Real Intersection Research Articles

Traffic Signal Control Optimization Based on Neural Network in the Framework of Model Predictive Control

To improve the effectiveness of model predictive control (MPC) in dynamic traffic signal control strategies, it has been combined with graph convolutional networks (GCNs) and deep reinforcement learning (DRL) technologies. In this study, a neural-network-based traffic signal control optimization method under the MPC framework is proposed. A dynamic correlation matrix is introduced in the predictive model to adapt to the dynamic changes in correlations between nodes over time. The signal control optimization strategy is solved using DRL, where the agent explores the optimal control strategy based on pre-set constraints in the future road environment. The geometric structure and traffic flow data of a real intersection were selected as the simulation validation environment, and a joint simulation was conducted using Python and SUMO. The experimental results indicate that in low-traffic scenarios, the queue length is reduced by more than 2 vehicles compared to the selected comparison methods; in high-traffic scenarios, the queue length is reduced by an average of 17 vehicles. Under the actual traffic data of the intersection, the average speed is increased by 6.4% compared to the fixed timing method; compared to the inductive signal control method, it increases from 9.76 m/s to 11.69 m/s, an improvement of 19.7%, effectively enhancing the intersection signal control performance.

Adaptive Traffic Management Model for Signalised Intersections

As population increases, one of the factors affecting life is traffic. Efficient traffic management has a direct positive impact on issues such as time, carbon dioxide emissions, and fuel consumption. Today, an important parameter under the heading of traffic is the signalling systems for intersections, which are operated with fixed-time, semi-actuated, fully actuated, and fully adaptive control methods. In this study, an adaptive traffic management model is developed for signalised intersections. The adaptive traffic management model developed includes phase extension with minimum and maximum time intervals dependent on density and phase skip features. Additionally, the most distinctive feature of the model is its flexible phase structure rather than a sequential phase. The Heybe intersection, located within the boundaries of Antalya province, is modelled one-to-one in the simulation of urban mobility (SUMO) simulation programme with real intersection data. The developed adaptive traffic management model is applied to the Heybe intersection, and the effects of the model are revealed. Improvements obtained from the SUMO simulation programme were verified through visual inspection, and high-accuracy results were determined. As a result of the studies, it was found that the application of the adaptive traffic management model developed at Heybe intersection, which has approximately 50,000 vehicles passing daily, resulted in a 27.2 % improvement in the average delay per vehicle parameter, a 32.4 % improvement in the average waiting time per vehicle parameter, and a 16.7 % improvement in the average speed per vehicle parameter.

On the Smith–Thom deficiency of Hilbert squares

AbstractWe give an expression for the Smith–Thom deficiency of the Hilbert square of a smooth real algebraic variety in terms of the rank of a suitable Mayer– Vietoris mapping in several situations. As a consequence, we establish a necessary and sufficient condition for the maximality of in the case of projective complete intersections, and show that with a few exceptions, no real nonsingular projective complete intersection of even dimension has maximal Hilbert square. We also provide new examples of smooth real algebraic varieties with maximal Hilbert square.

Average Degree of the Essential Variety

The essential variety is an algebraic subvariety of dimension 5 in real projective space RP8\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb R\\mathrm P^{8}$$\\end{document} which encodes the relative pose of two calibrated pinhole cameras. The 5-point algorithm in computer vision computes the real points in the intersection of the essential variety with a linear space of codimension 5. The degree of the essential variety is 10, so this intersection consists of 10 complex points in general. We compute the expected number of real intersection points when the linear space is random. We focus on two probability distributions for linear spaces. The first distribution is invariant under the action of the orthogonal group O(9)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\ extrm{O}(9)$$\\end{document} acting on linear spaces in RP8\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb R\\mathrm P^{8}$$\\end{document}. In this case, the expected number of real intersection points is equal to 4. The second distribution is motivated from computer vision and is defined by choosing 5 point correspondences in the image planes RP2×RP2\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\mathbb R\\mathrm P^2\ imes \\mathbb R\\mathrm P^2$$\\end{document} uniformly at random. A Monte Carlo computation suggests that with high probability the expected value lies in the interval (3.95-0.05,3.95+0.05)\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$(3.95 - 0.05,\\ 3.95 + 0.05)$$\\end{document}.

