Collision Prediction Research Articles

Spatial Effects on Zone-Level Collision Prediction Models

A recent study developed a set of zone-level negative binomial collision prediction models to investigate the relationship between various transportation and sociodemographic characteristics and overall roadway safety. The developed models used data from Metro Vancouver, British Columbia, Canada, and considered the effect of Poisson variations and heterogeneity (extra variation) on collision occurrence. This study aims to evaluate spatial effects on the occurrence of collisions and to check whether the inclusion of spatial variables can improve the goodness of fit and inference capability of those previously developed prediction models. Transit-reliant and application-based collision prediction models with spatial correlations were developed by using the WinBUGS software. The convergence of the developed models was tested by trace plots of the parameter estimated, the Brooks–Gelman–Rubin statistics, and ratios of Monte Carlo errors relative to the standard deviations of the estimates. The results showed that incorporation of the spatial correlations affected the parameter estimates, the values of dispersion parameters and intercepts, and also the t-statistics. The effect of the main exposure variable on all of the models for total, severe, and property-damage-only collisions was found to be smaller under spatial models. The smaller values of the exponents of the main exposure variable confirmed the assumption that spatial effects need to be considered in collision prediction models to mitigate any potential bias associated with model misspecification.

Comparing the road safety of neighbourhood development patterns: traditional versus sustainable communities

The Canada Mortgage and Housing Corporation (CMHC) has been researching a sustainable community development pattern — the Fused Grid road network. This paper reports on research to compare the road safety level of the Fused Grid with four other networks, including: traditional (1) grid and (2) culs-de-sac patterns, and, recently developed (3) 3-way offset and (4) Dutch sustainable road safety (SRS) patterns. Community-based, macro-level collision prediction models were developed and applied with data from Vancouver, Ottawa, and Victoria. The research used standard experimental design methods, including: control-trigger variables, sensitivity analysis, and cross-sectional analysis. Statistically significant results were obtained, and suggested that neighbourhoods built following CMHC's Fused Grid road network pattern would realize a 30 to 60% higher level of road safety than the commonly-used grid and culs-de-sac patterns, and a level of safety comparable to the 3-way offset pattern. Further research topics were recommended.

A high efficiency orbit screening method for space debris collision prediction

在航天器碰撞预警工作中, 为节省计算时间, 需要从大量空间目标中筛选出 可能的危险目标, 计算碰撞概率等参量并进行风险评估. 通常采用的筛选方 法包括高度筛选、几何筛选和时间筛选三步, 不同文献中后两步筛选的算 法略有不同, 同时各方法均难以实现预报三天的快速碰撞预警. 本文通过充 分考虑一阶摄动项对目标轨道的影响, 改进了时间筛选算法, 并在其后增加 了距离筛选, 将筛除比例从通常的大约99%提高到99.97%, 为实现快速碰 撞预警工作提供了理论支持. 通过对实测数据的计算比较, 验证了方 法的正确性及高效性.

S181011 移動小物体の自動車用自動衝突回避システム([S181]交通事故回避支援技術の開発とその課題)

Automatic collision avoidance system of ITS is studied in this paper. There are many subjects to be solved in the automatic collision avoidance systems. To clarify the avoidance characteristics in a situation of a pedestrian walking into the road, the computer simulation is conducted. In the analysis, automatic steering methods with the vehicle velocity, the pedestrian velocity, time to collision and the collision prediction position of the vehicle front part are discussed.

Assessing Mobility and Safety Impacts of a Variable Speed Limit Control Strategy

With the recent advances in active transportation and demand management, variable speed limits (VSLs) have been identified as an active traffic management strategy for improving freeway mobility and safety. Several heuristic VSL strategies have been proposed and evaluated. This paper proposes a model predictive VSL control strategy and evaluates its safety and mobility impacts. The strategy uses second-order traffic flow models to predict the traffic state and to provide a speed for optimizing corridor operational performance. A sensitivity analysis of the VSL update frequency and the safety constraints for the VSL strategy was performed to determine the best scenario in terms of safety and mobility. A stretch of Whitemud Drive, an urban freeway corridor in Edmonton, Alberta, Canada, was selected as the study area. The proposed VSL strategy was implemented in the microsimulation platform with a special software module. A real-time collision prediction model was developed for the same study area by using a matched case-control logistic regression technique to estimate the collision probability for each scenario. The results indicated that the proposed VSL control strategy can improve safety by approximately 50% and mobility by approximately 30%. A VSL update frequency of 5 min and a maximum speed difference of 10 km/h between successive time steps yielded the best performances. This finding can be useful for field implementation of VSL control.

