Road safety analysis of urban roads. Case study of an Italian municipality

Attention to the most vulnerable road users has grown rapidly over recent decades. The experience gained reveals an important number of fatalities due to accidents in urban branch roads. In this study, an analytical methodology for the calculation of urban branch road safety is proposed. The proposal relies on data collected during road safety inspections; therefore, it can be implemented even when historical data about traffic volume or accidents are not available. It permits us to identify geometric, physical, functional, and transport-related defects, and elements which are causal factors of road accidents, in order to assess the risk of death or serious injuries for users. Traffic volume, average speed, and expected consequences on vulnerable road users in case of an accident allow us to calculate both the level of danger of each homogeneous section which composes the road, and the hazard index of the overall branch. A case study is presented to implement the proposed methodology. The strategy proposed by the authors could have a significant impact on the risk management of urban roads, and could be used in decision-making processes to design safer roads and improve the safety of existing roads

A New Traffic Conflict Measure for Electric Bicycles at Intersections

As electric bicycles (e-bikes) are becoming popular in China, concerns have been raised about their safety conditions. A traffic conflict technique is commonly used in traffic safety analysis, and there are many conflict measures designed for cars. However, e-bikes have high flexibility to change speed and trajectories, which is different from cars, so the conflict measures defined for e-bikes need to be independently explored. Based on e-bike driving characteristics, this paper proposes a new measure, the Integrated Conflict Intensity (ICI), for traffic conflicts involving e-bikes at intersections. It measures the degree of dangerousness of a conflict process, with consideration of both conflict risk and conflict severity. Time to collision is used to measure the conflict risk. Relative kinetic energy is used to measure the conflict severity. ICI can be calculated based on video analysis. The method of determining ICI thresholds for three conflict levels (serious, less serious, and slight) and two conflict types (conflicts between two e-bikes, and conflicts between an e-bike and a car) is put forward based on the questionnaires about safety perception of e-bike riders, which is regarded as the criterion of e-bike safety conditions at intersections. The video recording and a questionnaire survey about conflicts involving e-bikes at intersections have been conducted, and the unified thresholds applicable to different intersections have been determined. It is verified that ICI and its thresholds meet the criterion of e-bike safety conditions. This work is expected to be used in the selection of intersections for safety improvement of e-bike traffic.</p

A NEW SIMULATION-BASED CONFLICT INDICATOR AS A SURROGATE MEASURE OF SAFETY

Traffic safety is one of the most essential aspects of transportation engineering. However, most crash prediction models are statistically-based prediction methods, which require significant efforts in crash data collection and may not be applied in particular traffic environments due to the limitation of data sources. Traditional traffic conflict studies are mostly field-based studies depending on manual counting, which is also labor-intensive and oftentimes inaccurate. Nowadays, simulation tools are widely utilized in traffic conflict studies. However, there is not a surrogate indicator that is widely accepted in conflict studies. The primary objective of this research is to develop such a reliable surrogate measure for simulation-based conflict studies. An indicator named Aggregated Crash Propensity Index (ACPI) is proposed to address this void. A Probabilistic model named Crash Propensity Model (CPM) is developed to determine the crash probability of simulated conflicts by introducing probability density functions of reaction time and maximum braking rates. The CPM is able to generate the ACPI for three different conflict types: crossing, rear-end and lane change. A series of comparative and field-based analysis efforts are undertaken to evaluate the accuracy of the proposed metric. Intersections are simulated with the VISSIM micro simulation and the output is processed through SSAM to extract useful conflict data to be used as the entry into CPM model. In the comparative analysis, three studies are conducted to evaluate the safety effect of specific changes in intersection geometry and operations. The comparisons utilize the existing Highway Safety Manual (HSM) processes to determine whether ACPI can identify the same trends as those observed in the HSM. The ACPI outperforms time-to-collision-based indicators and tracks the values suggested by the HSM in terms of identifying the relative safety among various scenarios. In field-based analysis, the Spearman’s rank tests indicate that ACPI is able to identify the relative safety among traffic facilities/treatments. Moreover, ACPI-based prediction models are well fitted, suggesting its potential to be directly link to real crash. All efforts indicate that ACPI is a promising surrogate measure of safety for simulation-based studies

Integrating spatial and temporal approaches for explaining bicycle crashes in high-risk areas in Antwerp (Belgium)

