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This work proposes a hardware-friendly, dense optical flow-based Time-to-Collision (TTC) estimation algorithm intended to be deployed on smart video sensors for collision avoidance. The algorithm optimized for hardware first extracts biological visual motion features (motion energies), and then utilizes a Random Forests regressor to predict robust and dense optical flow. Finally, TTC is reliably estimated from the divergence of the optical flow field. This algorithm involves only feed-forward data flows with simple pixel-level operations, and hence has inherent parallelism for hardware acceleration. The algorithm offers good scalability, allowing for flexible tradeoffs among estimation accuracy, processing speed and hardware resource. Experimental evaluation shows that the accuracy of the optical flow estimation is improved due to the use of Random Forests compared to existing voting-based approaches. Furthermore, results show that estimated TTC values by the algorithm closely follow the ground truth. The specifics of the hardware design to implement the algorithm on a real-time embedded system are laid out.

Vehicular wireless communications require both congestion control to guarantee the availability of a fraction of the bandwidth for safety-related event-driven messages in emergency cases, and awareness control to adapt the beaconing activity to the application needs and surrounding traf_c situation. Most current approaches either ignore the traf_c situation and only adapt the beaconing rate to the channel congestion state or override the congestion control limits, leading to questionable results in both cases. In this paper, we conceive and validate a novel approach, combining both aspects. Based on distributed Network Utility Maximization (NUM), our algorithm satis_es the constraints on channel availability, whereas the safety of the surrounding traf_c situation is captured with a time-to-collision metric, used to assign priorities in the optimal allocation problem. The performance of the proposed approach is validated and compared to other popular algorithms. Results show that our proposal automatically anticipates a potential increase in rate due to a critical safety situation, but does not interfere with the reserved bandwidth for safety applications. This work was supported in part by Spanish MECD/AEI/FEDER under Grant TEC2016-76465-C2-1-R, in part by Spanish MINECO/AEI/FEDER under Grant TEC2017-84423-C3-2-P (ONOFRE-2), in part by e-DIVITA under Grant 20509/PDC/18 (Proof of Concept, 2018), and in part by ATENTO Projects under Grant 20889/PI/18 (Fundación Seneca, Región de Murcia). The work of J. Aznar-Poveda was supported by the MECD under Grant BES-2017-081061.

The focus of this paper is the crash risk assessment of off-ramps in Xi&rsquo, an. The time-to-collision (TTC) is used for the measurement and cross-comparison of the crash risk of each location. Five sites from the urban expressway in Xi&rsquo, an were selected to explore the TTC distribution. An unmanned aerial vehicle and a camera were used to collect traffic flow data for 20 min at each site. The parameters, including speed, deceleration rate, truck percentage, traffic volume, and vehicle trajectories, were extracted from video images. The TTCs were calculated for each vehicle. The Gaussian mixture model (GMM) was proposed to predict the TTC probability density functions (PDFs) and cumulative density functions (CDFs) for five sites. The Kolmogorov&ndash, Smirnov (K-S) test indicated that the samples followed the estimated GMM distribution. The relationship between the crash risk level and influencing factors was studied by an ordinal logistic regression model and a naive Bayesian model. The results showed that the naive Bayesian model had an accuracy of 86.71%, while the ordinal logistic regression model had an accuracy of 84.81%. The naive Bayesian model outperformed the ordinal logistic regression model, and it could be applied to the real-time collision warning system.

The authors present an approach to the coordination of eye movements and locomotion in naturalistic steering tasks. It is based on recent empirical research, in particular, on driver eye movements, that poses challenges for existing accounts of how we visually steer a course. They first analyze how the ideas of feedback and feedforward processes and internal models are treated in control theoretical steering models within vision science and engineering, which share an underlying architecture but have historically developed in very separate ways. The authors then show how these traditions can be naturally (re)integrated with each other and with contemporary neuroscience, to better understand the skill and gaze strategies involved. They then propose a conceptual model that (a) gives a unified account to the coordination of gaze and steering control, (b) incorporates higher-level path planning, and (c) draws on the literature on paired forward and inverse models in predictive control. Although each of these (a–c) has been considered before (also in the context of driving), integrating them into a single framework and the authors’ multiple waypoint identification hypothesis within that framework are novel. The proposed hypothesis is relevant to all forms of visually guided locomotion.