Dynamic Modeling of Driver Control Strategy of Lane-Change Behavior and Trajectory Planning for Collision Prediction

This paper introduces a dynamic model of the driver control strategy of lane-change behavior and applies it to trajectory planning in driver-assistance systems. The proposed model reflects the driver control strategies of adjusting longitudinal and latitudinal acceleration during the lane-change process and can represent different driving styles (such as slow and careful, as well as sudden and aggressive) by using different model parameters. We also analyze the features of the dynamic model and present the methods for computing the maximum latitudinal position and arrival time. Furthermore, we put forward an extended dynamic model to represent evasive lane-change behavior. Compared with the fifth-order polynomial lane-change model, the dynamic models fit actual lane-change trajectories better and can generate more accurate lane-change trajectories. We apply the dynamic models in emulating different lane-change strategies and planning lane-change trajectories for collision prediction. In the simulation, we use the models to compute the percentage of safe trajectories in different scenarios. The simulation shows that the maximum latitudinal position and arrival time of the generated lane-change trajectories can be good indicators of safe lane-change trajectories. In the field test, the dynamic models can generate the feasible lane-change trajectories and efficiently obtain the percentage of safe trajectories by computing the minimum gap and time to collision. The proposed dynamic model and module can be combined with the human-machine interface to help the driver easily identify safe lane-change trajectories and area.

Safety models incorporating graph theory based transit indicators

There is a considerable need for tools to enable the evaluation of the safety of transit networks at the planning stage. One interesting approach for the planning of public transportation systems is the study of networks. Network techniques involve the analysis of systems by viewing them as a graph composed of a set of vertices (nodes) and edges (links). Once the transport system is visualized as a graph, various network properties can be evaluated based on the relationships between the network elements. Several indicators can be calculated including connectivity, coverage, directness and complexity, among others. The main objective of this study is to investigate the relationship between network-based transit indicators and safety. The study develops macro-level collision prediction models that explicitly incorporate transit physical and operational elements and transit network indicators as explanatory variables. Several macro-level (zonal) collision prediction models were developed using a generalized linear regression technique, assuming a negative binomial error structure. The models were grouped into four main themes: transit infrastructure, transit network topology, transit route design, and transit performance and operations. The safety models showed that collisions were significantly associated with transit network properties such as: connectivity, coverage, overlapping degree and the Local Index of Transit Availability. As well, the models showed a significant relationship between collisions and some transit physical and operational attributes such as the number of routes, frequency of routes, bus density, length of bus and 3+ priority lanes.

An empirical tool to evaluate the safety of cyclists: Community based, macro-level collision prediction models using negative binomial regression

Today, North American governments are more willing to consider compact neighborhoods with increased use of sustainable transportation modes. Bicycling, one of the most effective modes for short trips with distances less than 5km is being encouraged. However, as vulnerable road users (VRUs), cyclists are more likely to be injured when involved in collisions. In order to create a safe road environment for them, evaluating cyclists’ road safety at a macro level in a proactive way is necessary. In this paper, different generalized linear regression methods for collision prediction model (CPM) development are reviewed and previous studies on micro-level and macro-level bicycle-related CPMs are summarized. On the basis of insights gained in the exploration stage, this paper also reports on efforts to develop negative binomial models for bicycle–auto collisions at a community-based, macro-level. Data came from the Central Okanagan Regional District (CORD), of British Columbia, Canada. The model results revealed two types of statistical associations between collisions and each explanatory variable: (1) An increase in bicycle–auto collisions is associated with an increase in total lane kilometers (TLKM), bicycle lane kilometers (BLKM), bus stops (BS), traffic signals (SIG), intersection density (INTD), and arterial–local intersection percentage (IALP). (2) A decrease in bicycle collisions was found to be associated with an increase in the number of drive commuters (DRIVE), and in the percentage of drive commuters (DRP). These results support our hypothesis that in North America, with its current low levels of bicycle use (<4%), we can initially expect to see an increase in bicycle collisions as cycle mode share increases. However, as bicycle mode share increases beyond some unknown ‘critical’ level, our hypothesis also predicts a net safety improvement. To test this hypothesis and to further explore the statistical relationships between bicycle mode split and overall road safety, future research needs to pursue further development and application of community-based, macro-level CPMs.

