Oncoming Vehicle Research Articles

Drivers' decision-making when attempting to cross an intersection results from choice between affordances

In theory, a safe approach to an intersection implies that drivers can simultaneously manage two scenarios: they either choose to cross or to give way to an oncoming vehicle. In this article we formalize the critical time for safe crossing (CTcross) and the critical time for safe stopping (CTstop) to represent crossing and stopping possibilities, respectively. We describe these critical times in terms of affordances and empirically test their respective contribution to the driver's decision-making process. Using a driving simulator, three groups of participants drove cars with identical acceleration capabilities and different braking capabilities. They were asked to try to cross an intersection where there was an oncoming vehicle, if they deemed the maneuver to be safe. If not, they could decide to stop or, as a last resort, make an emergency exit. The intersections were identical among groups. Results showed that although the crossing possibilities (CTcross) were the same for all groups, there were between-group differences in crossing frequency. This suggests that stopping possibilities (CTstop) play a role in the driver's decision-making process, in addition to the crossing possibilities. These results can be accounted for by a behavioral model of decision making, and provide support for the hypothesis of choice between affordances.

The Prevalence and Correlates of Risky Driving Behavior Among National Guard Soldiers

Objective: Previous studies have reported that risky driving is associated with deployment and combat exposure in military populations, but there is limited research on risky driving among soldiers in the National Guard and Reserves, a group increasingly deployed to active international conflicts. The goal of this analysis was to assess the prevalence of risky driving and its demographic, mental health, and deployment-related correlates among members of the Ohio Army National Guard (OHARNG).Methods: The study group comprised 2,616 eligible OHARNG soldiers enlisted as of June 2008, or who enlisted between June 2008 and February 2009. The main outcome of interest was the prevalence of risky driving behavior assessed using six questions: “How often do you use seat belts when you drive or ride in a car?”; “In the past 30 days, how many times have you driven when you've had perhaps too much to drink?”; “In the past year, have you ever become impatient with a slow driver in the fast lane and passed them on the right?”; “In the past year have you crossed an intersection knowing that the traffic lights have already changed from yellow to red?”; “In the past year have you disregarded speed limits late at night or early in the morning?”; and “In the past year have you underestimated the speed of an oncoming vehicle when attempting to pass a vehicle in your own lane?” We fit multiple logistic regression models and derived the adjusted prevalence of risky driving behavior for soldiers with mental health conditions, deployment experience, exposure to combat or trauma, and psychosocial stressors or supports.Results: The prevalence of risky driving was higher in soldiers with a history of mental health conditions, deployment to a conflict area, deployment-related traumatic events, and combat or post-combat stressors. In contrast, the prevalence of risky driving was lower for soldiers who reported high levels of psychosocial support.Conclusions: Efforts to mitigate risky driving in military populations may be more effective if they incorporate both targeted messages to remediate dangerous learned driving behaviors and psychosocial interventions to build resilience and address underlying stressors and mental health symptoms.

Effects of Oncoming Vehicle Size on Overtaking Judgments

In 2011, 89,000 accidents in the United States involved a vehicle passing another vehicle, which resulted in 740 deaths and 19,000 injuries (NHTSA, 2011). When passing a vehicle on a two-way highway (overtaking), a driver often must temporarily cross into the opposite lane of traffic, and may face oncoming vehicles. To avoid a collision with an oncoming vehicle, the overtaking driver must estimate the time remaining until a collision would occur with the vehicle. Although information about an oncoming vehicle’s time-to-collision is theoretically available in the optical invariant tau (Lee, 1976), it is below threshold during high-speed overtaking maneuvers, which require a large passing distance. Under such conditions, we expect drivers to rely on the oncoming vehicle’s apparent distance and velocity, and thus depth cues such as relative size. We used a driving simulator to determine whether overtaking judgments are influenced by an oncoming vehicle’s size, and on whether such judgments differ between active driving and passive viewing. Twenty-four participants viewed computer-generated scenes in which they were following a lead vehicle on a straight, two-lane, two-way highway. At the start of each scene an oncoming vehicle (motorcycle, car, delivery truck) was visible in the opposite lane. Seven seconds after the scene an auditory tone signaled participants to make an overtaking decision. Participants in the active condition passed the lead vehicle if they thought it was safe to do so. Participants in the passive condition indicated whether it was safe to pass by pressing buttons on the steering wheel. We manipulated the participant’s (and lead vehicle’s) speed (48.28 km/h, 64.37 km/h, 80.47 km/h) and the oncoming vehicle’s speed (72.42 km/h, 88.51 km/h, 104.61 km/h) and distance when the tone occurred (457.20 m, 609.60 m). This resulted in 9 safe and 9 unsafe temporal gaps based on an equation generated from analyses of actual overtaking performance (Gordon & Mast, 1970). Results indicated more accepted gaps and more false alarms (accepted gap when unsafe) in front of motorcycles than larger cars or trucks. The judgments made by participants in the active and passive conditions did not differ. Analyses of signal detection theory measures of sensitivity (d-prime) and response bias (beta) suggested that the effect of vehicle size was due to shifts in response bias rather than sensitivity. Results have implications for traffic safety and for the potential role of driver-assistance technologies.

