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Effects on Road Safety of Converting Intersections to Roundabouts: Review of Evidence from Non-U.S. Studies
Abstract and Figures
A meta-analysis of studies reported outside the United States was performed to evaluate the effects on road safety of converting intersections to roundabouts. Twenty-eight studies that provided 113 estimates of effect were evaluated. State-of-the-art techniques of meta-analysis were applied to synthesize evidence from these evaluation studies. A meta-regression analysis was performed, and the possible presence of publication bias was tested and adjusted using the trim-and-fill method. The results show that roundabouts are associated with a 30% to 50% reduction in the number of injury accidents. Fatal accidents are reduced by 50 % to 70 %. Effects on property damage accidents are highly uncertain, but in three-leg intersections, an increase often will occur. Evidence from the evaluation studies, although highly uncertain, suggests that the effect of roundabouts on injury accidents is greater in four-leg intersections than in three-leg intersections, and it is greater in intersections previously controlled by yield signs than in intersections previously controlled by traffic signals. Few studies have evaluated in detail the effects on safety of design parameters for roundabouts. Findings are inconsistent, but the majority of studies find that small roundabouts (a small diameter of the central traffic island) are safer than large roundabouts (a large diameter of the central traffic island).
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... Roundabouts, as core components of urban transportation infrastructure, play a vital role in traffic flow and safety. Elvik [12] demonstrated that roundabouts can effectively reduce the probability of severe traffic accidents. However, the road structure and traffic flow within such scenarios are exceptionally intricate, posing significant challenges for AVs in terms of scene comprehension and intelligent control decision-making. ...
Autonomous driving has witnessed rapid advancement; however, ensuring safe and efficient driving in intricate scenarios remains a critical challenge. In particular, traffic roundabouts bring a set of challenges to autonomous driving due to the unpredictable entry and exit of vehicles, susceptibility to traffic flow bottlenecks, and imperfect data in perceiving environmental information, rendering them a vital issue in the practical application of autonomous driving. To address the traffic challenges, this work focused on complex roundabouts with multi-lane and proposed a Perception Enhanced Deep Deterministic Policy Gradient (PE-DDPG) for Autonomous Driving in the Roundabouts. Specifically, the model incorporates an enhanced variational autoencoder featuring an integrated spatial attention mechanism alongside the Deep Deterministic Policy Gradient framework, enhancing the vehicle’s capability to comprehend complex roundabout environments and make decisions. Furthermore, the PE-DDPG model combines a dynamic path optimization strategy for roundabout scenarios, effectively mitigating traffic bottlenecks and augmenting throughput efficiency. Extensive experiments were conducted with the collaborative simulation platform of CARLA and SUMO, and the experimental results show that the proposed PE-DDPG outperforms the baseline methods in terms of the convergence capacity of the training process, the smoothness of driving and the traffic efficiency with diverse traffic flow patterns and penetration rates of autonomous vehicles (AVs). Generally, the proposed PE-DDPG model could be employed for autonomous driving in complex scenarios with imperfect data.
... When it comes to the roundabout, which is integral to urban traffic infrastructure, Elvik [13] has shown that roundabouts can effectively reduce the probability of serious traffic accidents. However, the intricate interweaving with other road users and exit selection at roundabouts pose significant challenges to automated driving. ...
Traffic scenarios in roundabouts pose substantial complexity for automated driving. Manually mapping all possible scenarios into a state space is labor-intensive and challenging. Deep reinforcement learning (DRL) with its ability to learn from interacting with the environment emerges as a promising solution for training such automated driving models. This study explores, employs, and implements various DRL algorithms, namely Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO), and Trust Region Policy Optimization (TRPO) to instruct automated vehicles' driving through roundabouts. The driving state space, action space, and reward function are designed. The reward function considers safety, efficiency, comfort, and energy consumption to align with real-world requirements. All three tested DRL algorithms succeed in enabling automated vehicles to drive through the roundabout. To holistically evaluate the performance of these algorithms, this study establishes an evaluation methodology considering multiple indicators, i.e., safety, efficiency, comfort and energy consumption level. A method employing the Analytic Hierarchy Process is also developed to weigh these evaluation indicators. Experimental results on various testing scenarios reveal that the TRPO algorithm outperforms DDPG and PPO in terms of safety and efficiency, while PPO performs the best in terms of comfort level and energy consumption. Lastly, to verify the model's adaptability and robustness regarding other driving scenarios, this study also deploys the model trained by TRPO to a range of different testing scenarios, e.g., highway driving and merging. Experimental results demonstrate that the TRPO model trained on only roundabout driving scenarios exhibits a certain degree of proficiency in highway driving and merging scenarios. This study provides a foundation for the application of automated driving with DRL.