The majority of bicycle crash studies aim at determining risk factors and estimating crash risks by employing statistics. Accordingly, the goal of this paper is to evaluate bicycle-motor vehicle crashes by using spatial and temporal approaches to statistical data. The spatial approach (a weighted kernel density estimation approach) preliminarily estimates crash risks at the macro level, thereby avoiding the expensive work of collecting traffic counts; meanwhile, the temporal approach (negative binomial regression approach) focuses on crash data that occurred on urban arterials and includes traffic exposure at the micro level. The crash risk and risk factors of arterial roads associated with bicycle facilities and road environments were assessed using a database built from field surveys and five government agencies. This study analysed 4120 geocoded bicycle crashes in the city of Antwerp (CA, Belgium). The data sets covered five years (2014 to 2018), including all bicycle-motorized vehicle (BMV) crashes from police reports. Urban arterials were highlighted as high-risk areas through the spatial approach. This was as expected given that, due to heavy traffic and limited road space, bicycle facilities on arterial roads face many design problems. Through spatial and temporal approaches, the environmental characteristics of bicycle crashes on arterial roads were analysed at the micro level. Finally, this paper provides an insight that can be used by both the geography and transport fields to improve cycling safety on urban arterial roads

Reviewing traffic conflict techniques for potential application to developing countries

The economic and social costs due to road crashes are disproportionately higher in developing countries. In addition, underreporting, coupled with an incomplete and inconsistent recording of reported crashes is a major issue in such settings. A brief outline of the dimension of road safety problems in developing countries and the most common limitations of existing crash databases is given in the paper. The challenges in applying traditional approaches for traffic safety evaluation and initiatives are also discussed. Diagnosis of road safety problems using traffic conflict techniques has received considerable research interest and has gained acceptance as a proactive surrogate measure in developed countries. Significant studies have been accomplished to develop, validate and apply different surrogate indicators for the estimation of traffic conflicts, as well as an assessment of the safety problem in different road geometric and operating conditions. This has provided a substitute for the historical crash records in traffic safety research. The main objective of this paper is to assess the application potentiality of this surrogate safety measures to address safety issues in developing countries. To do that, this paper critically reviews and synthesizes the different indicators of surrogate safety measures. The main principles, as well as advantages and disadvantages of the major indicators and prospects of application, are presented here. Finally, future research directions for road traffic safety assessment are outlined in the perspective of understanding the most concerning human issue due to traffic crashes in developing countries

Use of Harsh-Braking Data from Connected Vehicles as a Surrogate Safety Measure

Traffic safety may be analyzed with the use of surrogate safety measures, measures of safety that do not incorporate collision data but rather rely on the concept of traffic conflicts. Use of these measures provides several benefits over use of more traditional analysis methods with historical crash data. Surrogate measures eliminate the need to wait for crashes to occur to conduct a safety analysis. The amount of time required for enough crash data to accumulate can be significant, delaying safety analyses. Similarly, these measures allow for safety analysis to be conducted prior to crashes occurring, potentially calling attention to hazardous areas which may be altered to prevent crashes. In addition to these benefits, traffic conflicts occur much more frequently than collisions, generating many more data points which in turn make statistical methods of analysis more effective. Evaluating surrogate safety measures for a particular transportation network is most effectively done with the use of traffic microsimulation or with connected vehicle data. Traffic microsimulation (such as the use of PTV VISSIM) will generate kinematic data that may then be used for computation of surrogate safety measures. A significant amount of research has been done on this topic, resulting in the establishment of algorithms for calculation of several different surrogate measures and validation of these measures. Kinematic data from connected vehicles has also been used for the calculation of surrogate safety measures. One data point collected by connected vehicles is harsh braking events which could serve as a surrogate safety measure. Because drivers usually brake more gently if given the opportunity to do so, harsh braking events indicate that a traffic conflict has occurred or is about to occur. Such events take away the driver’s opportunity to brake gently. This research establishes statistical models which relate harsh braking events to crashes on intersections and segments in Salt Lake City, Utah. The findings indicate that harsh braking events have the effect of reducing expected crashes because they represent traffic conflicts which were remedied through the use of harsh braking as an evasive action. The presence of schools and the presence of left turn lanes were also found to be statistically significant crash predictors. In addition to this research work a paper outlining the existing state of safety analysis with surrogate safety measures and evaluating the usefulness and practicality of various existing measures is presented

Advances and Applications of Computer Vision Techniques in Vehicle Trajectory Generation and Surrogate Traffic Safety Indicators

The application of Computer Vision (CV) techniques massively stimulates microscopic traffic safety analysis from the perspective of traffic conflicts and near misses, which is usually measured using Surrogate Safety Measures (SSM). However, as video processing and traffic safety modeling are two separate research domains and few research have focused on systematically bridging the gap between them, it is necessary to provide transportation researchers and practitioners with corresponding guidance. With this aim in mind, this paper focuses on reviewing the applications of CV techniques in traffic safety modeling using SSM and suggesting the best way forward. The CV algorithm that are used for vehicle detection and tracking from early approaches to the state-of-the-art models are summarized at a high level. Then, the video pre-processing and post-processing techniques for vehicle trajectory extraction are introduced. A detailed review of SSMs for vehicle trajectory data along with their application on traffic safety analysis is presented. Finally, practical issues in traffic video processing and SSM-based safety analysis are discussed, and the available or potential solutions are provided. This review is expected to assist transportation researchers and engineers with the selection of suitable CV techniques for video processing, and the usage of SSMs for various traffic safety research objectives

