Lead Car Research Articles

Statistical Properties of Car Following: Theory and Driving Simulator Experiments

A fair simple car driving simulator was created based on the open source engine TORCS and used in car-following experiments aimed at studying the basic features of human behavior in car driving. Four subjects with different skill in driving real cars participated in these experiments. The subjects were instructed to drive a car without overtaking and losing sight of a lead car driven by computer at a fixed speed. Based on the collected data the distributions of the headway distance, the car velocity, acceleration, and jerk are constructed and compared with the available experimental data for the real traffic flow. A new model for the car-following is proposed to capture the found properties. As the main result, we draw a conclusion that human actions in car driving should be categorized as generalized intermittent control with noise-driven activation. Besides, we hypothesize that the car jerk together with the car acceleration are additional phase variables required for describing the dynamics of car motion governed by human drivers.

How Do Children Perceive and Act on Dynamic Affordances in Crossing Traffic-Filled Roads?

Successfully perceiving and acting on dynamic affordances is critical for children and adults to function. In our work, we look at how children cross roads as a model for understanding how they learn to perceive and act on dynamic affordances. Ten- to 14-year-old children and adults ride an interactive bicycling simulator through an immersive virtual environment where they cross intersections with continuous cross traffic. We consistently find developmental and individual differences in children's ability to tightly time their entry into the roadway relative to the lead car in the gap. Given that children do not adjust their gap choices to match their less precise timing abilities, children take more risks when crossing roads than adults. We conclude by discussing possible reasons for these developmental differences in movement timing.

Study on the Display Positions for the Haptic Rotary Device-Based Integrated In-Vehicle Infotainment Interface

Integrated multimodal systems is one promising direction to improve human-vehicle interaction. In order to create intelligent human-vehicle interfaces and reduce visual load during secondary tasks, combining a haptic rotary device and a graphic display will provide one practical solution. However, in literature, the proper display position for the haptic rotary device is not fully investigated. In this paper, one experimental infotainment system is studied (including a haptic rotary control device and a graphic display) to evaluate the proper display position. Measurements used include task completion time, reaction to road events, lane/velocity keeping during secondary tasks, and user preference. Three display positions are considered: high mounted position, cluster position, and center stack position. The results show that, with increased on-road and off-road visual loads, the cluster display position can reduce lane position deviation significantly compared to high mounted and center stack positions. In addition, the high mounted and cluster display positions are better toward two different road events, including strong wind gust and extreme deceleration of the lead car.

The effects of age and workload on 3D spatial attention in dual-task driving

In the present study we assessed whether the limits in visual–spatial attention associated with aging affect the spatial extent of attention in depth during driving performance. Drivers in the present study performed a car-following and light-detection task. To assess the extent of visual–spatial attention, we compared reaction times and accuracy to light change targets that varied in horizontal position and depth location. In addition, because workload has been identified as a factor that can change the horizontal and vertical extent of attention, we tested whether variability of the lead car speed influenced the extent of spatial attention for younger or older drivers. For younger drivers, reaction time (RT) to light-change targets varied as a function of distance and horizontal position. For older drivers RT varied only as a function of distance. There was a distance by horizontal position interaction for younger drivers but not for older drivers. Specifically, there was no effect of horizontal position at any given level of depth for older drivers. However, for younger drivers there was an effect of horizontal position for targets further in depth but not for targets nearer in depth. With regards to workload, we found no statistically reliable evidence that variability of the lead car speed had an effect on the spatial extent of attention for younger or older drivers. In a control experiment, we examined the effects of depth on light detection when the projected size and position of the targets was constant. Consistent with our previous results, we found that drivers’ reaction time to light-change targets varied as a function of distance even when 2D position and size were controlled. Given that depth is an important dimension in driving performance, an important issue for assessing driving safety is to consider the limits of attention in the depth dimension. Therefore, we suggest that future research should consider the importance of depth as a dimension of spatial attention in relation to the assessment of driving performance.

