Safety Evaluation of Discontinuing Late Nighttime Flash Operations at Signalized Intersections

2013 ◽  
Vol 2398 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Bo Lan ◽  
Raghavan Srinivasan
Keyword(s):  
Safety Evaluation ◽  
Signalized Intersections

scholarly journals Modeling and Application of Pedestrian Safety Conflict Index at Signalized Intersections

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Wei Cheng ◽  
Ning Zhang ◽  
Wei Li ◽  
Jianfeng Xi
Keyword(s):  
Safety Evaluation ◽  
Pedestrian Safety ◽  
Evaluation Study ◽  
Signalized Intersections ◽  
Safety Level ◽  
Intersection Safety ◽  
Road Users ◽  
Traffic Conflict ◽  
Vulnerable Road Users ◽  
The City

Traffic conflict between turning vehicles and pedestrians is the leading cause of pedestrian fatalities at signalized intersections. In order to provide a solution for evaluating intersection safety for vulnerable road users, this paper first determines the most important factors in analyzing pedestrian-vehicle conflict and puts forward a pedestrian safety conflict index (SCI) model to establish a quantitative standard for safety evaluation of two- or multiphase intersections. A safety level system is then designed based on SCI to help categorize and describe the safety condition of intersections applicable to the model. Finally, the SCI model is applied to the evaluation of two intersections in the city of Changchun, the result of which complies with expectation, indicating the model’s potential in providing an improved approach for pedestrian-vehicle conflict evaluation study.

scholarly journals Safety evaluation of left-turn priority phasing at Toronto intersections

2021 ◽  
Author(s):  
Anwarul Haq Dogar
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Safety Evaluation ◽  
Vital Role ◽  
Signalized Intersections ◽  
Side Impact ◽  
Empirical Bayesian ◽  
Left Turn ◽  
Safety Performance Functions ◽  
The City

Traffic accidents cause a huge loss to the society. According to statistics, 50% of all accidents occur at urban intersections and 47% of these are due to left-turn collisions. Countermeasure Implementation at these locations therefore can play a vital role in the improvement of traffic safety. This study illustrates a methodology for evaluation of urban 4-legged signalized intersections treated with left-turn priority phasing. The methodology is applied to three important collisions types: those due to left-turn collisions; those due to left-turn side impact collisions; and all impact types combined collisions. Data used in this analysis were obtained from the City of Toronto. Safety Performance Functions for left-turn and all impact types combined collisions which were developed by the City of Toronto, were calibrated and used in an empirical Bayesian methodology that was employed to estimate the expected frequency of accidents occurring at each intersection in order to evaluate the effectiveness of left-turn priority phasing in reducing this frequency. The results revealed that left-turn priority phasing can be an effective treatment for addressing and reducing the number of collision at signalized intersections. Flashing advance green phasing is more effective in improving safety for two of three types; all left-turn and all impact types combined collisions. Left-turn green arrow (protected/permissive) phasing is more effective for left-turn side impact collisions. By implementing this type of treatment, the number of crashes and the associated monetary loss to society could be significantly reduced.

scholarly journals Safety evaluation of left-turn priority phasing at Toronto intersections

2021 ◽  
Author(s):  
Anwarul Haq Dogar
Keyword(s):  
Traffic Safety ◽  
Traffic Accidents ◽  
Safety Evaluation ◽  
Vital Role ◽  
Signalized Intersections ◽  
Side Impact ◽  
Empirical Bayesian ◽  
Left Turn ◽  
Safety Performance Functions ◽  
The City

Traffic accidents cause a huge loss to the society. According to statistics, 50% of all accidents occur at urban intersections and 47% of these are due to left-turn collisions. Countermeasure Implementation at these locations therefore can play a vital role in the improvement of traffic safety. This study illustrates a methodology for evaluation of urban 4-legged signalized intersections treated with left-turn priority phasing. The methodology is applied to three important collisions types: those due to left-turn collisions; those due to left-turn side impact collisions; and all impact types combined collisions. Data used in this analysis were obtained from the City of Toronto. Safety Performance Functions for left-turn and all impact types combined collisions which were developed by the City of Toronto, were calibrated and used in an empirical Bayesian methodology that was employed to estimate the expected frequency of accidents occurring at each intersection in order to evaluate the effectiveness of left-turn priority phasing in reducing this frequency. The results revealed that left-turn priority phasing can be an effective treatment for addressing and reducing the number of collision at signalized intersections. Flashing advance green phasing is more effective in improving safety for two of three types; all left-turn and all impact types combined collisions. Left-turn green arrow (protected/permissive) phasing is more effective for left-turn side impact collisions. By implementing this type of treatment, the number of crashes and the associated monetary loss to society could be significantly reduced.