Sensor-Based Robotic Model for Vehicle Accident Avoidance

The best approach for a robot to move in an uncertain environment requires integrated unmanned functions and remotely controlled instructions. We consider the implementation of collision prediction and avoidance system in the mobile robot. The control unit is instructed from the remotely controlled device and the range sensors, which are mounted on the front and back sides. According to the required need, a specific operation is selected and performed. The algorithm based on the sensory information is developed with the distance control approach. The efficiency of the robot is improved by increasing smoothness in motion, removing jerks, achieving accuracy in the navigation, and controlling the distance from the object. To demonstrate such a low cost system, experimental tests have been carried out in the indoor and outdoor environments by moving the robot among different vehicles and objects. Finally, simulation and experimental results have displayed the authenticity of the proposed robotic system.

Applicability of the macro-scale elastic contact theories for the prediction of nano-scaled particle collision with a rigid flat surface under non-adhesive and weakly-adhesive conditions

Applicability of the macro-scale elastic contact theories for the prediction of the collision dynamics involving nano-sized particles is examined. Essential parameters controlling the nano-scale collision are found by continuum-based Hertz (Hertz, 1896) and the JKR (Johnson et al., 1971) theories. Collision parameters of Lennard-Jones particles comprised of 2899 and 17,789 molecules onto a rigid flat surface are numerically obtained by a molecular dynamics simulation (MDS) method. MDS results validate the theories in terms of elastic limit velocity, the maximum compression force and the maximum radius of contact area. The elastic limit velocity of the nano-sized particles is accurately predicted by imposing the macro-scale elastic limit criterion. For the maximum compression force acting on the colliding nano-particle, Hertz impact theory shows good agreement with MDS result in both elastic and inelastic collision regimes. The theories incorporated with the correction factor for conforming contact accurately predicted the contact radius. Both theories are valid within the limit of the elastic collision.

Generalization of the collision cone approach for motion safety in 3-D environments

Avoidance of collision between moving objects in a 3-D environment is fundamental to the problem of planning safe trajectories in dynamic environments. This problem appears in several diverse fields including robotics, air vehicles, underwater vehicles and computer animation. Most of the existing literature on collision prediction assumes objects to be modelled as spheres. While the conservative spherical bounding box is valid in many cases, in many other cases, where objects operate in close proximity, a less conservative approach, that allows objects to be modelled using analytic surfaces that closely mimic the shape of the object, is more desirable. In this paper, a collision cone approach (previously developed only for objects moving on a plane) is used to determine collision between objects, moving in 3-D space, whose shapes can be modelled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained and used to derive dynamic inversion based avoidance strategies.

Collision Cones for Quadric Surfaces

The problem of collision prediction in dynamic environments appears in several diverse fields, which include robotics, air vehicles, underwater vehicles, and computer animation. In this paper, collision prediction of objects that move in 3-D environments is considered. Most work on collision prediction assumes objects to be modeled as spheres. However, there are many instances of object shapes where an ellipsoidal or a hyperboloid-like bounding box would be more appropriate. In this paper, a collision cone approach is used to determine collision between objects whose shapes can be modeled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained in the form of analytical expressions in the relative velocity space. For objects of arbitrary shapes, exact representations of planar sections of the 3-D collision cone are obtained.

A method to predict the derailment of rolling stock due to collision using a theoretical wheelset derailment model

A wheelset derailment model on rolling stock was developed to predict train collision-induced derailment. This model is based on the theoretical derailment behaviors of a wheelset under suspension loads. This theoretical derailment model was numerically simulated using commercial dynamics software, wherein it is demonstrated that this model is useful for predicting train collision-induced derailment. Furthermore, this theoretical derailment model was incorporated into a virtual testing model that did not consider wheel–rail contact conditions in order to evaluate useful applications to the derailment prediction of a train collision. The derailment behaviors of this virtual testing model, which were predicted by applying the theoretical derailment model under the condition of no wheel–rail contact, were closely correlated to those derived from simulations that considered surface-to-surface contact conditions.