... A study was conducted by converting cross intersections to roundabouts which showed that the total crash rate decreased by 60%, fatal crashes were eliminated and injury crashes were reduced by 82% (Cunningham, 2007). Another study found that such conversions typically result in a 30% to 50% reduction in the number of injury accidents and a 50 % to 70 % reduction in fatal accidents (Elvik, 2003). But given the cost and temporary traffic disruptions associated with constructing a roundabout intersection, it is vital to assess its long-term viability and effectiveness. ...
... He also highlighted the methodology of traffic volumes from different approach roads, which were collected using video graphics techniques and analysed for peak hour traffic volumes [6]. Elvik, (2003) showed that roundabouts reduce the number of injury accidents by 30% to 50% and fatal accidents by 50% to 70% [1]. ...
The growth rate of vehicles is increasing in most metropolitan areas, and as a result, traffic congestion is also increasing, particularly at intersections. Traffic congestion is one of the major problems faced by most of the developing countries despite the measures taken to mitigate and reduce it. In order to overcome traffic congestion, especially in four-way intersections with increasing growth rate of vehicles, roundabout design is a popular traffic management solution in urban areas. In most countries, roundabouts have been widely adopted as an alternative to signalized intersections due to their ease of operation with fewer conflict points. In a metropolitan city like Chennai, there are numerous areas facing traffic congestion. This study aims to design a roundabout for a four-armed intersection located at one of the most congested areas in Chennai, India - Porur Junction. It is a four-armed intersection with traffic on all approach roads and controlled by a signalized intersection. The effective solution would be an elevated roundabout bridge by connecting the major roads towards Poonamallee and Guindy with a two lane road and the minor roads towards Kundrathur and Arcot Road with two separate lanes, one for entering and the other for exiting the junction. The efficiency of the elevated roundabout bridge is that it has speed breakers in the entry ramp which slows down the vehicle & has a central island structure which is used to effectively manage the traffic without stopping the vehicles. After passing through the Central Island, vehicles can exit the barrier at a higher speed than the entry speed in a clockwise direction.
... When it comes to the roundabout, which is integral to urban traffic infrastructure, Elvik [13] has shown that roundabouts can effectively reduce the probability of serious traffic accidents. However, the intricate interweaving with other road users and exit selection at roundabouts pose significant challenges to automated driving. ...
Traffic scenarios in roundabouts pose substantial complexity for automated driving. Manually mapping all possible scenarios into a state space is labor-intensive and challenging. Deep reinforcement learning (DRL) with its ability to learn from interacting with the environment emerges as a promising solution for training such automated driving models. This study explores, employs, and implements various DRL algorithms, namely Deep Deterministic Policy Gradient (DDPG), Proximal Policy Optimization (PPO), and Trust Region Policy Optimization (TRPO) to instruct automated vehicles' driving through roundabouts. The driving state space, action space, and reward function are designed. The reward function considers safety, efficiency, comfort, and energy consumption to align with real-world requirements. All three tested DRL algorithms succeed in enabling automated vehicles to drive through the roundabout. To holistically evaluate the performance of these algorithms, this study establishes an evaluation methodology considering multiple indicators such as safety, efficiency, and comfort level. A method employing the Analytic Hierarchy Process is also developed to weigh these evaluation indicators. Experimental results on various testing scenarios reveal that the TRPO algorithm outperforms DDPG and PPO in terms of safety and efficiency, and PPO performs best in terms of comfort level. Lastly, to verify the model's adaptability and robustness regarding other driving scenarios, this study also deploys the model trained by TRPO to a range of different testing scenarios, e.g., highway driving and merging. Experimental results demonstrate that the TRPO model trained on only roundabout driving scenarios exhibits a certain degree of proficiency in highway driving and merging scenarios. This study provides a foundation for the application of automated driving with DRL in real traffic environments.