Enhancing Traffic Sustainability: An Analysis of Isolation Intersection Effectiveness through Fixed Time and Logic Control Design Using VisVAP Algorithm

This paper addresses the limitations of the fixed-time approach in traffic signal control, which can lead to bottlenecks and inefficiencies. Proposing an alternative algorithm based on design logic control, the study integrates data from inductive detectors and non-linear traffic flow rates to optimize signaling plans. Analytical models are developed for both fixed and semi-actuated traffic signal control approaches, with PTV Vissim software (version 8, 64 bit) used for simulation. The design logic control dynamically adjusts signaling plans, determining the duration of the green interval for the secondary road based on arrival traffic flow. In the absence of traffic, it eliminates the green interval, advancing to the next phase, thereby reducing cycle time. This dynamic adjustment follows a conditional “if-then” statement, optimizing traffic signal operation. The design logic control algorithm was tested in a real isolation intersection with four scenarios, using non-linear traffic flow rate data for one peak hour. Results demonstrated that the proposed design logic control, based on the Semi-Actuated Traffic Signal Control (SATSC) approach, outperformed the commonly used Fixed-Time Signal Control (FTSC) with overall reduction of queue lengths by 39.6% and reduction of vehicle delays by 51.3%. The findings suggest its viability as a solution for many cities, contributing to a more sustainable traffic system.

Innovations in the Russian and Belarusian Economies: Comparative Aspect, Cross Points and Growth

The international authors’ crew has recorded the weaknesses and strengths of the innovative development of the economies of the Russian Federation (RF) and the Republic of Belarus (RB), the points of their real intersection and the existing reserves of cooperation, that are relevant for the current situation having used analytical tools. The results of analysis in these materials helped define similar features of the two economies as a high scientific and educational potential. The study aimed to identify areas where the advantages of one economy under study are clear. The authors found that the RF economy excels in investments and the market environment, while RB excels in infocommunication technologies and the optimality of the branches’ economics. The research will continue to develop and clarifying ways for further cooperation between the two countries. The experience exchange and higher engineering education, high-tech sector and R&D will enable RF to use the positive experience of Belarusian partners today.

Mechanism singularities and shakiness from an algebraic viewpoint

Kinematic singularities are configurations where the configuration space (c-space) V is not smooth or configurations where the rank of the constraint Jacobian drops while the c-space is locally smooth. Both can be analyzed by means of a higher-order analysis, for which the kinematic tangent cone provides a conceptual framework. It is desirable to complement such an analysis with more insight into the origin of specific singular phenomena. Such additional insight is obtained by investigating the kinematics from an algebraic viewpoint. Points of interest are then the singularities of a variety, referred to as algebraic singularities. Algebraic singularities are reflected as kinematic singularities or as shakiness. It is shown that these algebraic singularities can be attributed to properties of the ideal generated by the loop constraints — the constraint ideal. Particular situations arise depending on whether this constraint ideal is radical. If it is not radical, a singular branch is locally defined by a primary ideal. If it is radical, it must be distinguished whether real and complex dimensions of intersecting branches are different. Real intersections indicate kinematic singularities; in all other cases, the mechanism may be in a singularity or may be shaky. Various examples are presented.

Urban traffic congestion alleviation system based on millimeter wave radar and improved probabilistic neural network

AbstractThe millimeter‐wave radar sensor is widely used for urban traffic surveillance because of its weather resistance and high detection accuracy. Methods such as fuzzy theory, pattern recognition, and artificial neural networks have been integrated into the research of traffic state discrimination. However, research on systematically describing the fusion of sensors and traffic state discrimination algorithms to alleviate urban road congestion is still lacking, especially based on millimeter‐wave radar. Thus, the authors propose an urban traffic congestion alleviation system framework. First, the design and deployment of the millimeter‐wave radar system, including waveforms, signal processing flow, and target tracking, are demonstrated to achieve vehicle information acquisition and output. Then, the appropriate traffic parameters are obtained by analysing traffic state influencing factors and the radar data characteristics. Finally, a traffic conditions identification algorithm combining spectral clustering and neural network algorithm is presented to realise road congestion level classification. The system is applied to real urban intersections rather than simulation or approximate real simulation. According to the current road congestion level, regulate the traffic light state to achieve road vehicle driving command. Experiments show that the proposed system can effectively reduce road congestion by 20% compared to the current fixed traffic light system.

