Assessing the Effectiveness of an Integrated Speed Management Plan on Highways

Manned speed enforcement has long been used as a safety measure to improve drivers' compliance with posted speed limits on highways. The sustainable presence of police squads at high-risk locations is key to the successful implementation of an enforcement program and is usually supported by other measures, such as educational campaigns, messages, and warnings. The goal of this study is to evaluate the effectiveness of an integrated speed management plan that is focused on manned traffic enforcement at three highway locations near the City of Leduc, Canada. Baseline speed data was collected and used to develop an enforcement deployment schedule. Following a public educational and engagement program, the enforcement plan was implemented. A detailed analysis was conducted for the speed data before, during, and after manned enforcement operations. To account for potential confounding factors, the evaluation method utilized a control site to correct for trends and other effects. The results showed that there was a statistically significant reduction in the average speed of vehicles that ranged from 1.14 to 8.96 km/h while the number of speed violations dropped by up to 25.5% at enforcement locations. Overall, the results from this study demonstrated that implementing an integrated speed management program, with manned enforcement at its core, has a high potential to improve safety by improving compliance, reducing the number of violations, and decreasing the average speeds on highways. The sustained manned enforcement is expected to increase drivers’ compliance with speed limits, which should eventually reduce collisions and improve safety. Keywords: Vehicular Speed, Manned Enforcement, Speed Violations, Safety Impacts, Speed Limit Compliance DOI: 10.7176/CER/13-1-04 Publication date: January 31st 202

PU-Ray: Point Cloud Upsampling via Ray Marching on Implicit Surface

While the recent advancements in deep-learning-based point cloud upsampling methods improve the input to autonomous driving systems, they still suffer from the uncertainty of denser point generation resulting from end-to-end learning. For example, due to the vague training objectives of the models, their performance depends on the point distributions of the input and the ground truth. This causes problems of domain dependency between synthetic and real-scanned point clouds and issues with substantial model sizes and dataset requirements. Additionally, many existing methods upsample point clouds with a fixed scaling rate, making them inflexible and computationally redundant. This paper addresses the above problems by proposing a ray-based upsampling approach with an arbitrary rate, where a depth prediction is made for each query ray. The method simulates the ray marching algorithm to achieve more precise and stable ray-depth predictions through implicit surface learning. The rule-based mid-point query sampling method enables a uniform output point distribution without requiring model training using the Chamfer distance loss function, which can exhibit bias towards the training dataset. Self-supervised learning becomes possible with accurate ground truths within the input point cloud. The results demonstrate the method's versatility across different domains and training scenarios with limited computational resources and training data. This allows the upsampling task to transition from academic research to real-world applications.Comment: 13 pages (10 main + 3 supplement), 19 figures (10 main + 9 supplement), 6 table

A Hybrid Geostatistical Method for Estimating Citywide Traffic Volumes – A Case Study of Edmonton, Canada

Traffic volume information has long played an important role in many transportation related works, such as traffic operations, roadway design, air quality control, and policy making. However, monitoring traffic volumes over a large spatial area is not an easy task due to the significant amount of time and manpower required to collect such large-scale datasets. In this study, a hybrid geostatistical approach, named Network Regression Kriging,has been developed to estimate urban traffic volumes by incorporating auxiliary variables such as road type, speed limit, and network accessibility.Since standard kriging is based on Euclidean distances, this study implements road network distances to improve traffic volumes estimations.A case study using 10-year of traffic volume data collected within the city of Edmonton was conducted to demonstrate the robustness of the model developed herein. Results suggest that the proposed hybrid model significantly outperforms the standard kriging method in terms of accuracy by 4.0% overall, especially for a large-scale network. It was also found that the necessary stationarity assumption for kriging did not hold true for a large network whereby separate estimations for each road type performed significantly better than a general estimation for the overall network by 4.12%