Enhancing Driver Car-Following Performance with a Distance and Acceleration Display

A car-following assisting system named the rear window notification display (RWND) was developed, with the aim of improving a driver's manual car-following performance. The RWND presented lead-car acceleration and time headway (THW) (i.e., intervehicle distance divided by the speed of the following car) on the rear window of a lead car, which was driven automatically. A simulator-based experiment with 22 participants showed that the RWND reduced both the mean and standard deviation of THW but did not increase the occurrence of potentially unsafe headways of less than 1 s. The parameter estimation of a common linear car-following model showed that drivers accomplished the performance improvements by adopting higher control gains with respect to intervehicle distance, relative speed, and acceleration. A postexperiment questionnaire revealed that the display was generally not regarded as a distraction nor did participants think that it provided too much information, with means of 4.0 and 2.9, respectively, on a scale from one (completely disagree) to ten (completely agree). The results of this study suggest that the RWND can be used along with Cooperative Adaptive Cruise Control to increase traffic flow without degrading safety.

The role of uncertainty and reward on eye movements in a virtual driving task

Eye movements during natural tasks are well coordinated with ongoing task demands and many variables could influence gaze strategies. Sprague and Ballard (2003) proposed a gaze-scheduling model that uses a utility-weighted uncertainty metric to prioritize fixations on task-relevant objects and predicted that human gaze should be influenced by both reward structure and task-relevant uncertainties. To test this conjecture, we tracked the eye movements of participants in a simulated driving task where uncertainty and implicit reward (via task priority) were varied. Participants were instructed to simultaneously perform a Follow Task where they followed a lead car at a specific distance and a Speed Task where they drove at an exact speed. We varied implicit reward by instructing the participants to emphasize one task over the other and varied uncertainty in the Speed Task with the presence or absence of uniform noise added to the car's velocity. Subjects' gaze data were classified for the image content near fixation and segmented into looks. Gaze measures, including look proportion, duration and interlook interval, showed that drivers more closely monitor the speedometer if it had a high level of uncertainty, but only if it was also associated with high task priority or implicit reward. The interaction observed appears to be an example of a simple mechanism whereby the reduction of visual uncertainty is gated by behavioral relevance. This lends qualitative support for the primary variables controlling gaze allocation proposed in the Sprague and Ballard model.

All aboard the robotic road train

Public transportation has its own drawbacks: Buses and trains don't start at your home and don't end at your destination, nor do they leave just when you'd like or even guarantee you a seat. To get the best of both worlds, we could teach our cars to work together, as closely grouped cyclists do in a peloton. The lead car could be entrusted to a professional driver to whom the other drivers would of course each pay a small fee; all the other cars would follow it automatically. The cars would all use networked communications coupled with the optical or electromagnetic sensors already installed in some luxury cars to avoid head-on collision, stay in the proper lane, and brake in case of emergency. These systems have been developed at great expense to provide active safety, as distinguished from the passive kind afforded by seat belts. But this investment, having been made, can now be exploited for other things-like allowing you to relax and read the paper. If only we'd let them. Active systems are improving at a splendid rate. Adaptive cruise control, for example, maintains a car's speed while using radar or lidar to keep a safe distance from the car in front of it, thus automating much of the braking and accelerating. The latest generation of this system can follow a lead car from highway speed to a stop and then resume automatically when that car drives away. Soon the system will get additional data from vision sensors and digitized maps and additional support for the steering, allowing it to slow down on curves.

Effects of Task-Irrelevant Cars on Judgments of Deceleration and Time-to-Contact During Car-Following

Rear-end collisions represent over 25% of crashes with other moving vehicles (NHTSA, 2005). Factors that potentially contribute to such accidents include a driver’s ability to respond to a lead car’s deceleration and to estimate how much time remains until a collision would occur (DeLucia & Tharanathan, 2009). Prior research (Oberfeld & Hecht, 2008) showed that time-to-contact (TTC) judgments of approaching objects were influenced by task-irrelevant distractor objects. This finding has implications for rear-end collisions when drivers must detect a lead car’s deceleration amidst surrounding cars. However, Oberfeld and Hecht simulated a stationary observer rather than a moving observer which is more representative of driving. We measured effects of task-irrelevant distractor cars on judgments of a lead car’s deceleration during simulations of self motion. Observers viewed car-following scenarios in which only a lead car was present or a lead car and two distractor cars were present in adjacent lanes. The lead car decelerated 10 s or 15 s after the scene’s onset, at either 4 ft/s2 (slow) or 10 ft/s2 (fast). The distractor cars decelerated earlier, later, or at the same time as the lead car, or never decelerated. Brake lights were disabled. Observers were instructed to maintain 40 mph and to press a button as soon as the lead car decelerated. Mean response time was significantly longer in the presence of distractor cars when the lead car decelerated 15 s after the scene’s onset, at 4 ft/s2. In a separate study of a TTC (prediction-motion) task used by Oberfeld and Hecht, car-following speed was pre-set to 40 mph, and the lead car decelerated for 3 s and then disappeared. Observers pressed a button when they thought a collision would occur. Distractor cars affected TTC judgments only when deceleration was concurrent with the lead car. In contrast to deceleration detection, TTC judgments were significantly shorter when distractor cars were present compared with absent, suggesting that effects of distractor cars are task-dependent. In summary, task-irrelevant distractor cars can affect deceleration detection and TTC judgments. The implication is that drivers cannot always ignore task-irrelevant cars on the road. Cars on lanes that do not have immediate consequences for a rear-end collision nevertheless may affect a driver’s response to a lead car’s deceleration. Warning systems designed to prevent rear-end collisions may be needed more in relatively dense traffic when drivers are potentially distracted by task-irrelevant cars.