레벨셋 방법을 이용한 액적 충돌에 대한 수치해석

액적 충돌은 물방울 형성 및 분무 유동 등의 현상을 예측하는데 있어 매우 중요하다. 이러한 액적 충돌은 액적 속도, 충돌 파라미터, 액적 크기비에 영향을 받아, 충돌 후 거동 특성이 결정된다. 충돌 후 액적은 반사, 합일, 스트레칭 분리, 리플렉시브 분리와 같은 거동 특성을 갖는다. 본 연구에서는 레벨셋 방법을 사용하여 충돌 후 액적 거동 특성에 대한 이상유동 해석을 수행하였다. 정면충돌 현상에 대한 2차원 축대칭 해석으로부터 합일 및 리플렉시브 분리 현상을, 비중심충돌 현상에 대한 3차원 해석으로부터 합일, 리플렉시브 분리, 스트레칭 분리 현상을 예측할 수 있었다. 이러한 해석 결과는 기존 실험 및 이론적 연구 결과와 일치하는 결과를 보였다. 또한, 초기 액적의 부피비에 대한 수송 방정식을 사용하여 충돌하는 두 액적의 성분을 추적하였다. 이로부터 크기가 다른 두 액적의 정면충돌에 대한 액적 성분 추적을 통해 액적 거동 및 액적 성분에 대해 분석하였다.

Sustainable road safety: A new (?) neighbourhood road pattern that saves VRU lives

Both the UN (2007) and World Health Organizations (2004) have declared the enormous social and economic burden imposed on society by injuries due to road collisions as a major global problem. While the road safety problem is not new, this prominent global declaration sends an important signal of frustration regarding progress to date on reducing road collisions. It is clear that governments, communities, businesses and the public must discover ways of reducing this burden, especially as it relates to vulnerable road users (VRUs), typically meaning pedestrian and bicyclist road users. Recent comparisons of global VRU collisions statistics suggest that, in addition to mixed land use density, the layout of neighbourhood roads plays a vital role in the encouragement of walkable, safe and quiet, yet accessible and sustainable communities. The purpose of this paper was to: (1) Review the literature concerning sustainable neighbourhood land use and transportation network patterns, increased VRU volumes, and road safety; (2) Present empirical research results on road safety related to VRU volumes; and (3) Present emerging research regarding more sustainable land use and transportation patterns, increased VRU volumes, and road safety. The Dutch Sustainable Road Safety (SRS) Program has produced a number of innovative land use and transportation initiatives for vehicular road users as well as non-vehicular VRUs. Following from the Dutch initiatives, these new 3-way offset, and fused grid neighbourhood patterns appear to not only have positive effects in encouraging mode split (i.e. increasing walking and bicycling, and transit), slowing traffic, and reducing energy consumption and GHG emissions; but also, to hold potential to improve road safety. To test the road safety hypothesis, UBCO researchers evaluated the level of road safety relative to five neighbourhood patterns – grid, culs-de-sac, and Dutch Sustainable Road Safety (SRS) (or limited access), 3-way offset, and fused grid networks. Analysis using standard transportation planning methodology revealed that they would maintain both mobility and accessibility. Analysis using standard road safety analysis methodology further revealed that these 3-way offset, and fused grid patterns would significantly improve road safety levels by as much as 60% compared to prevalent patterns (i.e. grid and culs-de-sac). It is important to note that these results ignore the road safety effects of providing convenient off-road trails along trip desire lines to shift mode choice from auto to non-auto VRU modes. Subject to further research, it is intuitive that shifting trips from auto to pedestrian/bike modes will lead to reduced auto collisions. Hence, these initial results should be considered as conservative estimates, subject to further research. In before and after studies to date, researchers have shown that increasing bicycle use does not lead to a commensurate increase in bicycle collisions, but no predictive relationship has been found in the literature. Therefore, the next steps in this research are to develop collision prediction models that provide insight on VRU mode split and overall road safety.

Numerical simulations of granular dynamics: I. Hard-sphere discrete element method and tests

We present a new particle-based (discrete element) numerical method for the simulation of granular dynamics, with application to motions of particles on small solar system body and planetary surfaces. The method employs the parallel N-body tree code pkdgrav to search for collisions and compute particle trajectories. Collisions are treated as instantaneous point-contact events between rigid spheres. Particle confinement is achieved by combining arbitrary combinations of four provided wall primitives, namely infinite plane, finite disk, infinite cylinder, and finite cylinder, and degenerate cases of these. Various wall movements, including translation, oscillation, and rotation, are supported. We provide full derivations of collision prediction and resolution equations for all geometries and motions. Several tests of the method are described, including a model granular “atmosphere” that achieves correct energy equipartition, and a series of tumbler simulations that show the expected transition from tumbling to centrifuging as a function of rotation rate.