Rear-end collisions often cause serious traffic accidents. Conventionally, in intelligent transportation systems (ITS), radar collision warning methods are highly accurate in determining the inter-vehicle distance via detecting the rear-end of a vehicle, however, in poor weather conditions such as fog, rain, or snow, the accuracy is significantly affected. In recent years, the advent of Vehicle to Vehicle (V2V) and Vehicle to Infrastructure (V2I) communication systems has introduced new methods for solving the rear-end collision problem. Nevertheless, there is still much left for improvement. For instance, weather conditions have an impact on human-related factors such as response time. To address the issue of collision detection under low visibility conditions, we propose a Visibility-based Collision Warning System (ViCoWS) design that includes four models for prediction horizon estimation, velocity prediction, headway distance prediction, and rear-end collision warning. Based on the history of velocity data, future velocity volumes are predicted. Then, the prediction horizon (number of future time slots to consider) is estimated corresponding to different weather conditions. ViCoWs can respond in real-time to weather conditions with correct collision avoidance warnings. Experiment results show that the mean absolute percentage error of our velocity prediction model is less than 11%. For non-congested traffic under heavy fog (very low visibility of 120 m), ViCoWS warns a driver by as much as 4.5 s prior to a possible future collision. If the fog is medium with a low visibility of 160 m, ViCoWs can give warnings by about 2.1 s prior to a possible future collision. In contrast, the Forward Collision Probability Index (FCPI) method gives warnings by only about 0.6 s before a future collision. For congested traffic under low visibility conditions, ViCoWS can warn a driver by about 1.9 s prior to a possible future collision. In this case, the FCPI method gives 1.2 s for the driver to react before collision.

As vehicles get increasingly automated, they need to properly evaluate different situations and assess threats at run-time. In this scenario automated vehicles should be able to evaluate risks regarding a dynamic environment in order to take proper decisions and modulate their driving behavior accordingly. In order to avoid collisions, in this work we propose a risk estimator based on fuzzy logic which accounts for risk indicators regarding (1) the state of the driver, (2) the behavior of other vehicles and (3) the weather conditions. A scenario with two vehicles in a car-following situation was analyzed, where the main concern is to avoid rear-end collisions. The goal of the presented approach is to effectively estimate critical states and properly assess risk, based on the indicators chosen. This work was supported by the AMASS project (H2020- ECSEL) with grant agreement number 692474.

Analyzing a crash using driving recorder data makes it possible to objectively examine factors contributing to the occurrence of the crash. In this study, car-to-cyclist crashes and near crashes recorded on cars equipped with advanced driving recorders were compared with each other in order to examine the factors that differentiate near crashes from crashes, as well as identify the causes of the crashes. Focusing on cases where the car and cyclist approached each other perpendicularly, the differences in the car's and cyclist's parameters such as velocity, distance and avoidance behavior were analyzed. The results show that car-to-cyclist crashes would not be avoidable when the car approaching the cyclist enters an area where the average deceleration required to stop the car is more than 0.45 G (4.4 m/s2). In order for this situation to occur, there are two types of cyclist crash scenarios. In the first scenario, the delay in the drivers’ reaction in activating the brakes is the main factor responsible for the crash. In this scenario, time-to-collision when the cyclist first appears in the video is more than 2.0 s. In the second scenario, the sudden appearance of a cyclist from behind an obstacle on the street is the factor responsible for the crash. In this case, the time-to-collision is less than 1.2 s, and the crash cannot be avoided even if the driver exhibited avoidance maneuvers.

It has been shown that knowing the size of an approaching object affects our perception of time to collision (TTC) in a manner similar to the way it affects perception of the physical speed of objects moving in the frontoparallel plane. In this article, we present a series of experiments exploring the effect of object familiarity on the perception of speed and distance in the context of motion in depth (MID), and the interplay among these variables in the perception of TTC. Results of the first experiment show that object familiarity does not help human observers to discriminate the speed of MID. In the second experiment, we show that familiar size may be used to infer the relative distance among objects, in the context of MID, but not to make accurate estimations. Finally, we show that the relative TTCs do not follow the perceived relative distances obtained in the second experiment. Fil: Martín, Andrés. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Investigación en Luz, Ambiente y Visión. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Instituto de Investigación en Luz, Ambiente y Visión; Argentina Fil: Decima, Agustin Patricio Rafael. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Investigación en Luz, Ambiente y Visión. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Instituto de Investigación en Luz, Ambiente y Visión; Argentina Fil: Barraza, Jose Fernando. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tucumán. Instituto de Investigación en Luz, Ambiente y Visión. Universidad Nacional de Tucumán. Facultad de Ciencias Exactas y Tecnología. Instituto de Investigación en Luz, Ambiente y Visión; Argentina