TRA-910: CONNECTED VEHICLE V2I COMMUNICATION APPLICATION TO ENHANCE DRIVER AWARENESS AT SIGNALIZED INTERSECTIONS

This study introduces a Vehicle-To-Infrastructure (V2I) architecture to enhance driver awareness at signalized intersections. The main objectives are to (i) provide a proof-of-concept field experiment on the use of V2I communication architecture at a signalized intersection and (ii) evaluate the impact of V2I communication on improving driver performance while crossing the intersection. The proposed V2I communication application will relay an advisory auditory message to the driver regarding the status of the traffic signal. It is expected that driver behaviour is going to change as a result of the in-vehicle audible message. Consequently, the proposed application will collect additional driver performance indicators which include information on average speed, maximum speed, and the acceleration\deceleration profiles. To understand the impact of the advisory message on changing driver behaviour, a comparison was performed between the indicators with and without the in-vehicle message. Driver behavior was investigated under two scenarios, namely; as the driver heads towards a green signal and as the driver heads towards a red signal. For both scenarios, the results show that the average speed of the driver have changed significantly after turning “on” the in-vehicle messages. In addition, the maximum speed distribution shifted towards a lower value indicating decreases in maximum speeds. Moreover, the difference between the acceleration\deceleration profiles near the intersection when driving with and without the message, while heading towards a red signal, was found to be significant. These preliminary results show that the proposed V2I communication application can have promising impacts on improving driver awareness at signalized intersections

Who, where, when: the demographic and geographic distribution of bicycle crashes in West Yorkshire

Factors associated with cycle safety, including international differences in injury and mortality rates, protective equipment and bicycle training, have been subject to increasing academic interest. Environmental variables associated with cycle safety have also been scrutinised, but few studies have focussed on geographical factors at the local level. This paper addresses this research gap by analysing a geo-referenced dataset of road traffic incidents, taken from the UK's STATS19 dataset (2005 - 2012). We investigate incidents involving cyclists within West Yorkshire. This is an interesting case study area as it has an historically low cycling rate but very ambitions cycling plans following investment from the Department for Transport. West Yorkshire is found to be an unusually risky area for cyclists, with an estimated 53 deaths and 1372 serious injuries per billion kilometres cycled, based on census commuting statistics. This is roughly double the national average. This riskiness varies spatially and temporally, broadly in line with expectations from the previous literature. An unexpected result was that cycling seems to be disproportionately risky for young people in West Yorkshire compared with young people nationally. The case study raises the issue of potential negative health impacts of promoting cycling amongst vulnerable groups in dangerous areas. We conclude by highlighting opportunities for increasing cycling uptake via measures designed primarily to improve safety. The analysis underlying this research is reproducible, based on code stored at https://github.com/Robinlovelace/bikeR

New techniques for developing safety performance functions

While motorized travel provides many benefits, it can also do serious harm in the form of road-related collisions. The problem affects millions of human lives and costs billions of dollars in economic and social impacts every year. The problem could be addressed thorough several approaches with engineering initiatives being recognized as the most sustainable and cost effective. However, the success of the engineering approaches in reducing collision occurrences hinges upon the existence of reliable methods that provide accurate estimates of road safety. Currently, Safety Performance Functions (SPFs) are considered by many as the main tool in estimating the safety levels associated with different road entities. Therefore, the research in this thesis focuses on addressing key issues related to the development of SPFs for i) collision data analysis and ii) collision intervention analysis. Some of the key issues addressed include: 1) adding spatial effects to SPFs thereby recognizing the evident spatial nature of road collisions, 2) fitting hierarchical models to allow inference to be made on more than one level, 3) recognizing the multivariate nature of collisions as most data are available by collision type or severity and modeling the data as such, 4) identifying and accounting for outliers in the development of SPFs, 5) developing a novel evaluation methodology to estimate the effectiveness of safety countermeasures when subject to data limitations, and 6) compare different tools for investigating the safety change in treated sites due to the implementation of safety countermeasures. The applications of the various models have been demonstrated using several collision datasets and/or safety programs. The results provide strong evidence for (i) incorporating spatial effects in SPFs, (ii) clustering road segments or intersections into homogeneous groups (e.g., corridors, zones, districts, municipalities, etc.) and incorporating random cluster parameters in SPFs, (iii) developing robust multivariate models with multiple covariates for modeling collisions by severity and/or type concurrently, and (iv) the effectiveness of the proposed full Bayes safety assessment methods that account for several theoretical and practical issues concurrently. In addition to the improvement in goodness of fit, the proposed models have also improved inference and precision of expected collision frequency.Applied Science, Faculty ofCivil Engineering, Department ofGraduat

