RESUMEN

OBJECTIVE: The vehicular traffic in the cities is becoming more complex in developing countries like India due to the rising population and rapid urbanization. With the annually increasing road accidents, a study on the effective safety assessment of heterogeneous traffic conditions is needed. The study aims to evaluate the safety of heterogeneous traffic by spotting the critical conflicts with respect to the speed of the involved vehicles. METHODS: The current study proposed Critical Following Speed instead of using a single threshold value for safety assessment in mixed traffic. Critical Following Speed was proposed by comparing the stopping and the available distances between the involved vehicles and used to identify the critical conflicts. With this, the study uses the speeds of both the leading and the following vehicles to judge the nature of the conflict. Three unsignalized four-legged intersections (S-1, S-2, and S-3) and two straight road sections (S-4 and S-5) were selected as the study area in Trichy, India. Post Encroachment Time (PET) and Time to Collison (TTC) were used as surrogate indicators to assess the crossing or merging and rear-end conflicts, respectively. RESULTS: The average PET and TTC values were between 1.25 and 1.73 s in the study locations. The overall percentage of critical conflicts indicated the non-safer crossing and merging maneuvers in three locations. The other two locations were experiencing safe rear-end conflicts, as the percentages of critical conflicts were below 4%. Various combinations of leading and following vehicle types were examined for the contribution of critical conflicts. The proposed methodology was validated with the 4-year accident data and a good relation was obtained. CONCLUSIONS: Fast-moving vehicles were responsible for the less safe maneuvers with a higher collision probability in all the study locations. The correlation between critical conflicts and road accidents shows the effectiveness of the proposed approach in the traffic safety assessments for mixed traffic. This approach could be employed even in countries with homogenous traffic conditions instead of using a single threshold value. The correlations also show the potential of the proposed Critical Following Speed as a surrogate safety indicator for safety evaluation in the future.

Asunto(s)

Accidentes de Tránsito , Conducción de Automóvil , Humanos , Accidentes de Tránsito/prevención & control , Seguridad , Ciudades , India

RESUMEN

A pedestrian was estimated to be killed every 85 min and injured every 7 min on US roads in 2019. Targeted safety treatments are particularly required at urban intersections where pedestrians regularly conflict with turning vehicles. Leading Pedestrian Intervals (LPIs) are an innovative, low-cost treatment where the pedestrian and vehicle usage of the potential conflict area (a crosswalk) is staggered in time to give the pedestrians a head start of a few seconds and reduce the "element of surprise" for right-turning vehicles. The effectiveness of LPI treatment on pedestrian safety is mixed, and most importantly, its effect on vehicle-vehicle conflicts is unknown. This study investigates the before-after effects of LPI treatments on vehicle-pedestrian and vehicle-vehicle crash risk by applying traffic conflict techniques. In particular, this study has developed a quantile regression technique within the extreme value model to estimate and compare crash risks before and after the installation of the LPI treatment. The before-after traffic movement video data (504 h in total) were collected from three signalized intersections in the City of Bellevue, Washington. The recorded movements were analyzed using Microsoft's proprietary computer vision platform, Edge Video Service, and Advanced Mobility Analytics Group's cloud-based SMART SafetyTM platform to automatedly extract traffic conflicts by analyzing road user trajectories. The treatment effect was measured using a Bayesian hierarchical extreme value model with the peak-over threshold approach. For the extreme value model, a Bayesian quantile regression analysis was conducted to estimate the conflict thresholds corresponding to a high (95th) quantile. Odds ratios were estimated for both conflict types using untreated crossing as a control group. Results indicate that the LPI treatment reduces the crash risk of pedestrians as measured by the reduction in extreme vehicle-pedestrian conflicts by about 42%. The LPI treatment has also been found not to negatively affect rear-end conflicts along the approaches leading to the LPI-treated pedestrian crossing at the signalized intersections. The findings of this study further emphasize the effectiveness of video analytics in proactive safety evaluations of engineering treatments.