Time-to-collision (TTC) underestimation has been interpreted as an adaptive response that allows observers to have more time to engage in a defensive behaviour. This bias seems, therefore, strongly linked to action preparation. There is evidence that the observer’s physical fitness modulates the underestimation effect so that people who need more time to react (i.e. those with less physical fitness) show a stronger underestimation effect. Here we investigated whether this bias is influenced by the momentary action capability of the observers. In the first experiment, participants estimated the time-to-collision of threatening or non-threatening stimuli while being mildly immobilized (with a chin rest) or while standing freely. Having reduced the possibility of movement led participants to show more underestimation of the approaching stimuli. However, this effect was not stronger for threatening relative to non-threatening stimuli. The effect of the action capability found in the first experiment could be interpreted as an expansion of peripersonal space (PPS). In the second experiment, we thus investigated the generality of this effect using an established paradigm to measure the size of peripersonal space. Participants bisected lines from different distances while in the chin rest or standing freely. The results replicated the classic left-to-right gradient in lateral spatial attention with increasing viewing distance, but no effect of immobilization was found. The manipulation of the momentary action capability of the observers influenced the participants’ performance in the TTC task but not in the line bisection task. These results are discussed in relation to the different functions of PPS.

With regard to impending object–object collisions, observers may use different sources of information to judge time to contact (tC). We introduced changes of the observer’s vantage point to test among three sets of hypotheses: (1) Observers may use a distance-divided-by-velocity algorithm or, alternatively, elaborated τ-formulae, all of which give exact tC information; (2) observers may use simple τ-formulae (i.e., formulae of the type: visual angle divided by its own first temporal derivative); (3) observers may capitalize on non-τ variables. Hypotheses (2) and (3) imply specific patterns of errors. We presented animated, impending collisions between a moving object and a stationary pole to naïve observers. The moving object either was a square tile or a small dot of fixed size. Participants viewed these events in a prediction-motion paradigm from different vantage points, covering a full circle around the setting. As accuracy of responses varied sinusoidally with viewing angle, irrespective of the type of object used, we conclude that observers mainly responded to the perspective view of the gap between object and pole, and less to the object’s changing visual angle, or τ. Results are discussed with regard to evolutionary demands and issues of generalization.

Collision avoidance system (CAS), with the help of surrogate safety measures is a beneficial tool for reducing driver errors and preventing rear-end collisions. One of the most well-known surrogate safety measures to detect rear-end conflicts is Time-to-collision (TTC). TTC refers to the time remaining before the rear-end accident if the course and the speed of vehicles are maintained constant. Different surrogate measures have been derived from TTC; however, the most important are Time Exposed Time-to-collision (TET) and Time Integrated Time-to-collision (TIT). In this paper a new surrogate safety measure based on TTC notion has been developed. This new indicator merges TET and TIT into one measure and gives a score between 0 and 100%, as the probability of collision. Applying this indicator in CAS as a safety measure will be more useful than TET&TIT, to reduce driver errors and rear-end collisions.

In order to improve vehicle safety, a interaction phase between primary and secondary safety systems has been defined. These systems use information provided by the primary safety systems to achieve both the primary and the secondary systems' objectives. It is essential to discriminate whether a collision is avoidable or not and to calculate the time available before the crash happens. This paper shows a method that improves on other simplified methods to calculate the time-to-collision (TTC) to provide a more accurate result that could be used in a collision avoidance system. The work reported in this paper has been partly funded by the Spanish Ministry of Science and Innovation (SAMPLER project TRA2010 20225 C03 01 and TRA2010 20225 C03 03; and IVANET project TRA 2010 15645).

A systems theory of movement control in animals is presented in this article and applied to explaining the controlled behaviour of the single-celled Paramecium caudatum in an electric field. The theory-General Tau Theory-is founded on three basic principles: (i) all purposive movement entails prospectively controlling the closure of action-gaps (e.g. a distance gap when reaching, or an angle gap when steering); (ii) the sole informational variable required for controlling gaps is the relative rate of change of the gap (the time derivative of the gap size divided by the size), which can be directly sensed; and (iii) a coordinated movement is achieved by keeping the relative rates of change of gaps in a constant ratio. The theory is supported by studies of controlled movement in mammals, birds and insects. We now show for the first time that it is also supported by single-celled paramecia steering to the cathode in a bi-polar electric field. General Tau Theory is deployed to explain this guided steering by the cell. This article presents the first computational model of prospective perceptual control in a non-neural, single-celled system.

