Prediction of Traffic Conflicts at Signalized Intersections using SSAM

The use of microsimulation to model the vehicles movement and pedestrian movements within a traffic network is widely undertaken to test and evaluate operational performance of a traffic network under different traffic conditions and control schemes. However, few studies have used microsimulation techniques to study pedestrian-vehicle interactions and potential conflicts, as safety assessment tool. This paper demonstrates the use of microsimulation environment to predict vehicle-vehicle and pedestrian-vehicle conflicts at signalized intersections. A case study from Doha in the State of Qatar was used as a study site. The real-life conflicts were observed and recorded, along with traffic and pedestrians’ data. The studied intersection is then modeled and calibrated using VISSIM microsimulation tool, where vehicles and pedestrians’ trajectories were generated. Then, Surrogate Safety Assessment Model (SSAM) was used to analyze the simulated trajectories to identify potential conflicts within the study area. The results showed that potential conflicts could be reasonably predicted. Moreover, microsimulation can be used to predict the location of potential conflicts while scenario testing and the results can be determined to assess the impact of geometric improvement in reducing potential conflicts.This publication was made possible by an NPRP award [NPRP 8-365-2-150] from the Qatar National Research Fund (a member of Qatar Foundation). The statements made herein are solely the responsibility of the authors

Simulated Conflict Based Safety Evaluation Models for Hetergenous Traffic in Controlled Intersections

In this paper, an attempt is made to investigate how traffic conflicts identified from microsimulation models can be correlated with explanatory variables which have been traditionally used in accident prediction models. In developing countries with heterogenous traffic streams, availability of accident data is limited especially since accidents are rare events.  Such traffic streams normally have some unique attributes like absence of lane discipline, presence of non-motorized vehicles. In urban intersections with such slow-moving traffic streams, conflicts are more useful determinants of intersection safety rather than previous records of accidents since geometry of intersection may be changed from the time to time. Simulated conflict-based safety evaluation models were developed for intersections of Dhaka city. The intersections were modeled in VISSIM after suitable calibration, for 8 hours of peak hour traffic. Surrogate Safety Assessment Model (SSAM) was used to identify the corresponding simulated hourly conflicts from the resulting trajectory files. It was found that hourly simulated conflicts had a significant statistical relationship with observed hourly traffic volume entering the intersection from major and minor roads. Increasing volumes of non-motorized traffic was found to contribute to intersection safety

DEVELOPMENT OF A DESIGN BASED INTERSECTION SAFETY PERFORMANCE EVALUATION TOOL

The purpose of this research is to develop an intersection safety evaluation tool that is capable of assisting designers and planners in the assessment of alternative intersection designs. A conflict exposure model utilizing design hour volumes, intersection configuration and traffic control measures is proposed to achieve this goal. This approach makes use of data typically available for preliminary intersection design. The research goes beyond existing safety performance models which only examine non-directional average daily traffic (ADT) or practices which only account for the geometric and lane configuration of an intersection, such as conflict point analysis. Conflict prediction models are developed for left-turn angle, right-turn, rear end and sideswipe crashes. These models were developed through the analysis of over 1000 simulation scenarios evaluating a full range of approach and turning volumes, lane configurations and traffic control strategies. The quantifiable metrics provided can be used to inform and improve alternative intersection selection processes by differentiating between alternatives based on a surrogate safety performance. This research may be used in screening of intersection alternatives to select the most beneficial design based on objective safety performance metrics

PREDICTION OF PROTECTED-PERMISSIVE LEFT-TURN PHASING CRASHES BASED ON CONFLICT ANALYSIS

Left-turning maneuvers are considered to be the highest risk movements at intersections and two-thirds of the crashes associated with left-turns are reported at signalized intersections. Left-turning vehicles typically encounter conflicts from opposing through traffic. To separate conflicting movements, transportation agencies use a protected-only phase at signalized intersections where each movement is allowed to move alone. However, this could create delays and thus the concept of a protected-permissive phase has been introduced to balance safety and delays. However, the permissive part of this phasing scheme retains the safety concerns and could increase the possibility of conflicts resulting in crashes. This research developed a model that can predict the number of crashes for protected-permissive left-turn phasing, based on traffic volumes and calculated conflicts. A total of 103 intersections with permissive-protected left-turn phasing in Kentucky were simulated and their left-turn related conflicts were obtained from post processing vehicle trajectories through the Surrogate Safety Assessment Model (SSAM). Factors that could affect crash propensity were identified through the Principal Component Analysis in Negative Binomial Regression. Nomographs were developed from the models which can be used by traffic engineers in left-turn phasing decisions with enhanced safety considerations