Background
Road Traffic injuries (RTI) are among the top ten leading causes of death in the world resulting in 1.35 million deaths every year, about 93% of which occur in low‐ and middle‐income countries (LMICs). Despite several global resolutions to reduce traffic injuries, they have continued to grow in many countries. Many high‐income countries have successfully reduced RTI by using a public health approach and implementing evidence‐based interventions. As many LMICs develop their highway infrastructure, adopting a similar scientific approach towards road safety is crucial. The evidence also needs to be evaluated to assess external validity because measures that have worked in high‐income countries may not translate equally well to other contexts. An evidence gap map for RTI is the first step towards understanding what evidence is available, from where, and the key gaps in knowledge.
Objectives
The objective of this evidence gap map (EGM) is to identify existing evidence from all effectiveness studies and systematic reviews related to road safety interventions. In addition, the EGM identifies gaps in evidence where new primary studies and systematic reviews could add value. This will help direct future research and discussions based on systematic evidence towards the approaches and interventions which are most effective in the road safety sector. This could enable the generation of evidence for informing policy at global, regional or national levels.
Search Methods
The EGM includes systematic reviews and impact evaluations assessing the effect of interventions for RTI reported in academic databases, organization websites, and grey literature sources. The studies were searched up to December 2019.
Selection Criteria
The interventions were divided into five broad categories: (a) human factors (e.g., enforcement or road user education), (b) road design, infrastructure and traffic control, (c) legal and institutional framework, (d) post‐crash pre‐hospital care, and (e) vehicle factors (except car design for occupant protection) and protective devices. Included studies reported two primary outcomes: fatal crashes and non‐fatal injury crashes; and four intermediate outcomes: change in use of seat belts, change in use of helmets, change in speed, and change in alcohol/drug use. Studies were excluded if they did not report injury or fatality as one of the outcomes.
Data Collection and Analysis
The EGM is presented in the form of a matrix with two primary dimensions: interventions (rows) and outcomes (columns). Additional dimensions are country income groups, region, quality level for systematic reviews, type of study design used (e.g., case‐control), type of road user studied (e.g., pedestrian, cyclists), age groups, and road type. The EGM is available online where the matrix of interventions and outcomes can be filtered by one or more dimensions. The webpage includes a bibliography of the selected studies and titles and abstracts available for preview. Quality appraisal for systematic reviews was conducted using a critical appraisal tool for systematic reviews, AMSTAR 2.
Main Results
The EGM identified 1859 studies of which 322 were systematic reviews, 7 were protocol studies and 1530 were impact evaluations. Some studies included more than one intervention, outcome, study method, or study region. The studies were distributed among intervention categories as: human factors (n = 771), road design, infrastructure and traffic control (n = 661), legal and institutional framework (n = 424), post‐crash pre‐hospital care (n = 118) and vehicle factors and protective devices (n = 111). Fatal crashes as outcomes were reported in 1414 records and non‐fatal injury crashes in 1252 records. Among the four intermediate outcomes, speed was most commonly reported (n = 298) followed by alcohol (n = 206), use of seatbelts (n = 167), and use of helmets (n = 66). Ninety‐six percent of the studies were reported from high‐income countries (HIC), 4.5% from upper‐middle‐income countries, and only 1.4% from lower‐middle and low‐income countries. There were 25 systematic reviews of high quality, 4 of moderate quality, and 293 of low quality.
Authors' Conclusions
The EGM shows that the distribution of available road safety evidence is skewed across the world. A vast majority of the literature is from HICs. In contrast, only a small fraction of the literature reports on the many LMICs that are fast expanding their road infrastructure, experiencing rapid changes in traffic patterns, and witnessing growth in road injuries. This bias in literature explains why many interventions that are of high importance in the context of LMICs remain poorly studied. Besides, many interventions that have been tested only in HICs may not work equally effectively in LMICs. Another important finding was that a large majority of systematic reviews are of low quality. The scarcity of evidence on many important interventions and lack of good quality evidence‐synthesis have significant implications for future road safety research and practice in LMICs. The EGM presented here will help identify priority areas for researchers, while directing practitioners and policy makers towards proven interventions.