scholarly journals PEDESTRIAN SAFETY EVALUATION OF SIGNALIZED INTERSECTIONS USING SURROGATE SAFETY MEASURES

Transport ◽  
2020 ◽  
Vol 35 (1) ◽  
pp. 48-56
Author(s):  
Sankaran Marisamynathan ◽  
Perumal Vedagiri
Keyword(s):  
Safety Evaluation ◽  
Pedestrian Safety ◽  
Signalized Intersections ◽  
Signalized Intersection ◽  
Mixed Traffic ◽  
Model Framework ◽  
Safety Measures ◽  
Severity Level ◽  
Traffic Conditions ◽  
Surrogate Safety Measures

The large proportions of pedestrian fatalities led researchers to make the improvements of pedestrian safety at intersections. Thus, this paper proposes a methodology to evaluate crosswalk safety at signalized intersections using Surrogate Safety Measures (SSM) under mixed traffic conditions. The required pedestrian, traffic, and geometric data were extracted based on the videographic survey conducted at signalized intersections in Mumbai (India). Post Encroachment Time (PET) for each pedestrian were segregated into three categories for estimating pedestrian–vehicle interactions and Cumulative Frequency Distribution (CDF) was plotted to calculate the threshold values for each interaction severity level. The Cumulative Logistic Regression (CLR) model was developed to predict the pedestrian mean PET values in the cross-walk at signalized intersections. The proposed model was validated with a new signalized intersection and the results were shown that the proposed PET ranges and model appropriate for Indian mixed traffic conditions. To assess the suitability of model framework, model transferability was carried out with data collected at signalized intersection in Kolkata (India). Finally, this study can be helpful to rank the severity level of pedestrian safety in the crosswalk and improve the existing facilities at signalized intersections.

scholarly journals Predicting Critical Bicycle-Vehicle Conflicts at Signalized Intersections

2020 ◽  
Vol 2020 ◽  
pp. 1-16
Author(s):  
Alireza Darzian Rostami ◽  
Anagha Katthe ◽  
Aryan Sohrabi ◽  
Arash Jahangiri
Keyword(s):  
Prediction Models ◽  
Model Performance ◽  
Safety Evaluation ◽  
Signalized Intersections ◽  
Video Data ◽  
Sustainable Transportation ◽  
Support Vector ◽  
Monitoring Period ◽  
Crash Data ◽  
Intersection Safety

Continuous development of urban infrastructure with a focus on sustainable transportation has led to a proliferation of vulnerable road users (VRUs), such as bicyclists and pedestrians, at intersections. Intersection safety evaluation has primarily relied on historical crash data. However, due to several limitations, including rarity, unpredictability, and irregularity of crash occurrences, quantitative and qualitative analyses of crashes may not be accurate. To transcend these limitations, intersection safety can be proactively evaluated by quantifying near-crashes using alternative measures known as surrogate safety measures (SSMs). This study focuses on developing models to predict critical near-crashes between vehicles and bicycles at intersections based on SSMs and kinematic data. Video data from ten signalized intersections in the city of San Diego were employed to train logistic regression (LR), support vector machine (SVM), and random forest (RF) models. A variation of time-to-collision called T2 and postencroachment time (PET) were used to specify monitoring periods and to identify critical near-crashes, respectively. Four scenarios were created using two thresholds of 5 and 3 s for both PET and T2. In each scenario, five monitoring period lengths were examined. The RF model was superior compared to other models in all different scenarios and across different monitoring period lengths. The results also showed a small trade-off between model performance and monitoring period length, identifying models with monitoring period lengths of 10 and 20 frames performed slightly better than those with lower or higher lengths. Sequential backward and forward feature selection methods were also applied that enhanced model performance. The best RF model had recall values of 85% or higher across all scenarios. Also, RF prediction models performed better when considering just the rear-end near-crashes with recalls of above 90%.

