The effect of the car-parazzi system on traffic accidents in Korea

In 2001 and 2002, the Korean government rewarded around $3 to civilians who photograph and report violations of traffic rules. This so-called ‘car-parazzi system’ was such a success with well over 4 million cases reported until its abolition. Our empirical results found that the car-parazzi system was much effective in significantly reducing the death tolls by traffic accidents.     

A hybrid clustering and classification approach for predicting crash injury severity on rural roads

As a threat for transportation system, traffic crashes have a wide range of social consequences for governments. Traffic crashes are increasing in developing countries and Iran as a developing country is not immune from this risk. There are several researches in the literature to predict traffic crash severity based on artificial neural networks (ANNs), support vector machines and decision trees. This paper attempts to investigate the crash injury severity of rural roads by using a hybrid clustering and classification approach to compare the performance of classification algorithms before and after applying the clustering. In this paper, a novel rule-based genetic algorithm (GA) is proposed to predict crash injury severity, which is evaluated by performance criteria in comparison with classification algorithms like ANN. The results obtained from analysis of 13,673 crashes (5600 property damage, 778 fatal crashes, 4690 slight injuries and 2605 severe injuries) on rural roads in Tehran Province of Iran during 2011–2013 revealed that the proposed GA method outperforms other classification algorithms based on classification metrics like precision (86%), recall (88%) and accuracy (87%). Moreover, the proposed GA method has the highest level of interpretation, is easy to understand and provides feedback to analysts.     

Modelling driver propensity for traffic accidents: a comparison of multiple regression analysis and fuzzy approach

Abstract

This research proposes an assessment and decision support model to use when a driver should be examined about their propensity for traffic accidents, based on an estimation of the driver’s psychological traits. The proposed model was tested on a sample of 305 drivers. Each participant completed four psychological tests: the Barratt Impulsiveness Scale (BIS-11), the Aggressive Driving Behaviour Questionnaire (ADBQ), the Manchester Driver Attitude Questionnaire (DAQ) and the Questionnaire for Self-assessment of Driving Ability. In addition, participants completed an extensive demographic and driving survey. Various fuzzy inference systems were tested and each was defined using the well-known Wang-Mendel method for rule-base definition based on empirical data. For this purpose, a programming code was designed and utilized. Based on the obtained results, it was determined which combination of the considered psychological tests provides the best prediction of a driver’s propensity for traffic accidents. The best of the considered fuzzy inference systems might be used as a decision support tool in various situations, such as in recruitment procedures for professional drivers. The validity of the proposed fuzzy approach was confirmed as its implementation provided better results than from statistics, in this case multiple regression analysis.     

The difference between hub and non-hub airports – An airside capacity perspective

Airport airside capacity is limited by the runway system capacity or apron capacity, whichever is more constraining. Sometimes, taxiway system can also impose constraint to airside capacity, but in the case of fully developed taxiway systems (involving parallel taxiway, high speed exits, etc.) that is usually not an issue. To determine which airside element is more constraining it is not always as simple as comparing runway system and apron capacities directly one to another. It is important to understand and take into consideration their relationship. Runway-apron relationship depends on demand characteristics e.g. dominant market segments (e.g. scheduled, charter, low-cost, general aviation, cargo), and/or specific traffic patterns (hubbing or point-to-point services, seasonality in demand, etc.).The paper brings up the issue of available airside capacity under different traffic characteristics, faced by hubs vs. non-hub airports, and the necessity to understand runway-apron interdependency in order to properly identify the bottleneck on the airside. Referring to earlier findings related to apron capacity analysis, the paper summarizes various factors that affect apron capacity at non-hub and hub airports and uses them to define the runway-apron relationship, as well as its role in the process of analyzing airside capacity under various demand characteristics.The main finding is that functional relationship between the runway system and aprons is much stronger in the case of hub airports, and should be carefully considered when analyzing airside capacity. Besides runway capacity, few other variables that affect apron capacity at hub airports are discussed. Generic examples are used to support the discussion.     

Buffering in evacuation management for optimal traffic demand distribution

This paper presents a new framework for managing congestion during emergency evacuations. The algorithm allows a long link of the network to be used as a buffer to keep the traffic flow moving in. Concurrently, a detour trigger time is estimated to keep the traffic under-saturated in the buffer zone and minimize the total travel time. The integration algorithm presented in this paper is an efficient mathematical solution for travel time cost calculation. A case study is presented to demonstrate the efficacy of the traffic demand buffering strategy developed in this research for managing the evacuation flow.     

基于分形理论的铁路客货运量预测

在阐述分形基本理论和分析铁路运输时间序列分形特性的基础上,基于变维分形理论对铁路客货运量进行预测。根据铁路运量分形预测原理及步骤,以全国铁路运量预测为例进行分析,计算得到铁路2012年、2015年、2020年的客货运量,以及2010—2020年的客货运量增长率,并对预测结果进行了具体分析。     

“大敦煌”“大交通”背景下的现代艺术设计教学研究

兰州交通大学研究丝路文化、敦煌文化、研究交通的条件得天独厚，在这样的条件和背景下思考，研究建立一个的“大敦煌”、“大交通”现代艺术设计教学体系，有着重要的现实意义。     

Pattern of road traffic injuries: one year hospital-based study in Western Nepal

Road traffic injuries and deaths caused by motor vehicles is a growing public health problem all over the world. Inter-country or regional differences in the pattern of injury by road users have significant implications in determining prevention policies. The present study was conducted to evaluate the pattern of injuries in 217 hospitalized trauma patients admitted during 1 year, 2003. The majority of the injuries (54%) involved motorcycles. The highest incidence amongst the male population was in the age group of 16 – 30 years. Head and face injuries and injuries to the lower limbs comprised 58.1% and 50.7% of all injuries respectively. The bones of the lower limbs were most commonly fractured. To conclude, the traffic casualties of motorcyclists and pedestrians are considered a major problem and the preventive measures to reduce these transport-related injuries are discussed in this study.     

Downtown curbside parking capacity

Current debates on downtown parking policy have been concentrating on downtown parking pricing, while overlooking downtown parking capacity. This paper focuses on how much curbside to allocate to parking when the private sector provides garage parking. In the first-best optimum, no cruising for parking occurs, and only curbside parking is provided when demand is low relative to street capacity, both curbside parking and garage parking are provided when demand in intermediate, and only garage parking is provided when demand is high. In the second-best optimum where curbside parking is underpriced, cruising for parking occurs only when both curbside and garage parking are both present. As the fee differential between garage and curbside parking increases, cruising for parking becomes more severe, and the range of demand levels over which curbside and garage parking are both present shrinks and eventually disappears.     

Do firms flee traffic congestion?

Much transport policy aims to use congestion relief measures to support economic activity, but planners know relatively little about how individual firms respond to traffic congestion. This study helps fill this gap by exploring individual firm location responses to traffic congestion within the Philadelphia metropolitan area between 2003 and 2007. This study tests whether existing, basic-industry firms flee congested areas to minimize exposure to the congestion externality. Relocation responses are estimated and compared for five separate industries (finance and insurance, health care, manufacturing, real estate and leasing, and wholesale trade) using firm-level data collected by InfoUSA and obtained from ESRI. Results suggest that congestion influences firm location decisions, but that the scale of congestion is important. While firms appear to relocate out of areas with high regionally-scaled congestion, areas with high local congestion are associated with a lower likelihood of relocating. In sum, while regional congestion appears to be a drag, local congestion appears to function as an amenity – implying that there is truth in the competing notions among engineers and economists of congestion as a diseconomy and among urban designers of congestion as an amenity.