Roundabouts have been viewed as a powerful movement control technique under a particular activity conditions for quite a long time. Single-path roundabouts, the most well-known compose, have just eight potential conflict points. Automobiles are enforced to decrease speeds because of the geometric of the roundabouts. If the roundabouts were designed in an accurate way, they demonstrated to have positive security and utilitarian exhibitions. The purpose of this research was to study the possibility of improving the design of existing roundabouts, comparing different design scenarios (alternatives) via Synchro and finding out the best scenario by analyzing the results of level of service capacity utilization, delay, travel time, speed, number of stops, and fuel consumption. The study area is located at Al Bidaa area; the network studied included the intersection of Blajat Street and Amr Ibn Al Aas Street. The base-year traffic data were obtained from the traffic impact study conducted by Egis Bceom International in October 2009. As the analysis focuses on the year 2030, growth factors and calibration of the traffic volumes were done in accordance with the guidelines set by Kuwait Municipality. The results obtained showed that for intersection 1, the implementation of a roundabout and a ramp (Scenario 2) has the highest impact, especially when considering the amount of emissions reduced. As the traffic reduced due to the ramp, the roundabout flow became more freely with the majority of traffic arriving from Fifth Ring Road. Implementing this scenario decreased the fuel consumption and related emissions by 55% (the highest among other scenarios (an increase in consumption was observed for scenario 3). As for the level of service and capacity utilization, the reduction was almost similar for all scenarios at 60% for the morning peak hour and 52% for the afternoon peak hour.
Connected Autonomous Vehicle (CAV) is considered as a proposal toward sustainable mobility. In order to succeed in a sustainable mobility solution, “CAV” or more precisely “CAV Transport System” should prove to be low energy, safe, and allow better performances than human-driven vehicles. This paper will propose a system architecture for a sustainable CAV Transport System on a standard scenario: crossing a roundabout. Nowadays, roundabouts are very common and practical crossing alternatives to improve the traffic flow and increase safety. This study aims to simulate and analyze the behavior of connected autonomous vehicles crossing a roundabout using a V2I (vehicle-to-infrastructure) architecture. The vehicles are exchanging information with a so-called central signaling unit. All vehicles are exchanging their position, speed, and target destination. The central signaling unit has a global view of the system compared to each ego vehicle (has more local than global information); thus, can safely and efficiently manage the traffic of the vehicles in the roundabout using a standard signaling block strategy. This strategy of decision of the central signaling unit (CSU) is performed by dividing the roundabout into several zones/blocks which can be booked by only one vehicle at a time. A solver, reproducing a vehicle’s behavior and dynamics, computes the trajectory and velocity of each vehicle depending on its surroundings. Finally, a graphical representation is used and implemented to facilitate the analysis and visualization of the roundabout crossing. The vehicle flow performance of the developed traffic control model is compared with SUMO.
The report gives the findings of a study of personal injury accidents at a sample of 84 four-arm roundabouts on main roads in the UK. The study includes small roundabouts and roundabouts of conventional design, in both 30-40 and 50-70 mile/h speed limit zones. Tabulations are given showing accident frequencies, severities, and rates by roundabout type. The accidents are further analyzed by type (entering-circulating, approaching, single-vehicle, etc) and by road-user involvement (cyclist, motorcyclist, pedestrian, etc). The accident frequencies by type are related to traffic flow and roundabout geometry using regression methods. Equations are developed to enable roundabout accidents to be predicted for use in design and appraisal.
Exploring the possible reasons for heterogeneity between studies is an important aspect of conducting a meta-analysis. This paper compares a number of methods which can be used to investigate whether a particular covariate, with a value defined for each study in the meta-analysis, explains any heterogeneity. The main example is from a meta-analysis of randomized trials of serum cholesterol reduction, in which the log-odds ratio for coronary events is related to the average extent of cholesterol reduction achieved in each trial. Different forms of weighted normal errors regression and random effects logistic regression are compared. These analyses quantify the extent to which heterogeneity is explained, as well as the effect of cholesterol reduction on the risk of coronary events. In a second example, the relationship between treatment effect estimates and their precision is examined, in order to assess the evidence for publication bias. We conclude that methods which allow for an additive component of residual heterogeneity should be used. In weighted regression, a restricted maximum likelihood estimator is appropriate, although a number of other estimators are also available. Methods which use the original form of the data explicitly, for example the binomial model for observed proportions rather than assuming normality of the log-odds ratios, are now computationally feasible. Although such methods are preferable in principle, they often give similar results in practice. Copyright © 1999 John Wiley & Sons, Ltd.