Estimation of time-to-arrival for moving objects is critical to obstacle interception and avoidance, as well as to timing actions such as reaching and grasping moving objects. The source of motion information that conveys arrival time varies with the trajectory of the object raising the question of whether multiple context-dependent mechanisms are involved in this computation. To address this question we conducted a series of psychophysical studies to measure observers’ performance on time-to-arrival estimation when object trajectory was specified by angular motion (“gap closure” trajectories in the frontoparallel plane), looming (colliding trajectories, TTC) or both (passage courses, TTP). We measured performance of time-to-arrival judgments in the presence of irrelevant motion, in which a perpendicular motion vector was added to the object trajectory. Data were compared to models of expected performance based on the use of different components of optical information. Our results demonstrate that for gap closure, performance depended only on the angular motion, whereas for TTC and TTP, both angular and looming motion affected performance. This dissociation of inputs suggests that gap closures are mediated by a separate mechanism than that used for the detection of time-to-collision and time-to-passage. We show that existing models of TTC and TTP estimation make systematic errors in predicting subject performance, and suggest that a model which weights motion cues by their relative time-to-arrival provides a better account of performance.

Over the last decades or so, empirical studies of perception, action, learning, and development have revealed that participants vary in what variable they detect and often rely on nonspecifying variables. This casts doubt on the Gibsonian conception of information as specification. It is argued that a recent ecological conception of information has solved important problems, but insufficiently explains what determines the object of perception. Drawing on recent work on developmental systems, we sketch the outlines of an alternative conception of perceptual information. It is argued that perceptual information does not reside in the ambient arrays; rather, perceptual information is a relational property of patterns in the array and perceptual processes. What a pattern in the ambient flow informs about depends on the perceiver who uses it. We explore the implications of this alternative conception of information for the ecological approach to perception and action. (C) 2009 Elsevier B.V. All rights reserved.

Many animals avoid dark, approaching objects seen against a lighter background but show no or weaker reactions to stimuli with inverted contrast. We investigated whether human observers would respond differently to such stimuli in terms of estimated time-to-arrival. We varied luminances of an approaching, light or dark disk and a plain, grey background, and for several conditions, continuously adjusted calibrations so as to keep contrast and/or overall lightness constant. Since no effects were found, we conclude that humans are able to discard luminance and contrast for the task at hand. Generally, however, performance was affected by different, consecutive regimes of feedback: Initially, without feedback, observers responded inconsistently and much too late; they improved after correct feedback, and in a third block of trials with pseudo-random feedback, they responded increasingly early without reverting to the initial level of uncertainty. We discuss our findings with regard to implications for neural mechanisms, put them in the context of evolutionary considerations, and propose continuative animal behavioral studies.

As an object approaches an observer’s eye, tau, defined as the inverse relative expansion rate of the object’s image on the retina (Lee, 1976) approximates time-to-collision (TTC). Many studies have suggested that human observers use TTC information, but evidence for the use of tau remains inconclusive. Here we present two studies that investigated the use of tau in object-motion and observer-motion situations. In Study I, we dissociated several monocular variables that potentially contributed to TTC perception, and found that participants were most sensitive to TTC information when performing a relative TTC estimation task; and less sensitive to non-time variables such as distance-to-collision, speed and object size. Additionally, when we manipulated sources of information to specify conflicting time-of-arrivals, TTC specified by tau was weighted more than TTC derived from distance and speed. Thus, we concluded that even in the presence of monocular depth information, observers strongly utilize tau when estimating TTC. In Study II, observers estimated TTC of a looming target in the presence or absence of background expansion. Results demonstrated that participants overestimated TTC in situations where the surroundings of the target’s contours expanded at a reduced rate. Moreover, simulated self-motion was unnecessary to induce this bias, as results were comparable in situations where this relative expansion was limited to the target’s immediate surroundings. Therefore, we also concluded that a relative tau variable, based on the relative rate of expansion, is utilized whenever expansion beyond the object’s immediate boundaries is less than the target’s absolute rate of expansion. Master of Science (MSc)

International audience; The constant bearing angle (CBA) strategy is a prospective strategy that permits the interception of moving objects. The purpose of the present study is to test this strategy. Participants were asked to walk through a virtual environment and to change, if necessary, their walking speed so as to intercept approaching targets. The targets followed either a rectilinear or a curvilinear trajectory and target size was manipulated both within trials (target size was gradually changed during the trial in order to bias expansion) and between trials (targets of different sizes were used). The curvature manipulation had a large effect on the kinematics of walking, which is in agreement with the CBA strategy. The target size manipulations also affected the kinematics of walking. Although these effects of target size are not predicted by the CBA strategy, quantitative comparisons of observed kinematics and the kinematics predicted by the CBA strategy showed good fits. Furthermore, predictions based on the CBA strategy were deemed superior to predictions based on a required velocity (V (REQ)) model. The role of target size and expansion in the prospective control of walking is discussed.