On the Topology of Random Real Complete Intersections

Given a smooth real projective variety X and m ample line bundles \(L_1,\dots L_m\) on X also defined over \(\mathbf {R}\), we study the topology of the real locus of the complete intersections defined by global sections of \(L_1^{\otimes d}\oplus \cdots \oplus L^{\otimes d}_m\). We prove that the Gaussian measure of the space of sections defining real complete intersections with high total Betti number (for example, maximal complete intersections) is exponentially small, as d grows to infinity. This is deduced by proving that, with very high probability, the real locus of a complete intersection defined by a section of \(L_1^{\otimes d}\oplus \dots \oplus L^{\otimes d}_m\) is isotopic to the real locus of a complete intersection of smaller degree.

Awareness on Present and Future Trajectory of Vehicle Using Multiple Hypotheses in the Mixed Traffic of Intersection

In the transition period, autonomous vehicles are mixed with unconnected traffic occupants, such as non-autonomous vehicles and pedestrians, resulting in a major hurdle toward autonomy in urban areas, especially at intersections. In this context, the cooperative-intelligent transportation system (C-ITS) affords a promising solution to achieve a breakthrough with its omniscient sensors network and computing capability. From the perspective of a C-ITS-based service, the trajectory of non-autonomous vehicle is a critical uncertainty that resides at the intersection. Therefore, this paper proposes a unique interactive framework, which is installed in the edge server of C-ITS and can estimate the present trajectories and predict the future trajectories of the non-autonomous vehicles at intersections. The proposed framework was based on multiple hypotheses of possible maneuvers that formed the confined prior set to reduce the high uncertainties posed by the complicated environment of the urban intersection. The resulting all-in-one framework provided a stable long-term trajectory prediction with intrinsic maneuver classification and improved tracking in an integrated way by incorporating the interactions between the multiple hypotheses. This situation awareness can assist autonomous vehicles to drive safely and defensively. The proposed framework was verified using a dataset collected at a real urban intersection.

