend to occur at higher speeds, roughly between 26 and 36 MPH, perhaps due to the driver reaction during the onset of yellow. The findings presented in this study provide transportation agencies with insights on the occurrence of normalized HB ratios at three different intersection types. The data provided in this paper provide a framework for agencies to use HB ratios to screen different types of intersections for further evaluation.

Comparative Sensitivity Analysis on Intersection Crash Prediction Models by Control Type: Highway Safety Manual Approach

A comprehensive, in-depth investigation into the comparative safety of different intersection control types is presented, specifically signalized and minor road stop-controlled intersections across facility types. Employing a rigorous sensitivity analysis, the study scrutinizes intersection crash prediction models (CPMs) rooted in the Highway Safety Manual (HSM) methodology. Through meticulous data analyses and thorough comparisons of predictive models across a range of major and minor road traffic volumes, the paper critically examines the portrayal of signalized and stop-controlled intersections within the default HSM Part C CPMs. Additionally, the study delves into the effects of certain crash modification factors on CPMs, further exploring the impacts of calibration factors and locally developed models on crash prediction results. CPMs for signalized intersections do not uniformly lead to fewer crashes compared with stop-controlled intersections, especially under certain traffic volumes and when considering fatal and injury crashes. Therefore, the choice of intersection control should be based on more nuanced criteria than traffic volume alone. Additionally, the research emphasizes the role of intersection geometry and operations, for example, the benefits of adding turn lanes and varying left-turn phasing, in influencing safety outcomes. This study significantly contributes to the understanding of intersection safety and HSM modeling approaches, providing a valuable resource for transportation professionals dedicated to advancing intersection safety. Examining strengths and limitations of existing models provides valuable input for researchers developing future intersection CPMs, and offers essential insights for transportation planners and engineers, informing decision-making for optimizing intersection control strategies and enhancing overall intersection safety and traffic management.

Impact of Auxiliary Markings on Intersection Safety

The rapid growth of motorcycle vehicles coupled with inadequate traffic discipline contributes to an escalating rate of traffic accidents and casualties. This study investigates the efficacy of auxiliary road markings in enhancing traffic safety and intersection performance along Lieutenant Sutopo Street, Promoter Street, and Boulevard BSD East in South Tangerang, Indonesia. Employing the Traffic Conflict Technique (TCT), the research evaluates safety enhancements and service level alterations subsequent to the installation of road markings. Preliminary observations highlight significant safety concerns and traffic conflicts at the intersection. Consequently, auxiliary road markings are strategically installed to regulate driver behavior, enhance lane discipline, and improve visibility. Post-installation observations revealed a significant decrease in total vehicle conflicts, though the percentage of severe conflicts slightly increased. Initially rated as Level of Service (LOS) F with high delays, the LOS remained the same post-marking installation but with reduced delays. Further cycle time adjustments improved the LOS to E, indicating a substantial overall reduction in delays. The findings suggest that although auxiliary road markings effectively reduce traffic conflicts and improve intersection performance, additional measures are necessary to address the severity of these conflicts. The study offers valuable insights into the effectiveness of road safety interventions, supporting broader strategies for improving traffic management and safety in urban areas.

Intersection Control Evaluation for Highway Safety Analysis

Road traffic accidents take more lives than a combination of other accidents and natural disasters. An article published on September 9, 2023, in the Nepali Times, reported that between April 2022 and April 2023, a total of 2,320 individuals lost their lives, with 28,856 sustaining injuries, many resulting in lifelong impairment. Traffic studies have revealed that Intersection Control Evaluation (ICE) facilitates strategic decision-making through the use of factual information, data, and metrics. The primary objective of this research on intersection control evaluation is to explore how the screening process and the selection of alternative intersections in ICE contribute to the reduction of accidents at intersections. A focused examination of the literature assessing the methodology's effectiveness in maintaining intersection safety suggests that intersection control evaluation aids in strategy selection during expansion and signal usage at major intersections. Subsequent discussions utilized various spreadsheet tools and online forums. The findings indicate that ICE serves as an effective framework for screening intersection alternatives and identifying optimal solutions. Results show that tools such as 'Capacity Analysis for Planning of Junctions' (CAP-X) effectively evaluate intersection types. Additionally, 'Safety Performance of Intersection Control Evaluations' (SPICE) is employed for safety analysis at grade intersections. Cost analysis, based on results obtained from the Life Cycle Cost Estimation Tool (LCCET) spreadsheet, demonstrated the cost-effectiveness of this approach.In light of the results and discussions, intersection control evaluation should play a crucial role in implementing safer, more balanced, and cost-effective solutions at road intersections.