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Accidentes de Tránsito , Peatones , Humanos , Accidentes de Tránsito/prevención & control , Seguridad , Teorema de Bayes , Ciudades , Caminata

RESUMEN

Pedestrian vehicle conflicts at non-signalized crosswalks are a world-wide safety concern. Although the "pedestrian priority" policy is applied in some regions to improve pedestrian safety, its effect needs further investigation. This study proposes the Lane-based Distance-Velocity model (LDV) to investigate pedestrian-vehicle interaction at non-signalized crosswalks. Compared with the DV model, the LDV model considers the lateral distance between vehicles and pedestrians. Therefore, the LDV model extends the application of the DV model by allowing it to be applied not only on one-lane streets to multi-lane streets. The conflict severities of pedestrian-vehicle interaction in the LDV model are classified into four categories: safe-passage, mild-interaction, potential-conflict and potential-collision. Based on that, pedestrian crossing decisions are graded as safe-crossing, risky-crossing, and dangerous-crossing. The experimental data are collected at a non-signalized crosswalk through drone footage collected in Xi'an City (China) with a Machine Vision Intelligent Algorithm. The model is tested through a case study to evaluate pedestrian crossing safety when interacting with private cars and taxis. Results from the case study suggest that the proposed model works well in the pedestrian-vehicle interaction analysis. Firstly, 87.9% of drivers are willing to provide right-of-way to pedestrians when they have enough time to react and yield. Then, both the DV model and LDV model have reached consistent conclusions: the deliberate violation rate (DVR) of taxi drivers is 22.64%, which is double that of private car drivers. Last, taxis commit a higher percentage of pedestrians' dangerous or risky crossing situations than private cars. Relevant government departments can utilize the results of this study to manage urban traffic better and improve pedestrian safety.

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Peatones , Accidentes de Tránsito/prevención & control , Automóviles , Ciudades , Humanos , Seguridad , Caminata

RESUMEN

Traffic conflict techniques represent the state-of-the-art for road safety assessments. However, the lack of research on transferability of conflict-based crash risk models, which refers to applying the developed crash risk estimation models to a set of external sites, can reduce their appeal for large-scale traffic safety evaluations. Therefore, this study investigates the transferability of multivariate peak-over threshold models for estimating crash frequency-by-severity. In particular, the study proposes two transferability approaches: (i) an uncalibrated approach involving a direct application of the uncalibrated base model to the target sites and (ii) a threshold calibration approach involving calibration of conflict thresholds of the conflict indicators. In the latter approach, the conflict thresholds of the Modified Time-To-Collision (MTTC) and Delta-V indicators were calibrated using local data from the target sites. Finally, the two transferability approaches were compared with a complete re-estimation approach where all the model parameters were estimated using local data. All three approaches were tested for a target set of signalized intersections in Southeast Queensland, Australia. Traffic movements at the target intersections were observed using video cameras for two days (12 h each day). The road user trajectories and rear-end conflicts were extracted using an automated artificial intelligence-based algorithm utilizing state-of-the-art Computer Vision methods. The base models developed in an earlier study were then transferred to the target sites using the two transferability approaches and the local data from the target sites. Results show that the threshold calibration approach provides the most accurate and precise predictions of crash frequency-by-severity for target sites. Thus, for peak-over threshold models, the threshold parameter is the most important, and its calibration improves the performance of the base models. The complete re-estimation of models for individual target sites yields inferior fits and less precise crash estimates than the two transferability approaches since they utilize fewer traffic conflict extremes in their development than the larger dataset utilized in base model development. Therefore, the study results can significantly advance the applicability of traffic conflict models for crash risk estimation at transport facilities.

Asunto(s)

Accidentes de Tránsito , Inteligencia Artificial , Accidentes de Tránsito/prevención & control , Australia , Calibración , Planificación Ambiental , Humanos , Modelos Estadísticos , Seguridad

RESUMEN

Freeway on-ramp merging areas are high-risk areas for motor vehicle crashes and conflicts due to the variety of driving styles, the difference in mainline and ramp traffic states, and factors related to roadway design and traffic control. The emerging Autonomous Vehicle (AV) technologies are expected to bring substantial improvements in ramp merging operations in general, including the possibility to reduce traffic conflicts and crashes by partially or fully eliminating the critical factors related to the human drivers. In order to investigate the potential safety impacts of AVs at on-ramp merging, this study first proposes a novel conflict index in theory as a specific indicator for ramp merging safety. Then, a merging conflict model is introduced to estimate the index value in various cases by considering the interactions between the mainline and ramp vehicles. In order to account for real-world uncertainties and variations in various crash-contributing factors, the proposed approach incorporates Monte-Carlo method and probabilistic distributions calibrated on the empirical freeway data. The developed approach is later applied in a case study with incremental AV market penetration rates to investigate AV safety impacts at on-ramp merging. The results show clear benefits of AVs in reducing the frequency and severity of the critical merging events. In addition, a sensitivity analysis on essential model parameters shows that the merging safety of AVs is closely related to their gap acceptance policy and the proper functioning of the driving systems, providing further insights into the future development of AVs.