Meter and Modernity in English Verse, 1350–1650 by Eric Weiskott

Reviewed by: Meter and Modernity in English Verse, 1350–1650 by Eric Weiskott Ben Glaser Meter and Modernity in English Verse, 1350–1650. By Eric Weiskott. Philadelphia: University of Pennsylvania Press. 2021. xviii+297 pp. £64. ISBN 978–0–8122–5264–4. Eric Weiskott's second monograph continues to reimagine a non-teleological history of English metre. Amid extensive archival research, two major methodological [End Page 478] concerns surface: a running critique of periodization that centres on modernity, and an expansion of historical prosody. Working against a false symmetry between metrical and social history, Weiskott dislodges the attribution to Chaucer of a break between earlier metrical traditions and pentameter. Before the modern 'break' with pentameter there was a retroprojected 'break' into it that left behind a large corpus and above all Langland. Weiskott brings decades of medieval scholarship on prosody into focus to demystify pentameter's prestige. With deep linguistic and archival knowledge, his book writes new plural histories of English verse forms for early periods in which there is little explicit poetics or meta-prosodic reflection. To overemphasize the latter threatens to reproduce a periodization in which the premodern is the untheorized and therefore untheorizable. Weiskott thus successfully historicizes historical prosody, building bridges backward from its 'Victorianist incarnation' (p. 17). His book answers the pressing need for poetics to find rigorous methods for moving between time periods with truly divergent and non-'modern' literary cultures. The first five chapters establish a corpus of prophetic texts which develop their own historiography and serve to 'think the ideal social arrangement' (p. 42). Prophecy dynamically conserves metrical pasts and lets that pastness infuse prophecy. The scholarship is impressive throughout, delineating an unfamiliar genre in full historical breadth. It was not entirely clear, however, which decisions about metre mattered to authors and scribes, why pentameter was unsuited or deselected for prophecy, or how tetrameter creates 'rhythmical dimensionality' so as to constitute a 'program of literary modernization' (pp. 83–84). To Weiskott's credit, he admits elements that might reinforce narratives of modernization, such as the force of the Chaucerian 'metrical avant-garde' or the Faerie Queene's treatment of prophecy as atavistic and alliteration as mere 'prosodic dried spice' (p. 69). Chapters 6–8 surprisingly reconnect blank and alliterative verse through their classicizing 'avoidance of rhyme' (p. 106). The lack of real intersection in composition, however unsatisfying from a technical perspective, is a necessary concession and indeed part of the book's new metrical history. The mid-sixteenth-century Scottish court—hardly the gravitational centre of our nineteenth- and twentieth-century literary historiographies—is the exception that proves the non-intersection. That said, Weiskott's analysis of George Gascoigne's Steele Glas cleverly shows how poetry assessed and valued alliterative verse in ways absent from that author's foundational prosodic treatise Certayne Notes of Instruction. As in his first book (English Alliterative Verse: Poetic Tradition and Literary History (New York: Cambridge University Press, 2016)), Weiskott sharply reassesses what he calls the 'language–meter dialectic' and its 'epistemological feedback loops between meter and language' (p. 169). Once we see language and metre as two distinct and internally diverse systems, we can recognize how, for example, Piers Plowman 'devises exceptionally difficult choices between innovative metrical phonology and asystematic metrical patterns' (p. 125). We then achieve a sense of Langland's innovative skill in using macaronic verse to 'bring form to consciousness' by contrasting alliterative metrics with London's rhyming forms (p. 130). The [End Page 479] two central chapters, on Langland (7) and Chaucer (10), achieve the methodological goal of a stylistics without explicit prosody. Each of these chapters is followed by rather melancholic but useful tales of how verse style got misrecognized thanks to prosodic ideologies. Langland's alliterative verse, for example, was taken up in an exaggerated 'accentual paradigm' after the seventeenth-century canonization of blank verse. C. S. Lewis's strenuous periodization gives a fair picture of the 'post-enlightenment literary historiography' as well as the simplified and abstract modern scansions Weiskott wishes to revise (p. 145). A third section productively disarticulates two Chaucers: one the inventor of pentameter as an English outcrop of continental decasyllabics, yet influenced by a...

СРАВНИТЕЛЬНАЯ ОЦЕНКА ЭФФЕКТИВНОСТИ АЛГОРИТМОВ МАШИННОГО ОБУЧЕНИЯ С ПОДКРЕПЛЕНИЕМ И ОПТИМИЗАЦИИ ПРИ УПРАВЛЕНИИ ТРАНСПОРТНЫМИ ПРОЦЕССАМИ В СРЕДЕ ANYLOGIC

The task of increasing the throughput of sections of the transport network of the metropolis with the existing infrastructure is solved by means of automated traffic control systems, the purpose of which is to form control actions on the objects of the transport system in real time. An adequate response to load changes in the transport network is implemented by controlling traffic light objects using built-in adaptive algorithms, among which artificial intelligence technologies, in particular, neural networks, are increasingly being used. The noted approaches compete with the widely used optimization-based adaptation method (phase duration, displacement, etc.). The proposed article examines the issue of comparing the efficiency of an optimization algorithm with reinforcement machine learning algorithms by the criterion of the time spent by vehicles in the intersection system in the Anylogic simulation environment. This study will help determine a more efficient solution to the problem of setting the duration of traffic light control phases. It was shown that in the reinforcement learning algorithm, the ability to adapt to input intensities within the schedule is higher compared to the optimization algorithm. However, the reinforcement algorithm is more sensitive to the type of schedule than the optimization algorithm, which outperformed the latter by about 20% at the optimal point for the weekday schedule. The advantage of the reinforcement algorithm was more pronounced on the 2nd schedule, which features a tendency to increase traffic intensity, namely: 61% compared to the optimization and 70% compared to the base setting. It turned out to be practically insensitive to the “detuning” of the input data relative to the optimal policy when changing the intensity levels within this schedule. Thus, it was shown that the results of the regulation of the traffic process at the studied real intersection, obtained by modeling using reinforcement learning, are superior to the optimization approach, but are sensitive to the given intensity schedule.

Machine-Learning-Based Real-Time Multi-Camera Vehicle Tracking and Travel-Time Estimation.