Time-To-Collision (TTC) is a common vision feature used to avoid obstacles, and is frequently used in cinematography to induce emotional effects. In this paper, we show how TTC can lead to several high-level video categories. The extracted TTC shots (low-level feature) are mapped to their corresponding high-level indices. The information conveyed by neighboring frames or shots (i.e., contextual information) is used to facilitate the mapping process. Our proposed TTC detection algorithm is based on computing TTC from the divergence of the image velocity field. A simple and novel method known as the pilot cue is used to further refine our algorithm. The experiments results are promising and show the effectiveness of the approach.

Time-to-collision is one of the possible sources of visual information participating in the control of deceleration when breaking a vehicle. Lee’s (1976) theory suggested that the inverse rate of expansion in the retina of an approaching obstacle, the optic variable tau (τ), and its first derivative in time, tau-dot (τ& ), provide information for, respectively, braking initiation and its intensity regulation. The purpose of this study was to test Lee’s hypotheses at the situation where a bicycle in linear trajectory is approaching a stationary obstacle. As relative quantities, τm and τ& should not be affected by the initial velocity. In three velocity conditions (high, medium, and low), participants had 23, 18 e 13 m to accelerate the bicycle until the final 14 m, when they were free to break at any time in order to stop at the obstacle. Peak velocities were 22.5, 19.5, and 16.6 m/s at 14.0, 12.0 and 10.2 m from the obstacle, respectively. Values of τm and τ& were not significantly affected by condition as expected. τm at braking initiation was 0.63, 0.62, and 0.62 s as τ& during the deceleration phase was -0.54, -0.54, and -0.55. These results strongly support the use of time-to-collision information contained in the optic flow to safely control braking initiation and intensity

Bij modelleren van bestuurdersgedrag is het van belang kritiek van normale gebeurtenissen te onderscheiden. Tijdmaten als TTC en TLC geven hiervoor de criteria.

Bij modelleren van bestuurdersgedrag is het van belang kritiek van normale gebeurtenissen te onderscheiden. Tijdmaten als TTC en TLC geven hiervoor de criteria.

The Directorate-General for Public Works and Water Management is considering the feasibility of dynamically switching the lighting on motorways (DYNO). This would provide under all traffic and weather conditions adequate illumination levels without illuminating the road unnecessarily brightly. This has been put into practice in a test conducted under contract of the Ministry of Transport, Public Works, and Water Management, Transport Research Centre into the effect of dynamic illumination of public highways on driving behaviour and traffic safety. The first step was to establish, on the basis of a road characterization analysis, a preliminary switching schedule. Besides the normal lation (100%) a reduced (20%) and an increased level (200%) was employed. Depending on traffic and weather conditions, a suitable level is switched on. The preliminary switching schedule was employed in the test, during which its effect on driving behaviour was examined. The results demonstrated that the normal level of illumination resulted in minor accommodations of behaviour: average speeds increased somewhat (ca. 0.7 km/h) and the number of critical situations (short traffic intervals, short TTCs) increased by a maximum of 1%. Taking also the positive effect of conventional lighting on traffic safety known from the literature, no negative effect on traffic safety is anticipated from those accommodations of behaviour. Differences between 100% and 200% were not reflected in driving behaviour for the combination of high traffic volume and precipitation. Other situations for which the preliminary switching schedule of 200% is prescribed are relatively rare and the increased benefit of a higher level of illumination in such situations is considered to be limited. An inquiry into motorists' perceptions of dynamic illumination of public highways showed that it enjoyed their broad support. There is absolutely no evidence to support the contention that the reduced level of illumination will under favourable circumstances be perceived as being too low. A cost-benefits analysis was addressed to the relationship between the installation costs of DYNO (20-100-200) for the trial location and the energy and environmental costs (CO2 emissions from the power station). It showed that both the installation costs and the energy and environmental costs were higher than for a conventional installation. This system will therefore be unable to recover its investment on the basis of energy and environmental costs. Even when the DYNO system is fitted only with reduced and normal levels, the installation costs will still be higher than for a conventional installation, but the energy ant the energy and environmental costs lower than for a conventional installation. Due to this the system can in principle recover its investment on the basis of energy and environmental costs. This is compatible with the government's policy of reducing CO2 emissions. The payback period will depend strongly on the local situation and the tariff structure in which the system is employed.