Bicycle rider evaluations of an intersection safety alert system: Learnings for similar technologies from a field trial

Bicycle-mounted crash avoidance technologies have been developed to improve cyclist safety. However, their effectiveness in alerting cyclists of potential dangers and the preferences of cyclists regarding the types and mechanisms of receiving alerts have not been examined extensively in field trials. To address this gap, this paper aims to understand how safety alerts are best communicated to cyclists. This aim was achieved by undertaking a field trial of a smartphone app, which was the user interface of an innovative Intersection Safety Alert System (ISAS). A total of 38 participants rode bicycles equipped with the ISAS in a 2-day field trial in downtown Melbourne, Australia, and then completed a technology acceptance survey. The survey data were analysed using statistical and thematic analysis methods to derive insights on how cycling safety technologies should be designed to ensure a good level of user acceptance. Results showed that cyclists would be willing to use or recommend a safety app that is free from privacy or security concerns, be able to provide alerts that can effectively notify about dangerous situations, and be effective in improving the safety for the whole cycling community. Cyclists preferred to receive simple and clear safety alerts that provided information on high-risk locations and the nature of dangers through an easy-to-use user interface that runs in the background and communicates with other cycling and navigational apps. They wanted the alerts to convey real-time and non-obvious traffic conditions and unpredictable movements of other road users. Preferences and comments regarding auditory, visual and haptic modalities of presenting alerts differed among riders.

Enhancing intersection safety in autonomous traffic: A grid-based approach with risk quantification

Existing studies on autonomous intersection management (AIM) primarily focus on traffic efficiency, often overlooking the overall intersection safety, where conflict separation is simplified and traffic conflicts are inadequately assessed. In this paper, we introduce a calculation method for the grid-based Post Encroachment Time (PET) and the total kinetic energy change before and after collisions. The improved grid-based PET metric provides a more accurate estimation of collision probability, and the total kinetic energy change serves as a precise measure of collision severity. Consequently, we establish the Grid-Based Conflict Index (GBCI) to systematically quantify collision risks between vehicles at an autonomous intersection. Then, we propose a traffic-safety-based AIM model aimed at minimizing the weighted sum of total delay and conflict risk at the intersection. This entails the optimization of entry time and trajectory for each vehicle within the intersection, achieving traffic control that prioritizes overall intersection safety. Our results demonstrate that GBCI effectively assesses conflict risks within the intersection, and the proposed AIM model significantly reduces conflict risks between vehicles and enhances traffic safety while ensuring intersection efficiency.

Advanced Traffic Light Controller using FPGA and ARDUINO

This study presents a novel approach to develop a traffic light controller using FPGA and Arduino platforms. The objective is to design a robust, adaptable, and efficient traffic management system. Methodology involves hardware integration of FPGA for real-time processing and Arduino for interfacing with sensors and actuators. The proposed system utilizes FPGA's parallel processing capabilities for rapid decision-making and Arduino's flexibility for sensor data acquisition and actuator control. Performance evaluation includes simulation and real-world testing to assess reliability, response time, and scalability. Results demonstrate the effectiveness of the proposed controller in optimizing traffic flow and improving intersection safety.

Pedestrian injury severities resulting from vehicle/pedestrian intersection crashes: An assessment of COVID-contributing temporal shifts

Pedestrian mobility has become an increasingly important concern in transportation system analysis because of its positive impacts on the environment and healthy lifestyles. However, pedestrian safety in a vehicle-dominated transportation network remains a concern and potential barrier to pedestrian mobility, with pedestrian intersection safety being of particular concern. In addition, it is important to understand how pedestrian safety has been affected by the COVID-19 pandemic, perhaps permanently shifting pedestrian injury risks. This research seeks to provide insight into how pedestrian injury risks at intersections have changed as a result of the pandemic by estimating a series pedestrian injury severity models. To do so, unconstrained and partially constrained random parameters multinomial logit models with heterogeneity in the means of random parameters were estimated. Using Florida data, two one-year periods (one year before and one year after the COVID-19 pandemic) were defined based on vehicle miles traveled. The sample includes 3,780 single pedestrian-single vehicle crashes (2,348 from daytime and 1,432 from nighttime). A broad range of variables was considered to assess how the parameters may have shifted between the before and after periods. A series of likelihood ratio tests were conducted to examine the stability of model parameter estimates across the predefined time periods as well as to determine the differences between the daytime and nighttime crash injury severity outcomes. The results show that the nighttime crashes experienced more temporal shifts relative to daytime crashes. The findings also showed that both pedestrian and driver behavior played key temporally-shifting roles before and after the COVID-19 pandemic period. Finally, the out-of-sample simulations suggest that pedestrian injuries have become more severe after the pandemic.