Travel-time estimation of traffic flow is an important problem with critical implications for traffic congestion analysis. We developed techniques for using intersection videos to identify vehicle trajectories across multiple cameras and analyze corridor travel time. Our approach consists of (1) multi-object single-camera tracking, (2) vehicle re-identification among different cameras, (3) multi-object multi-camera tracking, and (4) travel-time estimation. We evaluated the proposed framework on real intersections in Florida with pan and fisheye cameras. The experimental results demonstrate the viability and effectiveness of our method.

Gradient illumination scheme design at the highway intersection entrance considering driver’s light adaption

Objective Improving lighting arrangements at the highway intersections can significantly reduce the likelihood of crashes. Meanwhile, a reasonable gradient illumination scheme can increase drivers' safety by avoiding the rapid change of their pupil area when driving from an unlighted area into a lighted area. The purpose of this study is to design illumination transition zones for drivers when approaching the highway intersection, and optimize the illumination increments along the transition zones. Methods This issue is addressed in three stages. First, an indoor simulation platform is built using the UC-win/road software, and its parameters are calibrated using real intersection data collected at night. Second, the variation of pupil area under different increasing rates of illuminance near the driver's eyes (INDE) is analyzed, and a model representing the temporal change of the area in the pupil contraction stage is established. Last, an optimization model is proposed to obtain the optimal luminance increasing rates by minimizing the time needed for drivers to travel through the transition zones under different maximum illuminations and speed limits. Results The findings of this study indicate that the INDE increasing time in the transition zone remains unchanged with a determined illumination at the intersection, and the optimal transition zone length is directly proportional to the speed limit of the intersection. Therefore, the transition zone length needs to be adjusted to accommodate different speed limits: it should be extended or shortened by the same percentage as the increase or decrease of the speed limit. Conclusions It can be concluded that the illumination transition zone is necessary when the INDE of highway intersection and the speed limit exceed 8 lx and 40 km/h, respectively. The INDE increasing rate should be maintained around the optimal value, providing safe and comfortable light adaptation to drivers and preventing traffic accidents. The study will provide a scientific basis for safety implementation of lighting arrangements at highway intersections.

Design of “Immersive” Teaching Situation Simulation System for Law Course Based on Artificial Intelligence

The method of scene mapping provides a very effective technical support for classroom participants to roam freely in a virtual scene larger than the real space. When the virtual scene is larger than the area in the real space, the existing scene mapping method will cause distortion of the original virtual scene and affect the user’s roaming experience and visual experience. In order to obtain the scene map with low isometric distortion when the virtual scene scale is much larger than the real space, this paper proposes the block map to divide and group the roads in the virtual scene. For each group of roadblocks, the mapping is obtained by minimizing the isometric distortion energy of the mapping on the premise that the adjacent road blocks are smooth and continuous at the junction. The segmented roadblocks are mapped to the interior of the real intersections, and then the mapping of the whole scene is optimized globally to further reduce the isometric distortion of the whole mapping. Based on the above theories, the design scheme of immersive virtual legal reality classroom is proposed, including the overall framework of immersive virtual legal reality classroom, interactive scheme design, interactive behavior design, and required technical scheme, etc. The application technology, educational application, and application experience are analyzed in combination with the constructed immersive virtual legal reality scene for corresponding innovation and improvement. By applying immersive virtual reality technology in the field of education, the results show that the simulation system has good practicability and stronger stability and can provide a better immersive experience for law class participants.

EULER CHARACTERISTIC AND SIGNATURE OF REAL SEMI-STABLE DEGENERATIONS

AbstractWe give a motivic proof of the fact that for nonsingular real tropical complete intersections, the Euler characteristic of the real part is equal to the signature of the complex part. This was originally proved by Itenberg in the case of surfaces in $\mathbb {C}P^{3}$ , and has been successively generalized by Bertrand and by Bihan and Bertrand. Our proof, different from previous approaches, is an application of the motivic nearby fiber of semistable degenerations. In particular, it extends the original result by Itenberg, Bertrand, and Bihan to real analytic families admitting a $\mathbb {Q}$ -nonsingular tropical limit.

