Improved method for roadside barrier length of need modeling using real-world trajectories

The 2011 AASHTO Roadside Design Guide (RDG) contains perhaps the most widely used procedure for choosing an appropriate length of need (LON) for roadside barriers. However, this procedure has several limitations. The procedure uses a highly simplified model of vehicle departure, and the procedure does not allow designers to specify an explicit level of protection. A new procedure for choosing LON that addresses these limitations is presented in this paper. This new procedure is based on recent, real-world road departure trajectories and uses this departure data in a more realistic way. The new procedure also allows LON to be specified for a precisely known level of protection – a level which can be based on number of crashes, injury outcomes or even estimated crash cost – while still remaining straightforward and quick to use like the 2011 RDG procedure.     

Can child-pedestrians’ hazard perception skills be enhanced?

ObjectiveTraffic collisions yield a substantial rate of morbidity and injury among child-pedestrians. We explored the formation of an innovative hazard perception training intervention – Child-pedestrians Anticipate and Act Hazard Perception Training (CA²HPT). Training was based upon enhancing participants’ ability to anticipate potential hazards by exposing them to an array of traffic scenes viewed from different angles.MethodTwenty-four 7–9-year-olds have participated. Trainees underwent a 40-min intervention of observing typical residential traffic scenarios in a simulated dome projection environment while engaging in a hazard detection task. Trainees were encouraged to note differences between the scenarios presented to them from separate angles (a pedestrian's point-of-view and a higher perspective angle). Next, trainees and control group members were required to perform crossing decision tasks.ResultsTrainees were found to be more aware of potential hazards related to restricted field of view relative to control.ConclusionsChild pedestrians are responsive to training and actively detecting materialized hazards may enrich child-pedestrians’ ability to cross roads.     

Pedestrian detection and tracking at crossroads

This paper presents a system that can perform pedestrian detection and tracking using vision-based techniques. A very important issue in the field of intelligent transportation system is to prevent pedestrians from being hit by vehicles. Recently, a great number of vision-based techniques have been proposed for this purpose. In this paper, we propose a vision-based method, which combines the use of a pedestrian model as well as the walking rhythm of pedestrians to detect and track walking pedestrians. Through integrating some spatial and temporal information grabbed by a vision system, we are able to develop a reliable system that can be used to prevent traffic accidents happened at crossroads. In addition, the proposed system can deal with the occlusion problem. Experimental results obtained by executing some real world cases have demonstrated that the proposed system is indeed superb.     

Alcoholism at the time of injury among trauma center patients: Vehicular crash victims compared with other patients

A structured in-depth interview employing standardized criteria was used to determine the prevalence of lifetime and current alcohol dependence (alcoholism) in unselected consecutive patients admitted to a regional Level I trauma center. Of 629 patients, 157 (25.0%) were current alcoholics at the time of injury. An additional 87 (13.8%) were diagnosed as lifetime non-current alcoholics. There was no significant difference in the rates of current alcohol dependence among patients injured in vehicular crashes (23.5%), other unintentional trauma victims (29.3%), and those injured as a result of violence (24.6%). Of BAC + (blood alcohol concentration positive) patients, 54.5% were current alcoholics. However, 14.4% of alcohol-negative patients were also diagnosed as alcohol dependent.     

Pedestrian detection and tracking in infrared imagery using shape and appearance

In this paper, we present an approach toward pedestrian detection and tracking from infrared imagery using joint shape and appearance cues. A layered representation is first introduced and a generalized expectation-maximization (EM) algorithm is developed to separate infrared images into background (still) and foreground (moving) layers regardless of camera panning. In the two-pass scheme of detecting pedestrians from the foreground layer: shape cue is first used to eliminate non-pedestrian moving objects and then appearance cue helps to locate the exact position of pedestrians. Templates with varying sizes are sequentially applied to detect pedestrians at multiple scales to accommodate different camera distances. To facilitate the task of pedestrian tracking, we formulate the problem of shot segmentation and present a graph matching-based tracking algorithm that jointly exploits the shape, appearance and distance information. Experimental results with both OSU Infrared Image Database and WVU Infrared Video Database are reported to demonstrate the accuracy and robustness of our algorithm.     

Double auction mechanisms on Markovian networks

This paper studies the double auction (DA) mechanism in Ma and Li (2011) for a class of exchange economies. We extend their results to more general cases where sellers and buyers each form a complex time non-homogeneous Markovian chain, as specified in Ram et al. (2009), in the communication of their private information. A numerical example is also provided. Both bubbles and crashes are observed in the example, consistent with results of our theorems. Our example and theoretical results provide new evidence that a DA mechanism, widely utilized in real exchange markets, may contribute to the excess volatility identified in Shiller (1981) and LeRoy and Porter (1981).     

VR技术对地下步行商业街心理环境辅助设计初探

文章力图以VR（虚拟现实）技术手段应用于城市地下步行商业街规划设计,来解决当前传统规划手段地下步行商业街规划中普遍存在的对其心理环境构筑的忽视和考虑不完善的诟病,以期最大限度消除规划设计中消极空间的产生,并对其关键技术进行了研究和探讨     

Retrofitting of pedestrian overpass by Truss-Z modular systems using graph-theory approach

Installing pedestrian ramps is a common improvement towards a barrier-free environment. This paper introduces a graph-theoretical method of retrofitting of a single-branch Truss-Z (TZ) ramp in a constrained environment. The results produced by this exhaustive search method are usually ideal and better than those produced previously with meta-heuristic methods.A large case study of linking two sections of the Hongo Campus of Tokyo University using an overpass in an extremely constrained environment is presented. TZ modules with 1:12 (8.3%) slope are used, which is allowable in most countries for ramps for self-powered wheelchairs.The results presented here are highly satisfactory both in terms of structural optimization and aesthetics.Visualizations of the TZ ramp system, composed of 124 units, are presented.     

Improving pedestrians’ navigation safety at night by enhancing legibility of foreground and background information on the display

Traffic intersections are dangerous areas for pedestrians at night, primarily when people use their mobile phones while walking; pedestrians’ line of sight switches between their phones and the environment, which causes inattentional blindness during emergencies. The salience of the foreground and background information is different by the lightness conditions; therefore, identifying the lightness level of the foreground and background is critical. In this study, the brightness of urban traffic intersection scenes in the nighttime was analyzed, and improved color tones of the navigation interface for enhancing information recognition were identified. Moreover, identify the balance of visual attention by adjusting lightness and color treatment between foreground and background information. A glance legibility experiment indicated that a warm color tone with contrast and gamma correction under a lighting value of 65 in the LAB color mode is the optimal recognition combination. The results of this study indicated that low gamma under high lighting effectively reduced glare-related distractions and resulted in the lowest error rate in background information recognition. This paper proposes increasing the visual attention of urban pedestrians during nighttime navigation through the balancing of the lighting of the foreground interface and the color treatment of the background. Navigating at nighttime can be safer when their attention toward the environment increases and decreases attention distraction.