scholarly journals Safety evaluation of signalized intersections with automated vehicles at various penetration levels based on conflict analysis of simulated traffic

2021 ◽  
Author(s):  
Maria Espinosa
Keyword(s):  
Prediction Models ◽  
Safety Evaluation ◽  
Driving Behavior ◽  
Signalized Intersections ◽  
Automated Vehicles ◽  
Crash Frequency ◽  
Left Turn ◽  
Intersection Safety ◽  
Potential Safety ◽  
Traffic Conflicts

Automated vehicles (AVs) are expected to offer great benefits by potentially reducing crashes. The safety at signalized intersections is influenced by several factors, one of them being the driving behavior. By introducing AVs on the roads, the unpredictability of this factor will potentially decrease and eventually, reduce crashes. By using microsimulation, it was possible to use simulated traffic conflicts as indicators of potential crashes, to analyze the potential safety of signalized intersections in the presence of automated vehicles. The objective was to compare crash frequency for signalized intersections at various AVs penetration levels (0%, 50% and 100%) by using prediction models that relate crashes to conflicts. Furthermore, the effect on crashes of introducing hypothetical left turn treatments was also evaluated. The results indicated that intersection safety may improve in the presence of AVs. However, the safety effects of treatments may be reduced compared to the effects with no AVs.

scholarly journals Safety evaluation of signalized intersections with automated vehicles at various penetration levels based on conflict analysis of simulated traffic

2021 ◽  
Author(s):  
Maria Espinosa
Keyword(s):  
Prediction Models ◽  
Safety Evaluation ◽  
Driving Behavior ◽  
Signalized Intersections ◽  
Automated Vehicles ◽  
Crash Frequency ◽  
Left Turn ◽  
Intersection Safety ◽  
Potential Safety ◽  
Traffic Conflicts

Automated vehicles (AVs) are expected to offer great benefits by potentially reducing crashes. The safety at signalized intersections is influenced by several factors, one of them being the driving behavior. By introducing AVs on the roads, the unpredictability of this factor will potentially decrease and eventually, reduce crashes. By using microsimulation, it was possible to use simulated traffic conflicts as indicators of potential crashes, to analyze the potential safety of signalized intersections in the presence of automated vehicles. The objective was to compare crash frequency for signalized intersections at various AVs penetration levels (0%, 50% and 100%) by using prediction models that relate crashes to conflicts. Furthermore, the effect on crashes of introducing hypothetical left turn treatments was also evaluated. The results indicated that intersection safety may improve in the presence of AVs. However, the safety effects of treatments may be reduced compared to the effects with no AVs.

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.

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.

Safety-Based Left-Turn Phasing Decisions for Signalized Intersections

2017 ◽  
Vol 2619 (1) ◽  
pp. 13-19 ◽  
Author(s):  
Kiriakos Amiridis ◽  
Nikiforos Stamatiadis ◽  
Adam Kirk
Keyword(s):  
Urban Areas ◽  
Primary Objective ◽  
Signalized Intersections ◽  
Safety Performance ◽  
Signal Timing ◽  
Left Turn ◽  
Crash Data ◽  
Intersection Safety ◽  
Traffic Volumes

The efficient and safe movement of traffic at signalized intersections is the primary objective of any signal-phasing and signal-timing plan. Accommodation of left turns is more critical because of the higher need for balancing operations and safety. The objective of this study was to develop models to estimate the safety effects of the use of left-turn phasing schemes. The models were based on data from 200 intersections in urban areas in Kentucky. For each intersection, approaches with a left-turn lane were isolated and considered with their opposing through approach to examine the left-turn–related crashes. This combination of movements was considered to be one of the most dangerous in intersection safety. Hourly traffic volumes and crash data were used in the modeling approach, along with the geometry of the intersection. The models allowed for the determination of the most effective type of left-turn signalization that was based on the specific characteristics of an intersection approach. The accompanying nomographs provide an improvement over existing methods and warrants and allow for a systematic and quick evaluation of the left-turn phase to be selected. The models used the most common variables that were already known during the design phase, and they could be used to determine whether a permitted or protected-only phase would suit the intersection when safety performance was considered.

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 Using Cellular Automata to Investigate Pedestrian Conflicts with Vehicles in Crosswalk at Signalized Intersection

2012 ◽  
Vol 2012 ◽  
pp. 1-16 ◽  
Author(s):  
Xiaomeng Li ◽  
Xuedong Yan ◽  
Xingang Li ◽  
Jiangfeng Wang
Keyword(s):  
Cellular Automata ◽  
Signalized Intersections ◽  
Influential Factors ◽  
Urban Traffic ◽  
Signalized Intersection ◽  
Signal Timing ◽  
Cellular Automata Model ◽  
Intersection Safety ◽  
Traffic Conflicts ◽  
Simulation Results

The operational efficiency and safety of pedestrian flows at intersections is an important aspect of urban traffic. Particularly, conflicts between pedestrians and vehicles in crosswalk are one of the most influential factors for intersection safety. This paper presents a cellular automata model that simulates pedestrian and vehicle crossing behaviors at signalized intersections. Through the simulation, we investigate the effects of different pedestrian signal timing and crosswalk widths on the crosswalk capacity, the number of traffic conflicts between pedestrians and vehicles, and pedestrian delay due to the conflicts. The simulation results indicate that the cellular automata is an effective simulation platform for investigating complex pedestrian-related traffic phenomenon at signalized intersections.

Safety Evaluation of Freight Intermodal Connectors in Tennessee State

2019 ◽  
Vol 2673 (3) ◽  
pp. 237-246
Author(s):  
Deo Chimba ◽  
Emmanuel Masindoki ◽  
Xiaoming Li ◽  
Casey Langford
Keyword(s):  
Traffic Safety ◽  
Statistical Significance ◽  
Safety Evaluation ◽  
Crash Frequency ◽  
Left Turn ◽  
Crash Rates ◽  
Signal Density ◽  
Geometric Factors ◽  
Last Mile ◽  
Average Annual Daily Traffic

This paper evaluates the traffic safety along freight intermodal connectors (FICs), which are also known as “first mile/last mile roadways,” connecting facilities that link freight-intensive land uses to main freight routes. Using Tennessee’s FICs as a case study, the paper digests the safety with reference to crash frequency, crash rates, and statistical significance of attributing traffic and geometric factors. It was found that connectors leading to pipeline terminals have high crash rates (almost double) compared with other type of terminals, whereas port terminal connectors have the lowest safety problem indices. The study established correlative contributing causes of crash frequencies and rates along FICs that included average annual daily traffic, lanes, shoulders, access, and median types. Traffic signal density was found to strongly and significantly affect the probability of crashes, together with the presence of a two-way left-turn lane (TWLTL), which surprisingly tends to decrease the probability of crashes along these connectors. The presence of shoulders along intermodal connectors was found to help reduce the probability of crashes, whereas the presence of curb and gutter tends to increase crash frequency. Analysis indicated that most of the FICs with high crash rates were also operating at a lower traffic operations level of service (LOS), especially for critical movements toward freight facilities because of high truck volumes.

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