The Directorate-General for Public Works and Water Management is considering the feasibility of dynamically switching the lighting on motorways (DYNO). This would provide under all traffic and weather conditions adequate illumination levels without illuminating the road unnecessarily brightly. This has been put into practice in a test conducted under contract of the Ministry of Transport, Public Works, and Water Management, Transport Research Centre into the effect of dynamic illumination of public highways on driving behaviour and traffic safety. The first step was to establish, on the basis of a road characterization analysis, a preliminary switching schedule. Besides the normal lation (100%) a reduced (20%) and an increased level (200%) was employed. Depending on traffic and weather conditions, a suitable level is switched on. The preliminary switching schedule was employed in the test, during which its effect on driving behaviour was examined. The results demonstrated that the normal level of illumination resulted in minor accommodations of behaviour: average speeds increased somewhat (ca. 0.7 km/h) and the number of critical situations (short traffic intervals, short TTCs) increased by a maximum of 1%. Taking also the positive effect of conventional lighting on traffic safety known from the literature, no negative effect on traffic safety is anticipated from those accommodations of behaviour. Differences between 100% and 200% were not reflected in driving behaviour for the combination of high traffic volume and precipitation. Other situations for which the preliminary switching schedule of 200% is prescribed are relatively rare and the increased benefit of a higher level of illumination in such situations is considered to be limited. An inquiry into motorists' perceptions of dynamic illumination of public highways showed that it enjoyed their broad support. There is absolutely no evidence to support the contention that the reduced level of illumination will under favourable circumstances be perceived as being too low. A cost-benefits analysis was addressed to the relationship between the installation costs of DYNO (20-100-200) for the trial location and the energy and environmental costs (CO2 emissions from the power station). It showed that both the installation costs and the energy and environmental costs were higher than for a conventional installation. This system will therefore be unable to recover its investment on the basis of energy and environmental costs. Even when the DYNO system is fitted only with reduced and normal levels, the installation costs will still be higher than for a conventional installation, but the energy ant the energy and environmental costs lower than for a conventional installation. Due to this the system can in principle recover its investment on the basis of energy and environmental costs. This is compatible with the government's policy of reducing CO2 emissions. The payback period will depend strongly on the local situation and the tariff structure in which the system is employed.

Rijkswaterstaat overweegt verlichting op autosnelwegen dynamisch te gaan schakelen. Onder alle omstandigheden wordt een verlichtingsniveau aangeboden dat voldoende hoog is, gegeven de verkeers- en weersomstandigheden, terwijl de weg niet onnodig sterk wordt verlicht. In opdracht van de Rijkswaterstaat Adviesdienst Verkeer en Vervoer is een praktijkproef uitgevoerd naar het effect van dergelijke dynamische openbare verlichting op het rijgedrag en de verkeersveiligheid. In eerste instantie is op basis van een wegbeeldanalyse een voorlopig schakelregime vastgesteld. Naast de normale verlichtingssterkte (100%) wordt hierbij gebruik gemaakt van een verlaagd (20%) en een verhoogd (200%) verlichtingsniveau. Bij duisternis wordt minstens het lage niveau ingeschakeld. Bij normale tot hoge verkeersintensiteit wordt het normale niveau ingeschakeld, evenals bij ongunstige weers- of verkeersomstandigheden (neerslag, gladheid, werk in uitvoering). Het 200%-niveau wordt relatief sporadisch toegepast, namelijk bij combinaties van speciale verkeers- en weersomstandigheden (b.v. regen bij hoge verkeersintensiteit), bij mist, of bij calamiteiten. Dit voorlopige schakelregime is toegepast in de praktijkproef, waarin de effecten op het rijgedrag zijn onderzocht. De resultaten laten zien dat het normale niveau van verlichting leidt tot geringe gedragsaanpassingen: de gemiddelde rijsnelheid nam iets toe (ca. 0,7 km/u) en het aandeel kritische situaties (korte volgtijden, korte TTC's) steeg met maximaal 1%. Mede gegeven het uit de literatuur bekende positieve effect van conventionele verlichting op de verkeersveiligheid wordt van deze gedragsaanpassingen geen negatief effect op de verkeersveiligheid verwacht.