Why do drivers maintain short headways in fog? A driving-simulator study evaluating feeling of risk and lateral control during automated and manual car following

Drivers in fog tend to maintain short headways, but the reasons behind this phenomenon are not well understood. This study evaluated the effect of headway on lateral control and feeling of risk in both foggy and clear conditions. Twenty-seven participants completed four sessions in a driving simulator: clear automated (CA), clear manual (CM), fog automated (FA) and fog manual (FM). In CM and FM, the drivers used the steering wheel, throttle and brake pedals. In CA and FA, a controller regulated the distance to the lead car, and the driver only had to steer. Drivers indicated how much risk they felt on a touchscreen. Consistent with our hypothesis, feeling of risk and steering activity were elevated when the lead car was not visible. These results might explain why drivers adopt short headways in fog. Practitioner Summary: Fog poses a serious road safety hazard. Our driving-simulator study provides the first experimental evidence to explain the role of risk-feeling and lateral control in headway reduction. These results are valuable for devising effective driver assistance and support systems.

Driving With a Partially Autonomous Forward Collision Warning System

The effects of a forward collision warning (FCW) and braking system (FCW+) were examined in a driving simulator study analyzing driving and gaze behavior and the engagement in a secondary task. In-depth accident analyses indicate that a lack of appropriate expectations for possible critical situations and visual distraction may be the major causes of rear-end crashes. Studies with FCW systems have shown that a warning alone was not enough for a driver to be able to avoid the accident. Thus,an additional braking intervention by such systems could be necessary. In a driving simulator experiment, 30 drivers took part in a car-following scenario in an urban area. It was assumed that different lead car behaviors and environmental aspects would lead to different drivers' expectations of the future traffic situation. Driving with and without FCW+ was introduced as a between-subjects factor. Driving with FCW+ resulted in significantly fewer accidents in critical situations. This result was achieved by the system's earlier reaction time as compared with that of drivers. The analysis of the gaze behavior showed that driving with the system did not lead to a stronger involvement in secondary tasks. The study supports the hypotheses about the importance of missing expectations for the occurrence of accidents. These accidents can be prevented by an FCW+ that brakes autonomously. The results indicate that an autonomous braking intervention should be implemented in FCW systems to increase the effectiveness of these assistance systems.

Distributed Receding Horizon Control of Vehicle Platoons: Stability and String Stability

This paper considers the problem of distributed control of a platoon of vehicles with nonlinear dynamics. We present distributed receding horizon control algorithms and derive sufficient conditions that guarantee asymptotic stability, leader-follower string stability, and predecessor-follower string stability, following a step speed change in the platoon. Vehicles compute their own control in parallel, and receive communicated position and velocity error trajectories from their immediate predecessor. Leader-follower string stability requires additional communication from the lead car at each update, in the form of a position error trajectory. Predecessor-follower string stability, as we define it, implies leader-follower string stability. Predecessor-follower string stability requires stricter constraints in the local optimal control problems than the leader-follower formulation, but communication from the lead car is required only once at initialization. Provided an initially feasible solution can be found, subsequent feasibility of the algorithms are guaranteed at every update. The theory is generalized for nonlinear decoupled dynamics, and is thus applicable to fleets of planes, robots, or boats, in addition to cars. A simple seven-car simulation examines parametric tradeoffs that affect stability and string stability. Analysis on platoon formation, heterogeneity and size (length) is also considered, resulting in intuitive tradeoffs between lead car and following car control flexibility.