A Safety and Emissions Analysis of Continuous Flow Intersections

Increasing travel demand, and challenges associated with high percentages of left-turning vehicles, have encouraged the introduction of significant infrastructure advancements. Certain alternative intersection designs, such as continuous flow intersections, median U-turns, and jughandles, eliminate the traditional protected left-turn, increasing the intersection\u27s optional efficiency. While the design and operations of these intersection types have been studied to varying degrees, their safety and emissions-related impacts are not well-understood. This project develops a series of microsimulation models for two continuous flow intersections (CFI) located in Missouri and Colorado, and uses the Surrogate Safety Assessment Model (SSAM) to determine the impact of those designs on the location and type of conflicts compared to conventional signalized intersections. Additionally, an emissions model, CMEM, was used in the analysis of the Colorado study site to determine whether CFIs have the potential to reduce emissions compared to conventional signalized intersections. As hypothesized, the number of total conflicts did decrease upon installation of a CFI for both study sites, despite lane-change conflicts experiencing an insignificant increase at the Loveland, CO study site. While too small of a sample size to provide a definite validation of SSAM, these results show SSAM can accurately predict the types of conflicts likely to occur as well as indicate a reduction in total vehicle conflicts when a conventional signalized intersection is converted into a CFI. Emission rates per mile at the CFI were lower than those at a conventional signalized intersection, most likely due to fewer total stops and lower delay times for users. The CMEM analysis was repeated for four other volume scenarios, varying left-turn demand. Under all scenarios, the CFI performed better than the conventional signalized intersection. This improvement increased as volume increased, showing that the environmental performance of a CFI is less sensitive to demand than a conventional signalized intersection. This project set forth to quantify sustainability benefits to the installation of a CFI for practitioners. Ultimately, this research can aid transportation decision-makers by providing quantitative evidence that CFIs can improve the safety impacts for vehicle users and environmental impacts for the general population in both rural and urban applications

ESTIMATION OF PEDESTRIAN SAFETY AT INTERSECTIONS USING SIMULATION AND SURROGATE SAFETY MEASURES

With the number of vehicles increasing in the system every day, many statewide policies across the United States aim to increase the use of non- motorized transportation modes. This could have safety implications because the interaction between motorists and non-motorists could increase and potentially increasing pedestrian-vehicle crashes. Few models that predict the number of pedestrian crashes are not sensitive to site-specific conditions or intersection designs that may influence pedestrian crashes. Moreover, traditional statistical modeling techniques rely extensively on the sparsely available pedestrian crash database. This study focused on overcoming these limitations by developing models that quantify potential interactions between pedestrians and vehicles at various intersection designs using as surrogate safety measure the time to conflict. Several variables that capture volumes, intersection geometry, and operational performance were evaluated for developing pedestrian-vehicle conflict models for different intersection designs. Linear regression models were found to be best fit and potential conflict models were developed for signalized, unsignalized and roundabout intersections. Volume transformations were applied to signalized and unsignalized conditions to develop statistical models for unconventional intersections. The pedestrian-vehicle conflicting volumes, the number of lanes that pedestrians are exposed to vehicles, the percentage of turning vehicles, and the intersection conflict location (major or minor approach) were found to be significant predictors for estimating pedestrian safety at signalized and unsignalized intersections. For roundabouts, the pedestrian-vehicle conflicting volumes, the number of lanes that pedestrians have to cross, and the intersection conflict location (major or minor approach) were found to be significant predictors. Signalized intersection models were used for bowtie and median U-turn intersections using appropriate volume transformations. The combination of signalized intersection models for the intersection area and two-way unsignalized intersection models for the ramp area of the jughandle intersections were utilized with appropriate volume transformations. These models can be used to compare alternative intersection designs and provide designers and planners with a surrogate measure of pedestrian safety level for each intersection design examined