Field validation for surrogate safety assessment methodology (SSAM) using a multi-purpose micro-simulation

Several approaches exist for estimating safety ranging from using accident rates to accident prediction models which relate the expected accident frequency at a road location to its traffic and geometric characteristics. In recent years, the usefulness and reliability of accident records has led several researchers to consider surrogate safety measures. Among the most common surrogate measures is the Traffic Conflict Technique (TCT). However, there some shortcomings related to the cost of collecting conflicts data and the reliability of human observers. Several efforts were taken to incorporate safety, in terms of surrogate measures such as TCT, into multipurpose micro-simulations (MPMS). As a result, the Surrogate Safety Assessment Methodology (SSAM) was developed. The main objective of this thesis is to perform a field validation of the SSAM approach using VlSSlM 4.1-12 program. This thesis provides the results of the field validation plan for the Surrogate Safety Assessment Methodology (SSAM) with an aim to compare the predictive safety performance capabilities of the SSAM approach with actual accident experience at Canadian signalized intersections. The validation plan consisted of five tests aiming to quantify the relation between the recorded accidents and simulated conflicts. The first validation test, safety ranking analysis, compares the ranking of intersections from SSAM according to predicted average conflicts rates (ACR) and the ranking of the same intersections using actual accident frequency. The second test repeats the same comparative ranking procedures as test 1, but for sub-sets of accident/conflict types. The third validation test, conflict/accident paired comparison, compares the conflict frequency predicted by SSAM to the actual accident frequency at each intersection. A regression equation that relates actual accidents to the predicted conflicts was developed. The test determines the strength of the relationship between predicted conflicts and actual accidents. The fourth validation test, conflict/accident prediction model comparative analysis, determines whether the conflict prediction model can predict risk in a manner similar to the accident prediction model for intersections with the same characteristics. The comparison included several model applications such as the identification and ranking of accident prone locations. The fifth test repeats the same comparative ranking procedures as test 4, but for sub-sets of accident/conflict types. The results of the five validation tests indicated that the safety measures computed from the simulated conflicts were poorly related to those of actual accidents. In terms of model applications, the results indicate a poor agreement between the identification and ranking of accident prone locations obtained from the conflict/accident prediction models. Furthermore, it was concluded that traffic volumes alone can explain more variation in the occurrence of accidents than simulated conflicts obtained from SSAM. The poor relation between simulated conflicts and actual accidents could be associated with SSAM’s sensitivity to the manner by which an intersection was modeled in VISSIM. A number of validation issues were investigated to demonstrate the sensitivity of SSAM’s output by varying some of the design parameters. The effects of redefining the priority rules, changing the minimum allowable gap size and the effects of changing the lateral clearance parameters were investigated. The results of these investigations showed that the number of conflicts produced by SSAM varied considerably as a result of changing these parameters. As well, it was found that the lane changing logic in VlSSlM had a significant impact on the number of simulated conflicts. In many cases, an abrupt lane changing behavior was noticed. To this time, there is no clear justification for some of the abrupt lane-changing behaviors experienced in some intersections. Although certain measures were taken into account to reduce the effect of that unusual maneuver, this behavior continued to occur and affect the number of conflicts produced by SSAM.Applied Science, Faculty ofCivil Engineering, Department ofGraduat