Analysis and Simulation of Air Drag in Vehicles Close-Following

Vehicles drag reductions arising from close spacing are studied and verified by some research institutes. But this solution was queried by an experiment carried in RMIT University in 2006. Based on two standard Ahmed Bodies, Computational Fluid Dynamics(CFD) method is used to study this problem in this paper. The calculation results by comparing four different CFD turbulence models show that the drag coefficient of the rear car is more than the lead car, and even more than the isolated car when the space of these two cars is less than one time of car length. Furthermore, the calculate results of these four turbulence models show that the standard model is the best model to simulate this problem, and different far field condition will influence the calculate results much more. Therefore, the research of this paper verifies that drag reductions from close spacing still need to be studied.

The End of the Chinese Dream: Why Chinese People Fear the Future by Gerard Lemos (review)

Reviewed by: The End of the Chinese Dream: Why Chinese People Fear the Future by Gerard Lemos Franklin J. Woo (bio) Gerard Lemos. The End of the Chinese Dream: Why Chinese People Fear the Future. New Haven, CT: Yale University Press, 2012. ix, 320 pp. Hardcover $38.00, isbn 978-0-300-16924-9. During an October 2012 travel study to China, our group witnessed one day in Xian a fleet of three Mercedes-Benzes driving into the court of the Crystal Island Hotel, where we were staying. The passengers were all part of an excited wedding party, with one member rushing to light a thirty-foot-long chain of firecrackers, signaling the arrival of the bride and groom. Such a scene reminded me of an even more opulent scene posted on the Internet in 2011: a YouTube scene of the wedding of a coal magnate family in Shanxi Province. Parading its wealth through the streets of Datong, the wedding party involved four Rolls Royces leading the opulent parade, followed by four Ferraris and six Jeeps carrying the camera crew. Between the eight lead cars and the six Jeeps were six Mercedes-Benzes, six Bentleys, and one Hummer as a backup. These people were obviously not the fear-the-future Chinese that Gerard Lemos writes about in The End of the Chinese Dream. They are part of the superrich, the “princelings” (p. 45) of the powerful elites, mentioned by the author only as stark contrast to the poor and marginalized people, the main focus of his book. Lemos’s Chinese are those who fall between the cracks and are left behind in a modernizing China with an unrelenting drive to move ahead. They are people whose iron rice bowls have vanished with the closing or privatizing of the nation’s nonprofit, state-owned enterprises, mostly factories that once provided their workers with housing, food subsidies, health care, the education of children, and pensions upon retirement. Included are the unfortunate farmers whose land was grabbed by rapacious commercial and housing developers with compensation (if paid) less than the worth of the land and nowhere proportionate to the expensive structures being built. Overnight, these people found their security gone—having to fend for themselves with an inflationary cost of living, heath care with an expensive price tag, and hospitalization that, for most, was out of reach. Furthermore, how to pay for the expensive tuition and cost of books and school supplies for their children is a new burden, which under the cradle-to-grave coverage system of former state enterprises was a part of the overall benefits. As Lemos describes it, Economic growth since the 1980s has been achieved at the expense of another set of trauma to add to those of the 1950s, 1960s, and 1970s. The social safety net has been whisked away from more than 50 million people working in state-owned factories in cities. Forty to 50 million farmers have lost their land and many are poverty-stricken and devoid of hope. Hardship is unabated for several hundred million people in the countryside. Up to 200 million migrants float on the peripheries of the cities detached from the past and with no certainty for the [End Page 454] future. Communities have been demolished and dispersed by wholesale urban redevelopment sweeping aside families and ways of life with deep roots. (p. 211) In short, modernization brings manifold and unintended deleterious consequences, including the erosion of the lifestyle and culture of the people. An expert in social policy in England, Lemos was in China for a seminar and ended up teaching in Chongqing. For a person who has seriously studied China only since 2006 (p. 5), he has done remarkably well in providing in his book a more complete, albeit dismal picture of a China “run by the wealthy for the benefit of the wealthy” (p. 2). His description of the city of Chongqing (declared a municipality since 1998) is informative and comprehensive, giving a vivid picture of its stark contrasts: The super-elite are hidden away in leafy, gated communities near golf courses. The upward mobile young professional middle classes have moved to city centre high-rise flats, near...