Analysis of Pedestrian Safety Using Micro-simulation and Driving Simulator

In recent years, traffic agencies have begun to place emphasis on the importance of pedestrian safety. In the United States, nearly 70,000 pedestrians were reported injured in 2015. Although the number only account for 3% of all the people injured in traffic crashes, the number of pedestrian fatalities is still around 15% of total traffic fatalities. Furthermore, the state of Florida has consistently ranked as one of the worst states in terms of pedestrian crashes, injuries and fatalities. Therefore, it is befitting to focus on the pedestrian safety. This dissertation mainly focused on pedestrian safety at both midblock crossings and intersections by using micro-simulation and driving simulator. First, this study examined if the micro-simulation models (VISSIM and SSAM) could estimate pedestrian-vehicle conflicts at signalized intersections. A total of 42 video-hours were recorded at seven signalized intersections for field data collection. The observed conflicts from the field were used to calibrate VISSIM and replicate the conflicts. The calibrated and validated VISSIM model generated the pedestrian-vehicle conflicts from SSAM software using the vehicle trajectory data in VISSIM. The mean absolute percent error (MAPE) was used to determine the optimum TTC and PET thresholds for pedestrian-vehicle conflicts and linear regression analysis was used to study the correlation between the observed and simulated conflicts at the established thresholds. The results indicated the highest correlation between the simulated and observed conflicts when the TTC parameter was set at 2.7 and the PET was set at 8. Second, the driving simulator experiment was designed to assess pedestrian safety under different potential risk factors at both midblock crossings and intersections. Four potential risk factors were selected and 67 subjects participated in this experiment. In order to analyze pedestrian safety, the surrogate safety measures were examined to evaluate these pedestrian-vehicle conflicts. Third, by using the driving simulator data from the midblock crossing scenario, typical examples of drivers\u27 deceleration rate and the distance to crosswalk were summarized, which exhibited a clear drivers\u27 avoidance pattern during the vehicle pedestrian conflicts. This pattern was summarized into four stages, including the brake response stage, the deceleration adjustment stage, the maximum deceleration stage, and the brake release stage. In addition, the pedestrian-vehicle conflict prediction model was built to predict the minimum distance between vehicle and pedestrian. Finally, this study summarized the three different kinds of data that were to evaluate the pedestrian safety, including field data, simulation data, and driving simulator data. The process of combining of field data, simulation data, and simulator data was proposed. The process would show how the researches could evaluate the pedestrian safety by using the field observations, micro-simulation, and driving simulator

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

Simulated surrogate measures to assess the effectiveness of countermeasures at signalized intersections

The traditional method for assessing safety conditions at signalized intersections depends on historical crash data. Difficulty and long waits for data collection as well as lack of reliability, represent some limitations. As a result of safety evaluation using traditional methods, countermeasures may be proposed to improve the degree of safety. This paper aims to assess the effectiveness of countermeasures at signalized intersections using micro-simulation model (VISSM10) software and the Surrogate Safety Assessment Model (SSAM) to deal with traffic conflicts as surrogate measures rather than crash data. The study relied on VISSIM10 to create a trajectory file as input of SSAM to conduct a traffic safety assessment using traffic conflict indicators of time to collision (TTC). Four four-legged signalized intersections in the city of Diwaniya are chosen to assess safety and then propose appropriate countermeasures. Different countermeasures are tested through simulation to estimate their effectiveness using two measures: the increase in time to collision and the percentage reduction in traffic conflicts. The results showed that model calibration reduced the mean absolute error of prevention (MAPE) and improved the fit between both the actual conflicts and simulated conflicts. A validation simulation has been performed compared with the observed conflict. According to the linear regression the number that simulated conflicts which highly related to the number of actual conflicts. Additionally, R2 can be described by the difference in simulated conflicts. Results go with effectiveness based on crash data and promising for unknown ones