Development of Planning-Level Transportation Safety Models using Full Bayesian Semiparametric Additive Techniques

Recently, several attempts have been made to develop collision prediction models in which spatial dependency is considered. These models recognize the local nature of spatial data by relaxing the regression analysis assumption that the error terms for each observation are independent. The primary objective of this study is to investigate an alternative technique for capturing the spatial variations in the relationship between the number of zonal collisions and potential transportation planning predictors. Spatial relationships are incorporated into the full Bayesian semiparametric additive modeling framework through the covariance of the error terms. The secondary objective of this research study is to build on knowledge of comparing the accuracy of full Bayesian models to that of generalized linear and geographically weighted Poisson regression models. The spatial covariates from the full Bayesian semiparametric additive model indicate that collision frequencies in traffic analysis zones are spatially correlated. The results of accuracy comparison indicate that the spatial models perform better than the conventional generalized linear models. However, mixed results are obtained when the FBSA models were compared to the geographically weighted Poisson regression models.

Transferability of Community-Based Collision Prediction Models for Use in Road Safety Planning Applications

Collision prediction models (CPMs) are statistically developed mathematical models that relate the occurrence of traffic collisions to various traits or explanatory variables of locations and zones. This paper describes the use of several recently developed community-based, macro-level CPMs and model-use guidelines in a CPM transferability case study for spatial and temporal transferability. The objective was to test the model-use guidelines in an application that involved transferring CPMs developed using 1996 data for the Greater Vancouver Regional District (GVRD) for use in the Central Okanagan Regional District (CORD) using 2003 data. The GVRD and CORD are regions located 400 km apart in the Province of British Columbia, Canada. The case study was carried out in two parts. First, CPMs were developed using 2003 data for the City of Kelowna following recommended community-based, macrolevel collision prediction model development guidelines. Second, existing CPMs were transferred from the GVRD to the CORD, using the recommended transferability guidelines. An analysis of the results revealed that macrolevel CPM transferability was possible and no more complicated than microlevel CPM transferability. To facilitate the development of reliable community-based macrolevel collision prediction models, it is recommended that CPMs be transferred rather than developed whenever and wherever communities lack sufficient data of adequate quality.

Cooperative Motion Control of Multiple Autonomous Marine Vehicles: Collision Avoidance in Dynamic Environments

This paper addresses the problem of cooperative motion control (CMC) of multiple autonomous marine vehicles, taking explicitly into account collision avoidance in dynamic environments. A Collision Avoidance System (CAS) for a CMC architecture is proposed that consists of two subsystems: Collision Prediction and Collision Avoidance. Collision Prediction aims at estimating the most probable trajectory of a given obstacle. To this effect, a bank of Kalman filters are run in parallel, with each filter using a different plausible model for obstacle motion. The most probable model is chosen according to a decision algorithm. Each of the vehicle trajectories is then checked for possible collision with the obstacle. Should the possibility of a collision occur, Collision Avoidance is achieved either by controlling the speed of each vehicle along its assigned path or through path re-planing using harmonic potential fields. Because group coordination must be taken into consideration, collision avoidance is implemented using a decentralized system that is suited for multiple heterogeneous vehicles. The paper summarizes the key concepts and the methodology used to implement a Collision Avoidance System for teams of vehicles. The efficacy of the system is assessed in simulation with dynamic models of a group of marine surface craft using NetMarSys, a Cooperative Motion Control Simulator developed at ISR/IST.

Full Bayes Approach to Before-and-After Safety Evaluation with Matched Comparisons: Case Study of Stop-Sign In-Fill Program

The full Bayes (FB) approach has recently been proposed for evaluating road safety treatments in before-and-after studies. In recognition of the advantages of the FB method and because of the lack of sufficient data to develop the safety performance function necessary to conduct an empirical Bayes study, the FB approach is used to determine the effectiveness of the Stop-Sign In-Fill (SSIF) program of the Canadian Insurance Corporation of British Columbia. The SSIF program funds the conversion from uncontrolled residential intersections to two-way stop-controlled intersections in an alternating pattern. This alternating pattern provides consistency in the application of stop signs within a residential neighborhood. Different modeling formulations for the before-and-after evaluation were investigated, and the results were compared with those of the traditional approach. No postprocessing of the results is required to achieve the odds ratio. The FB analysis revealed an overall significant reduction in predicted collision frequency of 51.1% with the credible interval (36.8%, 62.3%) at the 0.95 confidence level. It was also found that incorporating such design features as matched yoked comparison groups in collision prediction models may significantly improve the fit, while reducing the need to account for overdispersion. The results of the traditional technique were compatible with those of the FB approach at the overall level. It seems that the random selection of sites, which reduces the regression-to-the-mean effect, is the reason that both approaches gave relatively similar overall level results. However, the two methods produced quite different results at the zone (site) level.