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Accidentes de Tránsito , Conducción de Automóvil , Accidentes de Tránsito/prevención & control , Predicción , Humanos , Vehículos a Motor , Seguridad

RESUMEN

Because pedestrian crash rates remain lower than other collision types, surrogate measures such as traffic interactions are now used in road safety research to complement crash history. Using naturalistic data collection, we sought to assess 1) the likelihood of occurrence of interactions between pedestrians and vehicles based on individual and crossing characteristics; and 2) differences in interaction characteristics between children, adult and senior pedestrians. Observations of pedestrian crossing behaviours (n=4687) were recorded at 278 crossings. For recorded interactions (n=843), information was collected to characterize the behaviours of involved parties. A mixed-effect logit regression model was performed to assess the factors associated with interactions. Chi-square tests evaluated differences between age groups and characteristics of observed interactions. Older adults were those more likely to be involved in an interaction event. Bicycle paths, different crossing surface material and one-way streets were significantly associated with fewer interactions with vehicles, while parked vehicles nearby and crossings on arterial roads were significantly associated with more interactions. Children and the elderly (80 years of age or more) did have distinct patterns of interaction, with more careful drivers/cyclists behaviours being observed towards children and lesser regulation compliance towards the elderly. Given the growing emphasis and adoption of active transportation in many cities, the number of interactions between pedestrians and vehicles during street crossings is likely to increase. Educating drivers and pedestrians to respect each other's space requires an understanding of where, between whom, and under what circumstances interactions occur. Such an approach can also help identify which engineering and enforcement programs are needed to ensure safe pedestrian crossings since interactions can be good markers of uncomfortable crossing situations that may deter walking and lead to more collisions.

Asunto(s)

Accidentes de Tránsito/prevención & control , Conducción de Automóvil/psicología , Peatones/psicología , Accidentes de Tránsito/estadística & datos numéricos , Adolescente , Adulto , Factores de Edad , Anciano , Anciano de 80 o más Años , Conducción de Automóvil/educación , Ciclismo/psicología , Distribución de Chi-Cuadrado , Niño , Femenino , Humanos , Modelos Logísticos , Masculino , Persona de Mediana Edad , Peatones/estadística & datos numéricos , Seguridad , Adulto Joven

RESUMEN

This study presents the results of a collision-based full Bayes (FB) before-after (BA) safety evaluation of a newly proposed design for channelized right-turn lanes. The design which is termed "Smart Channels" decreases the angle of the channelized right-turn to approximately 70°. Its implementation is usually advocated to afford drivers a better view of the traffic stream they are to merge with and to allow also for safer pedestrian crossing. The evaluation used data for three treatment intersections and several comparison sites in the city of Penticton, British Columbia. The evaluation utilized FB univariate and multivariate linear intervention models with multiple regression links representing time, treatment, and interaction effects as well as the traffic volumes effects. As well, the models were extended to incorporate random parameters to account for the correlation between sites within comparison-treatment pairs. The results showed that the implementation of the right-turn treatment has resulted in a considerable reduction in the severity and frequency of collisions. Another objective of the paper was to compare the results of the collision-based evaluation with the results of a traffic conflict-based evaluation of the same treatment intersections. The comparison showed remarkable similarity between the overall and the location specific reductions in conflicts and collisions which provides support for using traffic conflicts in BA studies. The results also provide positive empirical evidence that can support the validity of traffic conflict techniques.

Asunto(s)

Accidentes de Tránsito/prevención & control , Conducción de Automóvil , Planificación Ambiental , Accidentes de Tránsito/estadística & datos numéricos , Teorema de Bayes , Colombia Británica , Humanos , Análisis Multivariante , Análisis de Regresión