A Hybrid Ensemble Model for Urban Lane-Level Traffic Flow Prediction

In recent years, automatic driving and internet of vehicles technology have made great progress. Road oriented the traditional traffic flow prediction methods can no longer meet the needs of automatic driving, lane-level map navigation. This paper takes urban lanes as the research object, and proposes a traffic flow prediction model for urban lanes. First, a boosting based Catboost model is introduced to construct a series of spatiotemporal features and perform feature selection to reduce the model bias. Second, the model variance is reduced by using bagging-based random forest algorithm. Third, a long short-term memory network (LSTM) is used to extract the temporal trend of traffic flow in the current lane. The prediction results of these three models are finally integrated by the method of stacking ensemble learning. The proposed method is evaluated with the dataset collected from real intersections in Wuxi city. The experimental results show that our model has higher prediction precision than other methods.

大型車の一般路自動走行のための経路計画手法

In order to solve the problem regarding the shortage of truck and bus drivers in recent years, manpower-saving and unmanned operation of commercial vehicles is currently being actively researched and developed. However, when traveling on narrow road widths and curves with large curvatures, such as urban roads, commercial vehicles have larger internal wheel truck differences and overhang swing than passenger cars. Therefore, the path tracking control focusing on CG position tracking applied to passenger cars cannot be applied directly to commercial vehicles. Therefore, the purpose of this study is to develop a path planning and motion control system for automated operation of commercial vehicles in urban areas. In designing the control system, a risk potential field was used to express the driver's sense of danger with respect to obstacles and road boundaries. A simulation is conducted on a course that recostructs a real intersection, and a parameter study is conducted. Finally, the simulation results of this method are compared with those of a general path-following method, and the results show that this method is effective for avoiding obstacles in intersection situations.

Experimental Study on Different Types of Curves for Ride Comfort in Automated Vehicles

Vehicle automation is among the best possible solutions for traffic issues, including traffic accidents, traffic jams, and energy consumption. However, the user acceptance of automated vehicles is critical and is affected by riding comfort. In addition, human factors in automated vehicle control should be clear. This study evaluates the effect of different courses on driving comfort in automated vehicles using field experiments with 25 subjects. This study focused on lateral motion, but speed control was not targeted. Further, generating a path for obstacle avoidance and lane keeping, which have several constraining conditions, was also not targeted. Rendering a comfortable path is beneficial for developing an acceptable system as a car developer and for building new curves for automated or driving assistance systems from the perspective of construction. The automated vehicle drove at a speed of 30 km/h on four courses, namely, clothoid, two types of spline curves, and arc, based on the real intersection. Each participant sat on both the driver and passenger seat and answered a questionnaire. The experimental data indicated the clothoid course to be the most comfortable, while the arc was most uncomfortable for a significance level of 1%. These tendencies are applicable to driver and passenger seats, all genders, and experiences and will be beneficial for human factor research in automated vehicle control.

Hey, watch where you’re going! An on-road study of driver scanning failures towards pedestrians and cyclists

The safety of Vulnerable Road Users (VRUs), such as pedestrians and cyclists, is a serious public health concern, especially at urban intersections. A major reason for vehicle-VRU collisions is driver attentional errors. Prior studies suggest that cross-modal transportation experiences (e.g., being a driver who also cycles) improve visual attention allocation toward VRUs. However, these studies were conducted in simulators or in a laboratory, limiting their generalizability to real world driving. We utilized an instrumented vehicle equipped with eye tracking technology to examine (a) the prevalence of drivers’ visual scanning failures toward VRUs at real intersections and (b) whether there is an effect of cycling experience on this prevalence. Twenty-six experienced drivers (13 cyclists and 13 non-cyclists), between the ages of 35 and 54, completed 18 different turns at urban Toronto intersections, for which gaze and video data were utilized to determine drivers’ visual scanning failures towards areas where conflicting VRUs could approach. Among the 443 unique turn events, 25% were identified as having a visual scanning failure. Results from a mixed effects logit model showed that the odds of committing visual scanning failures towards VRUs during a turning maneuver at an intersection were 2.01 times greater for drivers without cycling experience compared to drivers with cycling experience. Given that our participants represented a low crash-risk age group, this study suggests that the rate at which VRUs are unattended to may be much higher.