Evaluating traffic safety network screening: an initial framework utilizing the hierarchical Bayesian philosophy

Highway crashes result in over 40,000 deaths per year (500,000 worldwide). Their impact on the national economy is estimated at more than 230 billion dollars. Highway safety is the top priority of the United States Department of Transportation (US DOT). Funds dedicated to the problem are expected to increase substantially.;Highway safety is a multidisciplinary issue. An important tool is the safety improvement candidate location (SICL) list. SICL lists list high crash locations for potential mitigation. SICL lists are developed using crash data. Crash frequency, rate, or loss is used to rank the worst locations. Classical statistical techniques are applied. In some cases, simple frequency analyses are used to draw attention to problem locations.;Simple ranked lists suffer from methodological and practical limitations. Chief among these is the inability to identify sites with promise , sites where mitigation has the best chance of success. Agencies representing engineering and enforcement generally examine top sites prior to resource dedication. This is resource intensive and efforts of different safety interests are often not well coordinated.;For over 20 years, empirical Bayesian (EB) has been proposed to address these limitations. EB identifies sites where mitigation might be most effective, increases estimate confidence, and provides information on relative site safety. EB is being widely implemented at the national level. State and local agencies continue SILL development based on long-standing procedures.;EB allows decision makers to more reliably estimate the crash reduction potential at specific sites. However, EB requires development of safety performance functions for road type classes. The technique also requires a priori development of accident modification factors. These requirements add significant expense.;Powerful computers and advanced statistical sampling techniques allow hierarchical Bayesian statistics to be applied to highway safety. Hierarchical Bayesian eliminates the need for a priori functions and factors. This approach can readily incorporate additional information. It can also explicitly identify important relationships between causal factors and safety performance. The approach uses data to define results, based on an analyst-specified level of uncertainty. This dissertation discusses SICL list development and evaluates the potential of Bayesian statistics to improve their utility

Surrogate Measures of Safety with a Focus on Vulnerable Road Users : An exploration of theory, practice, exposure, and validity

Surrogate measures of safety (SMoS) are meant to function as tools to investigate traffic safety. The term surrogate indicates that these measures do not rely on crash data; instead, they focus on identifying safety critical events (or near-crashes) in traffic, which can be used as an alternative to crash records. The overall aim of this thesis is to explore which SMoS are suitable when analysing the safety of vulnerable road users (pedestrians and cyclists). The thesis attempts to answer this question using two different approaches: 1) a literature review focusing on existing surrogate measures and how well they consider vulnerable road users from a theoretical perspective, and 2) four observational studies which focus on the validity of SMoS and their relation to exposure.The literature review focuses on identifying existing SMoS, and on two main aspects when evaluating their suitability for analysing the safety of vulnerable road users. Firstly, if the indicators theoretically are able to measure both the risk of collision and the potential for injury should a collision occur, and secondly, to what extent vulnerable road users were included in previous validation studies. The findings from the literature review are that the most commonly used indicators (Time to Collision Minimum and Post Encroachment Time) are also the most validated, but that they have several theoretical limitations, mainly that they to do not measure injury potential and that they measure the severity of an event based on the outcome rather than the initial conditions or potential/observed evasive actions. There are also several indicators which theoretically are more suitable but instead lack validation studies.The observational studies, which make up the second part of this thesis, consist of an attempt at a large-scale validation study, followed by several studies which focus on the shortcomings discovered in the first attempt. The large-scale study is based on three weeks of video recordings made at 26 signalized intersections in seven European countries. The analysis of these videos resulted in three major findings. Firstly, the lack of comparable crash records made any large-scale validation attempts impossible. Secondly, the lack of comparability between the critical events identified by human observers and those identified by computer calculations made it infeasible to perform a long-term analysis. Thirdly, there is a significant relationship between meetings and critical events identified using Time to Collision Minimum and Post Encroachment Time, which suggests that some of the benefit of using those (and other indicators) might originate from their inherent connection to simple meetings between road users (i.e. exposure). Following these results, the thesis presents a limited validation study based solely on the Scandinavian intersections followed by a suggestion for how a relative approach to validity might offer a potentially easier way of evaluating SMoS in the future. The results from these studies indicate that Time to Collision Minimum can measure safety to at least some extent, while Post Encroachment Time measures it to a lesser extent. Due to the strong connection between critical events and meetings, the thesis also explores how a meeting between road users can be defined and how understanding what constitutes an opportunity for a crash might help to explain the so-called safety-in-numbers effect, as well as how future SMoS studies should consider meetings