Seeing pedestrians at night: effect of driver age and visual abilities.

To quantify the effects of driver age on night-time pedestrian conspicuity, and to determine whether individual differences in visual performance can predict drivers' ability to recognise pedestrians at night. Participants were 32 visually normal drivers (20 younger: M=24.4years±6.4years; 12 older: M=72.0years±5.0years). Visual performance was measured in a laboratory-based testing session including visual acuity, contrast sensitivity, motion sensitivity and the useful field of view. Night-time pedestrian recognition distances were recorded while participants drove an instrumented vehicle along a closed road course at night; to increase the workload of drivers, auditory and visual distracter tasks were presented for some of the laps. Pedestrians walked in place, sideways to the oncoming vehicles, and wore either a standard high visibility reflective vest or reflective tape positioned on the movable joints (biological motion). Driver age and pedestrian clothing significantly (p<0.05) affected the distance at which the drivers first responded to the pedestrians. Older drivers recognised pedestrians at approximately half the distance of the younger drivers and pedestrians were recognised more often and at longer distances when they wore a biological motion reflective clothing configuration than when they wore a reflective vest. Motion sensitivity was an independent predictor of pedestrian recognition distance, even when controlling for driver age. The night-time pedestrian recognition capacity of older drivers was significantly worse than that of younger drivers. The distance at which drivers first recognised pedestrians at night was best predicted by a test of motion sensitivity.

Accident analysis on intersection right turning by using driving simulator

We simulated an accident prone traffic scene with our highly realistic driving simulator. In this research, the scene features a motorcycle suddenly appearing from a behind a line of vehicles in a congested street into the path of an oncoming car turning right at an intersection. As a result, the driver often only has less than one second before applying brake, that is to say, the permitted avoidance time is short. To avoid a collision between a vehicle turning right and an oncoming vehicle, it is important to predict the possibility of danger in the intersection and lower the vehicle speed while driving through the intersection. Driving behaviour in a collision was compared among different ages of drivers and manoeuvre differences before collision were confirmed. The analysis of the collision patterns and driver collision avoidance behaviour described above suggests that enhancing forward collision avoidance support systems.

Human Perceptions of Vehicle Turning Intention

All pedestrians, drivers, and cyclists regularly make predictions about where they think an oncoming vehicle is intending to travel so that they can successfully and safely navigate road systems. Despite the importance of these predictions, the effectiveness of this process is currently poorly understood, as all existing research has been focused on predictions from in-vehicle technologies. This study investigated how well observers were able to predict a vehicle's turning intention as it approached an intersection. Logistic regression analysis was used to explore the explanatory variables involved in the success of this process. An interactive touch screen experiment was developed, and more than 100 participants attempted to predict the turning intention of several vehicles. The participants were very good overall at predicting turning intention, with a median success rate of approximately 90% when the vehicle was 0 to 20 m (0 to 21.9 yd) away from the intersection; however, the median success rate fell substantially to approximately 70% when the vehicle was 30 to 50 m (32.8 to 54.7 yd) away. Other key explanatory variables included both vehicle-specific factors (e.g., use of indicator lights) and, crucially, the intersection layout, which together provided valuable information on the relationship between intersection design and road safety.

The Auto-Dim of Vehicle Head Light using RF-waves

The paper is about developing a cost effective and simple way to auto dim the head light of automobile using RF communication approach. Vehicles travelling at night usually face a problem of distraction for the drivers when an opposite vehicle(s) with high-beam switched on come about 200 meters apart from each other's vehicle. This project is about automatically diming the head light of opposite vehicles which has high-beam switched-on from high-beam to low-beam. This is done using the RF wave to communicate the proximity of the on-coming vehicles and also a photodiode to detect the overall intensity of the high-beam to the driver. Each vehicle is fitted with the RF transmitter and receiver to detect the proximity of the vehicles. A photodiode is to detect the intensity of the high-beam of the opposite vehicle, after confirming the proximity of the vehicle. Consider Two vehicle 'A' and 'B' travelling opposite direction to each other during night with their high beam switched on, once 'A' and 'B' come to about 200 meter to each other (this triggers the RF communication, the high beam of the 'A' vehicle start affecting the driver of the 'B' vehicle or vice-versa, this is detected by photo diode (which is activated only when RF communication is triggered. To prevent this distraction of the driver, the high-beam of the opposite vehicle is dimed to low-beam.

