Multinational vehicle license plate detection in complex backgrounds

Many methods for multinational License Plate Detection (LPD) have been proposed in recent times but most of them are not sophisticated enough to handle complex backgrounds. Moreover, their ability to handle various environmental and illumination conditions has been limited and still needs improvement. In this paper, we propose a novel technique to detect license plates of vehicles regardless of their color, size, and content. As the rear vehicle lights are an essential part of any vehicle, we reduce the image processing area to eliminate the complex background by detecting the rear-lights as the license plates are in a certain range of these lights. Heuristic Energy Map (HEM) of the vertical edge information in the Region of Interest (ROI) is calculated and area with the dense edges is selected using a unique histogram approach which is considered to be the license plate. The proposed algorithm is tested on 855 images from various countries including China, Pakistan, Serbia, Italy and various states of America. Experimental results show that the proposed method is able to detect license plates 90.4% of times despite of complex backgrounds in 0.25 s on average that can achieve real time performance.     

A multinomial logit analysis of risk factors influencing road traffic injury severities in the Erzurum and Kars Provinces of Turkey

A retrospective cross-sectional study is conducted analysing 11,771 traffic accidents reported by the police between January 2008 and December 2013 which are classified into three injury severity categories: fatal, injury, and no injury. Based on this classification, a multinomial logit analysis is performed to determine the risk factors affecting the severity of traffic injuries. The estimation results reveal that the following factors increase the probability of fatal injuries: drivers over the age of 65; primary-educated drivers; single-vehicle accidents; accidents occurring on state routes, highways or provincial roads; and the presence of pedestrian crosswalks. The results also indicate that accidents involving cars or private vehicles or those occurring during the evening peak, under clear weather conditions, on local city streets or in the presence of traffic lights decrease the probability of fatal injuries. This study comprises the most comprehensive database ever created for a Turkish sample. This study is also the first attempt to use an unordered response model to determine risk factors influencing the severity of traffic injuries in Turkey.     

Safe mobility for elderly drivers—Considerations based on expert and self-assessment

To further understand the needs of the growing population of elderly drivers and create solutions for safe mobility it is important to understand the driving scenarios and aspects in day to day traffic that may be of challenge for this group. More so, individual differences in how drivers perceive their own driving ability may have an effect on how individuals limit their mobility and/or increase their exposure to risk situations, with a potential negative effect on safety.     

On-road experiment to assess drivers’ detection of roadside targets as a function of headlight system,target placement,and target reflectance

Adaptive headlights swivel with steering input to keep the beams on the roadway as drivers negotiate curves. To assess the effects of this feature on driver’s visual performance, a field experiment was conducted at night on a rural, unlit, and unlined two-lane road during which 20 adult participant drivers searched a set of 60 targets. High- (n = 30) and low- (n = 30) reflectance targets were evenly distributed on straight road sections and on the inside or outside of curves. Participants completed three target detection trials: once with adaptive high-intensity discharge (HID) headlights, once with fixed HID headlights, and once with fixed halogen headlights. Results indicated the adaptive HID headlights helped drivers detect targets that were most difficult to see (low reflectance) at the points in curves found by other researchers to be most crucial for successful navigation (inside apex). For targets placed on straight stretches of road or on the outside of curves, the adaptive feature provided no significant improvement in target detection. However, the pattern of results indicate that HID lamps whether fixed or adaptive improved target detection somewhat, suggesting that part of the real world crash reduction measured for this adaptive system (Highway Loss Data Institute (HLDI), 2012a) may be due to the differences in the light source (HID vs. halogen). Depending on the scenario, the estimated benefits to driver response time associated with the tested adaptive (swiveling HID) headlights ranged from 200 to 380 ms compared with the fixed headlight systems tested.     

A multinomial logit model-Bayesian network hybrid approach for driver injury severity analyses in rear-end crashes

Rear-end crash is one of the most common types of traffic crashes in the U.S. A good understanding of its characteristics and contributing factors is of practical importance. Previously, both multinomial Logit models and Bayesian network methods have been used in crash modeling and analysis, respectively, although each of them has its own application restrictions and limitations. In this study, a hybrid approach is developed to combine multinomial logit models and Bayesian network methods for comprehensively analyzing driver injury severities in rear-end crashes based on state-wide crash data collected in New Mexico from 2010 to 2011. A multinomial logit model is developed to investigate and identify significant contributing factors for rear-end crash driver injury severities classified into three categories: no injury, injury, and fatality. Then, the identified significant factors are utilized to establish a Bayesian network to explicitly formulate statistical associations between injury severity outcomes and explanatory attributes, including driver behavior, demographic features, vehicle factors, geometric and environmental characteristics, etc. The test results demonstrate that the proposed hybrid approach performs reasonably well. The Bayesian network reference analyses indicate that the factors including truck-involvement, inferior lighting conditions, windy weather conditions, the number of vehicles involved, etc. could significantly increase driver injury severities in rear-end crashes. The developed methodology and estimation results provide insights for developing effective countermeasures to reduce rear-end crash injury severities and improve traffic system safety performance.     

空间句法轴线分析法在方格网城市慢行空间网络分析中的空间分割方法研究

在城市交通问题凸显的今天,慢行交通作为低碳健康的出行方式,越来越受到重视。慢行空间是慢行系统的实体表现,慢行空间网络是慢行空间的集合。文章将空间句法应用于我国普遍存在的方格网城市慢行空间网络的研究,重点介绍了应用过程中最关键的空间分割方法。文章将宣化县太阳能新城城市设计作为分析对象,验证本方法对慢行系统规划设计的指导作用。最后,提出分析中的不足,并展望了改进方向。     

基于ARMA的无线传感器网络流量预测模型的研究

无线传感器网络(WSN)的流量预测研究对于WSN管理具有至关重要的意义。基于WSN的特点,结合自回归滑动平均(ARMA)模型,该文提出了一个面向WSN的流量预测算法。仿真结果表明,该算法具有较高的预测精度;利用本算法对WSN的多路径路由机制进行改进后,可进一步提高WSN的生存期。     

基于无连接多路径路由的负载均衡

介绍了一种可以应用于Internet网络的无连接多路径路由计算方法,称为概率无连接多路径路由(probability-Disjoint Multi-paths Routing,p-DMR)。该方法使用概率构造无连接多路径,降低了在复杂网络环境中计算无连接多路径的复杂度,并将多路径路由与自适应按比例动态流量分割算法相结合,使网络性能得到优化,拥塞得到避免。