Evaluating the effectiveness of engineering countermeasures at yellow dilemma zone: a driving simulator-based study

ABSTRACT The indecisiveness of drivers at the yellow onset creates a dilemma zone (DZ) upstream of the signalized crossings. The yellow light dilemma negatively influences intersection safety, often leading to rear-end and right-angle collisions. This study explores the impact of upstream road marking and active in-vehicle warnings designed based on DZ boundaries. The prototype concepts of in-vehicle warning systems and upstream road marking were designed and implemented in the driving simulator environment. The driver responses from the experimental setup were captured to evaluate the effectiveness of the designed DZ countermeasures. Study results indicate that implemented DZ countermeasures (i.e. DZ road marking, in-vehicle display warning, and in-vehicle audio warning) significantly decreased the drivers’ crossing probability, resulting in a shorter dilemma zone. However, the proposed countermeasures did not show any improvement in the drivers’ red-light running (RLR) behavior. The driving simulator study showed promising results in reducing aggressive crossing responses at the yellow onset.

Effects of Intersections on the Safety of Horizontal Curves

Both horizontal curves and intersections are generally considered high-risk locations in roadway safety. Although extensive research has been conducted separately on the safety of curves and intersections, the safety performance of curves as affected by their spatial relationship with intersections has not been fully understood. Previous research has not examined this relationship because of the use of limited or pre-existing datasets that did not include intersection data in the analysis. This study addresses these gaps by analyzing the spatial relationship between curves and intersections, utilizing a large dataset of over 8,000 rural curves in Florida. The study performs a systemic analysis using this dataset and six years of statewide crash data of all injury severity levels and develops customized curve Safety Performance Functions based on various spatial relationships between curves and intersections. This study confirms that the previously identified risk factors such as traffic volume, curve radius and length, roadway speed limit, and functional classification have significant impacts on curve safety. More importantly, the study quantifies, for the first time in the literature, the influence of intersections on curves or close to curves on safety, demonstrating that curves with one or more intersections present a higher risk than curves with no intersections. The findings show that the presence of nearby intersections can increase the crash risk for curves with no intersections but can lead to a decrease in crashes for curves with one or multiple intersections. These findings can be utilized to determine high-risk curve locations for systemic safety analysis studies.

The Safety of Society

Complex, ever-changing surroundings can be managed with intelligent transport systems from Jenoptik that tackle speeding, distracted driving, tolling challenges and intersection safety

Analysis of traffic conflicts at big intersection types in urban areas

In the past decades, planners developed intersections for the caroriented city. Above all, they should handle motor vehicle traffic efficiently. Urban areas currently have a high proportion of private cars and, as a result, congestion and high CO2 emissions. At the same time, the importance of and demand for sustainable mobility is increasing. Pedestrians and cyclists are particularly vulnerable as the weakest road users. The goal of transport policy is to achieve “Vision Zero,” i.e., no serious injuries or fatalities in road traffic (Federal Ministry of Digital Affairs and Transport, 2022). Many accidents occur primarily at intersections and junctions. Road traffic authorities in Germany generally use accident data from the accident atlas as the basis for evaluating the road safety of intersections. Planners can improve traffic safety by avoiding critical situations. To this end, an intensive study of the development of conflicts as a precursor to accidents can provide further insights. The research in this project shows that such data on traffic conflicts are not available to road authorities. The project will investigate which and how many conflicts between pedestrian, bicycle, and motor vehicle traffic frequently occur at individual intersection types, such as signalized intersections or traffic circles. The initial goal of the project is to develop a survey concept. In the future, planners should be able to use this to quickly identify risks to pedestrian and bicycle traffic at the types of intersections studied. With the help of vehicle sensor data (e.g. from emergency brake assistants), further findings on the frequency and course of conflicts are to be derived. In addition, a methodology would be developed that will enable traffic planners and municipalities to carry out risk management for intersections in the future in order to improve traffic safety and promote local mobility. From the results of the conflict analysis, we will derive recommendations for transport planning and policy. An action guide will then present the recommendations. The end of the project will be in summer 2024.