Crossing Roads Safely: Influence of Various Vehicle Types in Gap Selection by Pedestrians

This paper analyzed the relationship between the gap selection and the types of oncoming vehicle in the process of pedestrians crossing the road. The oncoming vehicles were divided into large and small vehicle; six groups of pedestrians were recorded, young-male, mid-aged-male, old-male, young-female, mid-aged-female and old-female. The accepted gaps were recorded and analyzed using one-way ANOVA analysis. The results showed that, oncoming vehicles type had significant impact upon gap selection of pedestrians. A large oncoming vehicle had a shorter selected gap than a small oncoming vehicle. It is concluded that pedestrians have a smaller perceived velocity and overestimate the gap, large oncoming vehicle arrive conflict point. However, the overestimated gap was likely not safe to crossing the road. So, at no signal control intersection, a strict speed limit was necessary for large vehicle.

Visibility of Pedestrian by the Headlight in Consideration of the Glare to the Driver on the Oncoming Vehicle

Visibility of Pedestrian by the Headlight in Consideration of the Glare to the Driver on the Oncoming Vehicle

J102013 ドライビングシミュレータを用いた運転支援システム設計(〔J102-01〕1DCAEを活用した設計と教育)

In this paper we propose Operator-in-the-loop Design to design a driving support system for a vehicle using a driving simulator. The functional requirements of the brake assist system can be defined from the analysis based on a scenario in turning right involving a driver in the driving simulator. Also the control system is designed in the loop of a driver. It is verified using the driving simulator that the driving support system we designed is effective to assist the driver's brake in turning right with an oncoming vehicle.

Effects of mobile Internet use on college student pedestrian injury risk

BackgroundCollege-age individuals have the highest incidence of pedestrian injuries of any age cohort. One factor that might contribute to elevated pedestrian injuries among this age group is injuries incurred while crossing streets distracted by mobile devices. ObjectivesExamine whether young adult pedestrian safety is compromised while crossing a virtual pedestrian street while distracted using the Internet on a mobile “smartphone.” MethodA within-subjects design was implemented with 92 young adults. Participants crossed a virtual pedestrian street 20 times, half the time while undistracted and half while completing an email-driven “scavenger hunt” to answer mundane questions using mobile Internet on their cell phones. Six measures of pedestrian behavior were assessed during crossings. Participants also reported typical patterns of street crossing and mobile Internet use. ResultsParticipants reported using mobile Internet with great frequency in daily life, including while walking across streets. In the virtual street environment, pedestrian behavior was greatly altered and generally more risky when participants were distracted by Internet use. While distracted, participants waited longer to cross the street (F=42.37), missed more safe opportunities to cross (F=42.63), took longer to initiate crossing when a safe gap was available (F=53.03), looked left and right less often (F=124.68), spent more time looking away from the road (F=1959.78), and were more likely to be hit or almost hit by an oncoming vehicle (F=29.54; all ps<0.01). Results were retained after controlling for randomized order; participant gender, age, and ethnicity; and both pedestrian habits and mobile Internet experience. ConclusionPedestrian behavior was influenced, and generally considerably riskier, when participants were simultaneously using mobile Internet and crossing the street than when crossing the street with no distraction. This finding reinforces the need for increased awareness concerning the risks of distracted pedestrian behavior.

Effect of Car/Truck Differential Speed Limits on Two-lane Highways Safety Operation Using Microscopic Simulation

The safety implications of car-truck speed limits have not been adequately researched for two-lane highways. On two-lane highways speed controls can have a significant effect on vehicles interactions. Two different types of speed control strategies are considered: Uniform and Differential. Safety implications are considered using three overtaking-related indicators: Number of vehicles overtaking, 2) Percentage time spent in “desire to overtake mode”, and 3) Average Time-to-Collision with the on-coming vehicle prior to returning to the original lane. Vehicle interactions affecting safety are estimated through the application of a calibrated microscopic traffic simulation model to a 6Km straight segment of two-lane highway.