The results of a study on the effects on injury accidents of 20 bypass road projects in Norway are reported. Effects were evaluated by means of an observational before-and-after study, controlling for the regression-to-the-mean effect and general areawide trends in the number of accidents. On the average, a statistically significant reduction of 19 percent in the number of injury accidents was found. The two confounding factors controlled in the study did not significantly affect the results. The results of the Norwegian study are consistent with the results of previous studies that evaluated the road safety effects of bypasses. A meta-analysis of 9 evaluation studies, containing a total of 93 estimates of the effects of bypasses, indicated an average reduction of 25 percent in the total number of accidents. Effects did not vary according to accident severity. Note, however, that none of the evaluation studies employed a sufficiently rigorous study design to rule out the possibility that confounding variables not controlled may have influenced the results.
The findings of a 3-year study conducted at Pennsylvania State University for FHWA on the safety and operational performance and geometric characteristics of roundabouts are presented. The study focused on geometric characteristics that influence the safety and operational performance of roundabouts. Accident data (including driver testimonials) were reviewed along with videotapes developed at several roundabouts in Maryland, Florida, and Nevada. Several conclusions were drawn, including the need to improve geometric design on approaches to rural roundabouts to reduce loss-of-control accidents; the need for adequate right-of-way to properly deflect vehicles around the center island; and the need for guidance regarding operating-volume-to-capacity ratios. The findings from the study will assist planners, designers, and engineers in avoiding unnecessary safety hazards and operational failures.
Modern roundabouts are designed to control traffic flow at intersections without the use of stop signs or traffic signals. U.S. experience with modern roundabouts is rather limited to date, but in recent years there has been growing interest in their potential benefits and a relatively large increase in roundabout construction. This interest has created a need for data regarding the safety effect of roundabouts. Changes in motor vehicle crashes following conversion of 23 intersections from stop sign and traffic signal control to modern roundabouts are evaluated. The settings, located in seven states, are a mix of urban, suburban, and rural environments with the urban sample consisting of both single-lane and multilane designs and the rural sample consisting of only single-lane designs. A before-after study was conducted using the empirical Bayes procedure, which accounts for regression to the mean and traffic volume changes that usually accompany conversion of intersections to roundabouts. For the 23 intersections combined, this procedure estimated highly significant reductions of 40 percent for all crash severities combined and 80 percent for all injury crashes. Reductions in the numbers of fatal and incapacitating injury crashes were estimated to be about 90 percent. In general, the results are consistent with numerous international studies and suggest that roundabout installation should be strongly promoted as an effective safety treatment for intersections. Because the empirical Bayes approach is relatively new in safety analysis, the potential of this methodology in the evaluation of safety measures is demonstrated.
Roundabouts are a form of at-grade intersection control that is used frequently around the world and is becoming popular in the United States. Roundabouts are being used to replace two-way and all-way stop-controlled intersections and traffic signals in the United States. Roundabouts have also been used recently in Vail, Colorado, to improve an existing stop-controlled freeway interchange system. In this study, five single-lane roundabouts are studied to assess their safety and operational performance. All five sites were stop-controlled before roundabouts were installed, and overall the sites experienced a reduction in accident frequencies, rates, and also control delay. Aside from a review of safety and delay data before and after installation of the roundabouts, this study includes a comparison of field-measured control delay with that predicted by SIDRA, an analytically based software package that can analyze atgrade sign- and signal-controlled intersections as well as roundabouts. This study will help agencies better understand their ability to predict delay at American roundabouts. Finally, findings are presented regarding the accuracy of the roundabout capacity model contained in the 1997 update to Chapter 10 of the Highway Capacity Manual. Because of the lack of roundabout entries that are operating at capacity in the United States, an approximation of potential capacity based on available gaps in the circulating stream was made. These findings indicate that the manual may be optimistic in its prediction of capacity for single-lane round-abouts in the United States; however, it should be noted that the lack of roundabout entries operating under capacity in the United States only allows for an approximation of field capacity to be made at this time.