Evaluating the Impact of Processing Spoken Words on Driving

The potential impact on driving of the processing of a single, auditorily presented word is analyzed in this work. Because driving is a complex cognitive activity that involves the integration and coordination of multiple subprocesses, the authors narrowed the scope of the research to concentrate on one critical task involved in driving: driver braking response. If two tasks have to be performed concurrently and both of them require access to a capacity-limited system, then performance in one or both of the tasks will dramatically worsen because the two processes will compete for access to cognitive resources. It has been shown that both word recognition and driving require central resources; therefore, these tasks are likely to interfere with each other. In the experiments, participants were required to perform two tasks during simulated driving. In the word recognition task, participants had to categorize auditorily presented words. In the braking task, participants depressed a brake pedal in response to the lead car's brake lights. The interval of time between the onset of the tasks’ stimuli was varied. Braking responses were substantially slower as the overlap between tasks increased. This finding demonstrates that the processing of a single word hinders driving performance. The experiments carried out have significant implications in the field of road safety. Many situations, such as cell phone ringing, cell phone conversations, auditory tips from navigation systems, and auditory alerts from driver warning systems, are similar to those studied. The experiments suggest that all these situations can negatively affect a driver's response time, increasing the likelihood of near misses and accidents.

Task-dependent gaze priorities in driving

During complex visuo-motor tasks, gaze behavior is largely controlled by the current task [1]. However, it is unclear how gaze allocation is accomplished when confronted with multiple task demands, especially in dynamic and unpredictable environments, as in driving. This has been called the “scheduling problem”. One simple solution is to actively search the visual scene for potentially important information (e.g. pedestrians, other cars, lane centering) at regular intervals (round-robin strategy). Another is to weight search frequency by the importance of the sub-tasks, as in reward-based models of gaze allocation. Alternatively, participants might rely on attentional capture by salient events. To address this question, we manipulated the tasks demands of participants who drove in a virtual environment including other cars, pedestrians and urban scenery. While driving there are several concurrent sub-goals, including avoiding other cars, following a lead car, and avoiding pedestrians. We recorded and analyzed gaze behavior for these driving sequences. These data provide the ground truth for gaze allocation as well as unique traversals through the environment for use in simulations. We simulate gaze allocation as a high-level, object based scheduling problem where covert object searches are engaged at regular intervals. If the object is present onscreen, an overt fixation occurs. Simulations were run with a uniform distribution across object categories and using a round-robin strategy. We found neither to be a good predictor of gaze allocation. Weighting search frequency by participants' global fixation distributions provides a better fit and using fixation distributions for local scene context provides the best. If subjects' fixation distributions are proportional to task priority, we discuss how a task-based reinforcement-learning model may accomplish such gaze allocation. [1] Hayhoe, M., & Ballard, D. (2005). Eye movements in natural behavior. Trends in Cognitive Sciences, 9(4), 188–193.

Miserable banditti: the pot-head outlaws of rural Greece

The plan seemed simple enough. One car in the lead to scout for roadblocks, and the old van following behind carrying a kilo of pot. In the mountains of southern Greece, roadblocks are fairly common, especially at night. The blocks are carried out by special anti-narcotics police, the EKAM. Locals call them 'Cherokees' because of the distinctive black Jeeps they drive as well as the cowboys-and-Indians quality of their interdiction methods. Roadblocks often appear out of nowhere, a clutch of black Cherokees off the side of the road with a group of black-suited paramilitary police, often with black ski masks covering their faces. In areas of heavy drug trafficking, roadblocks are often backed by snipers positioned in the hills above the roadway, or in helicopters. Locals transporting pot generally travel in pairs, with a lead car for spotting roadblocks and warning those behind via cell phone. As a backup, the driver of the second car with the pot also carries a small bottle of gasoline. In the event he is pulled over, he is supposed to pour the gasoline in the car and ignite it, destroying the pot and the car. That way he can plead to a lesser charge and avoid jail time. None of the farmers I was with had known anyone who actually carried out this last-ditch defense, but they seemed confident it would work if needed. That night, fortunately, everything went smoothly. On the drive from the mountains, through the central plains, and onto the Aegean coast, there was no sign of the EKAM. We arrived a little after 4 a.m. and celebrated with a big three-paper spliff before retiring for a few hours sleep. The farmers I was with do this trip once or twice a year. Two of them, Petro and Taki, are truck farmers who sell produce at the Athens street markets. The other, Gianni, produces high-quality olive oil. Together they are the core of a group of 6-10 pot smokers who hang out together and exchange weed. In their village of around 450 residents, there are several such groups, usually divided by generations. Petro, Taki, and Gianni are in their early-40s