통계적 특징 기반 SVM을 이용한 야간 전방 차량 검출 기법

A driver assistance system is critical to improve a convenience and stability of vehicle driving. Several systems have been already commercialized such as adaptive cruise control system and forward collision warning system. Efficient vehicle detection is very important to improve such driver assistance systems. Most existing vehicle detection systems are based on a radar system, which measures distance between a host and leading (or oncoming) vehicles under various weather conditions. However, it requires high deployment cost and complexity overload when there are many vehicles. A camera based vehicle detection technique is also good alternative method because of low cost and simple implementation. In general, night time vehicle detection is more complicated than day time vehicle detection, because it is much more difficult to distinguish the vehicle's features such as outline and color under the dim environment. This paper proposes a method to detect vehicles at night time using analysis of a captured color space with reduction of reflection and other light sources in images. Four colors spaces, namely RGB, YCbCr, normalized RGB and Ruta-RGB, are compared each other and evaluated. A suboptimal threshold value is determined by Otsu algorithm and applied to extract candidates of taillights of leading vehicles. Statistical features such as mean, variance, skewness, kurtosis, and entropy are extracted from the candidate regions and used as feature vector for SVM(Support Vector Machine) classifier. According to our simulation results, the proposed statistical feature based SVM provides relatively high performances of leading vehicle detection with various distances in variable nighttime environments.

Issues in motorcycle sensory and cognitive conspicuity: The impact of motorcycle low-beam headlights and riding experience on drivers’ decisions to turn across the path of a motorcycle

BackgroundCrashes involving a passenger car and a motorcycle, where the car is turning across the path of the motorcycle, are a major crash type of motorcycle riders. It has been proposed that the incidence of such crashes could be reduced through improvements in motorcycle conspicuity. Operation of low-beam headlights on motorcycles has been discussed as one approach for improving the “sensory conspicuity” of motorcycles during daylight hours, whilst previous experience as a rider may serve to heighten “cognitive conspicuity” through raised awareness of motorcyclists on our roads. MethodTwenty-three experienced car drivers with no riding experience (“drivers”) and 20 experienced car drivers who were also motorcycle riders (“driver–riders”) completed a series of trials in a driving simulator where their task in each trial was to turn ahead of an oncoming vehicle if they felt that they had sufficient room to do so safely. A key manipulation across trials was whether the oncoming vehicle was a motorcycle with headlights on, or a motorcycle with headlights off. Time gap (short, medium, long) was also manipulated. ResultsResults indicate that, at time gaps defined in the current study as short, low-beam headlights may confer some benefit in gap acceptance by encouraging drivers to accept fewer gaps ahead of a motorcycle with headlights on than ahead of a motorcycle with headlights off. No statistically significant differences in gap acceptance between the headlight conditions were found at either the medium or long time gaps. Irrespective of time gap, driver–riders were found to adopt a more efficient turn strategy than drivers with no direct riding experience. ConclusionsOverall, the present research provides support for the use of low-beam headlights and riding experience as tools through which to augment the sensory and cognitive conspicuity of motorcycles, respectively. It is proposed that further research aim to explore directly the precise mechanisms underlying the observed effects.

Night Time Vehicle Detection

Night driving is one of the major factors which affects traffic safety. Although detecting oncoming vehicles at night time is a challenging task, it may improve traffic safety. If the oncoming vehicle is recognised in good time, this will motivate drivers to keep their eyes on the road. The purpose of this paper is to present an approach to detect vehicles at night based on the employment of a single onboard camera. This system is based on detecting vehicle headlights by recognising their shapes via an SVM classifier which was trained for this purpose. A pairing algorithm was designed to pair vehicle headlights to ensure that the two headlights belong to the same vehicle. A multi-object tracking algorithm was invoked to track the vehicle throughout the time the vehicle is in the scene. The system was trained with 503 single objects and tested using 144 587 single objects which were extracted from 1410 frames collected from 15 videos and 27 moving vehicles. It was found that the accuracy of recognition was 97.9% and the vehicle recognition rate was 96.3% which indicates clearly the high robustness attained by this system.

The neural correlates of impaired collision avoidance in hemianopic patients

The aim of this study was to assess the brain regions associated with impaired performance in a virtual, dynamic collision avoidance task, in a group of patients with homonymous visual field defects (HVFDs) because of unilateral vascular brain lesions. Overall task performance was quantitatively assessed as the number of collisions while crossing an intersection at two levels of traffic density. Twenty-six patients were divided into two subgroups using the median split method: patients with 'performance above average' (HVFD(A), i.e. lower number of collisions) and patients with 'performance below average' (HVFD(B), i.e. higher number of collisions). In order to identify the anatomical structures that might be specifically affected in HVFD(B) patients but spared in HVFD(A) patients, overlap, subtraction and voxel-based lesion-symptom mapping analyses were performed using the MRIcron software. No significant difference in collision avoidance between patients with left- and right-hemispheric lesions was revealed. Separate lesion analysis in 12 patients with right- and 14 patients with left-hemispheric lesions showed that the cortical structures associated with impaired collision avoidance were the parieto-occipital region and posterior cingulate gyrus in the right hemisphere and the inferior occipital cortex and parts of the fusiform (occipito-temporal) gyrus in the left hemisphere. In the present collision avoidance paradigm, impaired performance of patients with right-hemispheric lesions is associated with damage in the dorsal processing stream and potential impact on the visual spatial working memory (WM), while impaired performance of patients with left-hemispheric lesions is associated with damage in the ventral stream and potential impact on the visual object WM.