scholarly journals Safety evaluation of unconventional outside left-turn lane using automated traffic conflict techniques

2016 ◽  
Vol 43 (7) ◽  
pp. 631-642 ◽  
Author(s):  
Yanyong Guo ◽  
Tarek Sayed ◽  
Mohamed H. Zaki ◽  
Pan Liu
Keyword(s):  
Urban Areas ◽  
Safety Evaluation ◽  
Signalized Intersections ◽  
Video Data ◽  
Contributing Factors ◽  
Left Turn ◽  
Time To Collision ◽  
Traffic Conflicts ◽  
Traffic Conflict ◽  
The Right

The objective of this study is to evaluate the safety impacts of unconventional outside left-turn lane at signalized intersections. New designed unconventional outside left-turn lanes are increasingly used at signalized intersections in urban areas in China. The unconventional outside left-turn lane design allows an exclusive left-turn lane to be located to the right of through lanes to improve the efficiency and increase the capacity of left-turn movements. However, the design also raises some concerns regarding potential negative safety impacts. The evaluation is conducted using an automated video-based traffic conflict technique. The traffic conflicts approach provides better understanding of collision contributing factors and the failure mechanism that leads to road collisions. Traffic conflicts are automatically detected and time to collision is calculated based on the analysis of the vehicles’ positions in space and time. Video data are collected from a signalized intersection in Nanjing, China, where both traditional inside and unconventional outside left-turn lanes are installed on two intersection approaches. The other two approaches have only inside left-turn lanes. The study compared frequency and severity of conflict for left-turning vehicles as well as the percentage of vehicles involved in conflicts from the inside and outside left-turn lanes. The results show that the intersection approaches with outside left-turn lanes had considerably more conflicts compared to approaches without outside left-turn lanes. As well, the approaches with outside left-turn lanes had significantly higher conflict severity than the approaches without outside left-turn lanes. As such, it is recommended that the trade-off between the improved mobility and negative safety impact of outside left-turn lanes be carefully considered before recommending their installation.

Safety Evaluation of the Advanced Stop Assist System in Connected Vehicle Environment

2018 ◽  
Vol 2672 (22) ◽  
pp. 47-57 ◽  
Author(s):  
Gwamaka Njobelo ◽  
Thobias Sando ◽  
Soheil Sajjadi ◽  
Enock Mtoi ◽  
Eren Erman Ozguven ◽  
...  
Keyword(s):  
Safety Evaluation ◽  
Signalized Intersections ◽  
Simulation Software ◽  
Sensitivity Analyses ◽  
Dominant Factor ◽  
Connected Vehicle ◽  
Market Penetration ◽  
Test Bed ◽  
Dilemma Zone ◽  
Advisory Speed

Although traffic signals are installed to reduce the overall number of collisions at intersections, certain types, in particular, rear-end collisions are increasing due to signalization. One dominant factor associated with rear-end crashes is the indecisiveness of the driver, especially in the dilemma zone. An advisory system to help the driver make the stop-or-pass decision would greatly improve intersection safety. This study proposes and evaluates an Advanced Stop Assist System (ASAS) at signalized intersections by using Vehicle-to-Infrastructure (V2I) communication. The proposed system utilizes communication data, received from roadside equipment, to provide approaching vehicles with vehicle-specific advisory speed messages to prevent vehicle hard-braking at a yellow or red signal. A simulation test bed was modeled using VISSIM, a microscopic simulation software, to evaluate the effectiveness of the proposed system. The results demonstrate that at full market penetration (100% saturation of vehicles equipped with on-board communication equipment), the proposed system reduces the number of hard-braking vehicles by nearly 50%. Sensitivity analyses of market penetration rates also show a degradation in safety conditions at penetration rates lower than 40%. The results suggest that a penetration rate of at least 60% is required for the proposed system to minimize rear-end collisions and improve safety at the signalized intersections.

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