Traffic safety has traditionally been measured by analyzing historical accident data, which is a reactive method where a certain number of accidents must occur in order to identify the safety problem. An alternative safety assessment method is to use proximal safety indicators that are defined as measures of accident proximity, which is considered a proactive method. With this method it is possible to detect the safety problem before the accidents have happened. To be able to detect problems in traffic situations in general, microscopic simulation is commonly used. In these models it may be possible to generate representative near-accidents, measured by proximal safety indicator techniques. A benefit of this would be the possibility to experiment with different road designs and evaluate the traffic safety level before reconstructions of the road infrastructure. Therefore has an investigation been performed to test the possibility to identify near-accidents (conflicts) in a microscopic simulation model mimicking the Traffic Conflict Technique developed by Hydén (1987). In order to perform the investigation a case study has been used where an intersection in the city center of Stockholm was studied. The intersection has been rebuilt, which made it possible to perform a before and after study. For the previous design there was a traffic safety assessment available which was carried out using the Traffic Conflict Technique. Microscopic simulation models representing the different designs of the intersection were built in PTV Vissim. In order to evaluate and measure the traffic safety in reality as well as in the microscopic simulation models, a traffic safety assessment was performed in each case. The traffic safety assessment in field for the present design was carried out as a part of this thesis. The main focus of this thesis was the road safety for vulnerable road users. The method to identify conflicts in the simulation model has been to extract raw data output from the simulation model and thereafter process this data in a Matlab program, aiming to mimic the Traffic Conflict Technique. The same program and procedure was used for both the previous and the present design of the intersection. The results from the traffic safety assessment in the simulation model have been compared to the results from the field study in order to evaluate how well microscopic simulation works as an evaluation tool for traffic safety in new designs. The comparison shows that the two methods of conflict identification cannot replace each other straight off. But with awareness of the differences between the methods, the simulation model could be used as an indication when evaluating the level of traffic safety in a road design.

This study adopted the traffic conflict technique, investigated and applied it for evaluation of freeway weaving section safety performance. Conflicts between vehicles were identified based on the state of interactions between vehicles in the traffic stream at microscopic level. The VISSIM microscopic simulation model was employed to simulate traffic operation. Surrogate safety measures were formulated based on deceleration rate required to avoid crash and these simulation-based measures were statistically compared and validated using crash data collected from the same study site. Three study sites located in Houston and Dallas areas were selected. Geometric and traffic data were collected using various technique including the use of traffic surveillance cameras and pneumatic tubes. The study revealed the existence of links between actually observed crashes and the surrogate safety measures. The study findings support the possible the use of microscopic simulation to evaluate safety performance of weaving areas and other transportation facilities.

<p dir="ltr">In 2021, the U.S. experienced over 45,000 road accident fatalities and approximately two million injuries, resulting in both emotional trauma and tangible economic impact. Road safety management traditionally depends on crash data, which though invaluable, is reactive, takes a long time to aggregate and has certain limitations. Traffic conflicts, the most used surrogate measure, promises to enhance road safety estimation without the drawbacks of crash data using a short amount of data collection.</p><p dir="ltr">After decades of debate, a definition for traffic conflicts that can be practically applied (Tarko, 2018, 2021) and a bridge method to estimate number of crashes given conflicts (Tarko, 2018) have emerged. The predictive validity of the bridge method has been successfully demonstrated for naturalistic driving data using a framework to extract conflicts (Tarko & Lizarazo, 2021). The only hurdle remaining for adoption of traffic conflicts to estimate safety at a given location is a means to record trajectories of all road users at that location.</p><p dir="ltr">Traditionally, video cameras and associated image processing techniques have been used to track road users at a given location. Cameras capture a 2D projection of the 3D world, therefore incur a loss of information and cameras are sensitive to ambient light conditions.</p><p dir="ltr">Over the past decade, LiDARs have emerged as an alternative to cameras for tracking road users. The advantage of LiDARs is that they record 3D information directly and are insensitive to ambient light conditions. Furthermore, they are less affected by adverse weather conditions than cameras. Spurred by the adoption by autonomous vehicle manufacturers, LiDAR sensors are projected to achieve cost parity with cameras over the next several years.</p><p dir="ltr">This dissertation explores the various aspects of LiDAR based tracking starting with sensor selection. The simulation work done shows the advantage of a multi-LiDAR setup in effectively covering an intersection. A novel self-aligning procedure to achieve spatial congruity proposed is shown to outperform the state of the art.</p><p dir="ltr">New methods for identifying and removing background points that work even under moderate congestion have been proposed. New methods for clustering the non-background points and estimating a bounding box with proper orientation are proposed. The results of the experiments show that they work better than the corresponding state of the art methods. The rest of the processing follows the framework introduced by (Bandaru, 2016).</p><p dir="ltr">A thorough evaluation of positional accuracy, orientation accuracy and accuracy of estimated vehicle dimensions has been undertaken using data from an instrumented vehicle acting as ground truth to prove that the trajectories generated are of sufficient quality to identify traffic conflicts.</p><p dir="ltr">Further, the framework proposed by (Lizarazo, 2020) has been adopted to identify traffic encounters from the trajectories obtained. A new method to select an alternative trajectory for a vehicle exhibiting an evasive maneuver, used in the counterfactual analysis to estimate time to collision is proposed. Data collected at three different intersections using a LiDAR are processed to extract trajectories and the framework is applied to identify safety relevant events. The spatial distribution of the identified events is compared against the spatial distribution of crashes.</p><p dir="ltr">While the spatial distribution shows promise, the actual number of claimed conflicts was too low. The rare nature of failure caused traffic conflict that can be linked to crashes could be a reason. A more permanent installation is suggested to ascertain the duration required to observe sufficient number of traffic conflicts, that could be used to reliably estimate crashes.</p><p dir="ltr"><b>References:</b></p><p dir="ltr">Bandaru, V. K. (2016). Algorithms for LiDAR Based Traffic Tracking: Development and Demonstration. <i>Open Access Theses</i>. https://docs.lib.purdue.edu/open_access_theses/922</p><p dir="ltr">Lizarazo, C. (2020). <i>Identification Of Failure-Caused Traffic Conflicts in Tracking Systems: A General Framework</i> [PhD Thesis]. Purdue University.</p><p dir="ltr">Tarko, A. (2018). Estimating the expected number of crashes with traffic conflicts and the Lomax Distribution–A theoretical and numerical exploration. <i>Accident Analysis & Prevention</i>, <i>113</i>, 63–73.</p><p dir="ltr">Tarko, A. (2021). A unifying view on traffic conflicts and their connection with crashes. <i>Accident Analysis & Prevention</i>, <i>158</i>, 106187. https://doi.org/10.1016/j.aap.2021.106187</p><p dir="ltr">Tarko, A., & Lizarazo, C. (2021). Validity of failure-caused traffic conflicts as surrogates of rear-end collisions in naturalistic driving studies. <i>Accident Analysis & Prevention</i>, <i>149</i>, 105863.</p>