Drivers' Decisions to Turn Across the Path of a Motorcycle with Low Beam Headlights

Crashes involving a passenger car and a motorcycle, where the car is turning across the path of the motorcycle, are a major crash type of motorcycle riders. The incidence of such crashes could be reduced through improvements in motorcycle conspicuity. Operation of low-beam headlights on motorcycles has been discussed as one approach for improving the sensory of motorcycles during daylight hours. Forty-three experienced drivers completed a series of trials in a driving simulator where their task in each trial was to turn ahead of an oncoming vehicle if they felt that they had sufficient room to do so safely. A key manipulation across trials was whether the oncoming vehicle was a motorcycle with headlights on, or a motorcycle with headlights off. Time gap (short, medium, long) was also manipulated. At short time gaps low-beam headlights may confer some benefit in gap acceptance by encouraging drivers to accept fewer gaps ahead of a motorcycle with headlights on than ahead of a motorcycle with headlights off. No statistically significant differences in gap acceptance between the headlight conditions were found at either the medium or long time gaps. Overall the present research provides support for the use of low-beam headlights as a tool through which to augment the conspicuity of motorcycles. It is proposed that further research aim to explore directly the precise mechanisms underlying the observed effects. Language: en

Mind the gap: Training road users to use speed and distance when making gap-acceptance decisions

Accurate gap-acceptance decisions require individuals to take into account both the distance to and the speed of an oncoming vehicle. The aim of the present studies was to develop an intervention that could successfully teach road users to focus on speed as well as distance. Across three studies, participants judged whether it was safe to cross the road or not when an oncoming vehicle was approaching from different distances and at different speeds. Study 1 trialed two techniques (“standard feedback” versus “three-look”) aimed at improving gap judgments. Standard feedback involved telling participants what the actual speed of a car was after they had made an estimate, whereas the three-look technique required participants to make timed and controlled head movements when scanning the road environment. Only standard feedback increased the participants’ mean gap-acceptance accuracy (assessed using both verbal and behavioral response measures). Study 2 also trialed two techniques, the standard feedback intervention used in Study 1, and a “two-response” intervention in which participants judged whether the oncoming vehicle was traveling at an atypical or normal speed. Study 2 found the two-response intervention to be more promising than the standard feedback procedure. Finally, Study 3 used video footage of oncoming vehicles to train younger (18–27 years) and older (60–80 years) adults and found the two-response intervention to be successful at improving gap-acceptance accuracies for both age groups. However, the intervention also resulted in more conservative gap judgments from participants in the older population independent of improvements in accuracy.

Method for Evaluating Effectiveness of Information Presentation in Terms of Collision Avoidance

A methodology for evaluating the effectiveness of information presentation regarding oncoming vehicles at intersections in terms of reducing traffic accidents was proposed. In this study, a method for analyzing the accident-reduction effect is discussed based on the "integrated error of driver and system" that the authors propose. First, driver performance was analyzed in a driving simulator with the visibility range being changed and the information system used or not used. Next, a driver model simulating right turns at intersections was constructed. From these investigations, the integrated error is discussed considering the risk-taking behavior of the driver as related to system dependence. The frequency of collisions at intersections was analyzed through simulations by using this driver model. One result analyzed through this simulation study indicates that the frequency of collisions at intersections decreased from 6.1 × 10-3 to 1.0 × 10-6 when the driver used the information system for avoiding collisions.

Situation Analysis, Warnings and Emergency Braking for Collision Avoidance in Overtaking Situations - PRORETA 2

The basic concept and the practical demonstration of driver assistance functions, which early detect dangerous overtaking maneuvers on two-lane rural roads and help to prevent accidents, is presented. Based on data of an environment perception system and vehicle dynamic sensors, a situation analysis is performed, which includes a classification of the current maneuver and a prediction of the overtaking trajectory. If this analysis indicates a conflict with an oncoming vehicle, a collision avoidance strategy is initialized, which includes warnings and an automatic braking intervention. Besides the newly developed functions, the results of driving maneuvers are presented.