Expectations while car following—The consequences for driving behaviour in a simulated driving task

The purpose of this study was to better understand the causes of driver errors in the context of rear-end crashes. When drivers move in traffic they generate an overall assessment of the driving situation and what will happen in the near future. Certain cues in the traffic environment may create an expectation that some specific action is required. The more relevant cues are present, the more the driver will expect that some kind of intervention may be required. In contrary, if hardly any or no relevant cues are present, the driver does not anticipate that an imminent reaction will be necessary. This idea is supported by results from accident analyses which showed that in many cases, rear-end crashes occur in situations which are usually easy to handle (e.g. straight roads, low traffic density). In these situations, drivers may not anticipate that the driver in front will brake and they are thus following too closely to be able to react in time when the front vehicle suddenly brakes or stops. In order to test this hypothesis experimentally, in a driving simulator experiment different expectations were generated by varying the behaviour of a lead car (different braking behaviour, signalling or not before a turn). Driver behaviour was examined after these variations. The analyses partially confirm the influence of different expectations generated by the lead car's behaviour in the first phase of the scenario. Drivers with a respective expectation reacted faster when the car in front suddenly braked and signalled their manoeuvre before turning right at an intersection. However, during a car following phase, drivers did not adapt their speed or distance depending on this expectation. These results can be used to adapt a driver assistance system in car following situations. This should warn and intervene, especially in cases when drivers do not foresee the need for action and therefore cannot react in time.

Anticipation in car following: Modelling expectations for the development of driver assistance systems

The EU-project ISi-PADAS aims to integrate driver models into the development process of driver assistance systems. Driver modeling is used to predict whether the driver is likely to not react adequately to the driving situation and whether the PADAS should intervene. It is based on empirical investigations. An accident analysis showed that in many rear end accidents, driver's inadequate expectations about the lead car may be a major factor in causing the accident. A driving simulator study was conducted to examine this hypothesis. The behavior of a lead car was varied in order to create different expectations. Attention allocation and driver behavior was examined. The results are partially consistent with the hypotheses

Merging into heavy motorway traffic by young and elderly drivers

An increase in the number of Heavy Goods Vehicles on motorways may lead to additional problems in the interaction with an increased number of elderly drivers. Elderly drivers suffer from reduced information processing speed and capacity, and in general effectively compensate for this by taking more time. However, this strategy, regulating task demands by slowing down will make merging into motorway traffic actually more difficult. In an experiment performed in a driving simulator, young and elderly drivers merged into motorway traffic. Driver behaviour and mental workload were studied while the following factors were manipulated: type of traffic and density of Heavy Goods Vehicles on the main road, the length of the acceleration lane, presence of a slowly driving lead car, and presence of a driver support system that encouraged the drivers to speed up if their speed was too low. Results show that the effects of an increased number of Heavy Goods Vehicles on the main road were not more adverse for elderly than for the young participants, with the exception that elderly drivers merged at a lower speed. This lower speed could make the manoeuvre more risky in real traffic. The support system and an extended acceleration lane facilitated merging, while a slowly driving lead car impeded completion of the manoeuvre.

Responses to deceleration during car following: Roles of optic flow, warnings, expectations, and interruptions.

More than 25% of accidents are rear-end collisions. It is essential to identify the factors that contribute to such collisions. One such factor is a driver's ability to respond to the deceleration of the car ahead. In Experiment 1, we measured effects of optic flow information and discrete visual and auditory warnings (brake lights, tones) on responses to deceleration during car following. With computer simulations of car-following scenes, university students pressed a button when the lead car decelerated. Both classes of information affected responses. Observers relied on discrete warnings when optic flow information was relatively less effective as determined by the lead car's headway and deceleration rate. This is consistent with DeLucia's (2008) conceptual framework of space perception that emphasized the importance of viewing distance and motion (and task). In Experiment 2, we measured responses to deceleration after a visual interruption. Scenes were designed to tease apart the role of expectations and optic flow. Responses mostly were consistent with optic flow information presented after the interruption rather than with putative mental expectations that were set up by the lead car's motion prior to the interruption. The theoretical implication of the present results is that responses to deceleration are based on multiple sources of information, including optical size, optical expansion rate and tau, and discrete warnings that are independent of optic flow. The practical implication is that in-vehicle collision-avoidance warning systems may be more useful when optic flow is less effective (e.g., slow deceleration rates), implicating a role for adaptive collision-warning systems.