试析道路交通肇事逃逸案件发生原因及对策

论述了交通肇事逃逸发生的时间、地点、条件和司机的心理因素 ,提出了预防和减少交通肇事逃逸的具体措施。     

IP ADDRESS AUTOCONFIGURATION FOR WIRELESS AD HOC NETWORKS

IntroductionWireless ad hoc networks are gaining increas-ing popularity in recent years because of their easeof deployment. No wired base station or infras-tructure is supported,and each hostcommunicatesone anothervia packetradios. In ad hoc networks,routing protocols are challenged with establishingand maintaining multihop routes in the face of mo-bility,bandwidth limitation and power con-straints. In ad hoc networks,each node( host)acts as a router since routes are mostly multihop.Nodes in …     

船舶调度闸外编排算法

为了提高船闸的通过能力,优化船舶进闸调度,分析了三峡船闸船舶的平均过闸间隔时间,提出了闸外编排的概念,分析了船舶在进闸调度中的操作流程,以安全性和进闸耗时为目标,建立了闸外编排的数学模型,设计了相应的启发式求解算法,将模型的目标和约束条件通过启发式方法生成船舶在闸外的排序法则。数值试验分析结果表明闸外编排数学模型切实可行,排序算法可以生成安全高效的进闸方案,闸外编排的实现考虑了船舶进闸时间和安全性原则,缩短了闸次间隔时间,提高了日开闸次数,有效地提高了通航设施的整体通过能力。     

低交通量道路路线技术标准的研究

基于低交通量道路概念,通过对低交通量道路路线技术指标的分析研究,制定符合农村实际情况的路线标准,对农村公路建设具有指导意义,值得同行借鉴.     

A methodology for identifying similar days in air traffic flow management initiative planning

This article describes a methodology for selecting days that are comparable in terms of the conditions faced during air traffic flow management initiative planning. This methodology includes the use of specific data sources, specific features of calendar days defined using these data sources, and the application of a specific form of classification and then cluster analysis. The application of this methodology will produce results that enable historical analysis of the use of initiatives and evaluation of the relative success of different courses of action. Several challenges are overcome here including the need to identify the appropriate machine learning algorithms to apply, to quantify the differences between calendar days, to select features describing days, to obtain appropriate raw data, and to evaluate results in a meaningful way. These challenges are overcome via a review of relevant literature, the identification and trial of several useful models and data sets, and careful application of methods. For example, the cluster analysis that ultimately selects sets of similar days uses a distance metric based on variable importance measures from a separate classification model of observed initiatives. The methodology defined here is applied to the New York area, although it could be applied by other researchers to other areas.     

Modification of the Highway Capacity Manual two‐lane highway analysis procedure for Spanish conditions

The US Highway Capacity Manual (HCM) methodology is used in Spain to evaluate traffic operation and quality of service. The effect of passing manoeuvre on two‐lane highway operational performance is considered through adjustment factors to average travel speeds and percent time spent following. The procedure is largely based on simulations in TWOPAS and passing behaviours observed during US calibrations in the 1970s. It is not clear whether US driving behaviour and vehicles' performance are comparable with Spanish conditions. The objective of this research is to adapt the HCM 2010 methodology to Spanish driver behaviour, for base conditions (i.e. no passing restrictions). To do so, TWOPAS was calibrated and validated based on current Spanish passing field data. The calibration used a genetic algorithm. The case study included an ideal two‐lane highway with varying directional traffic flow rate, directional split and percentage of trucks. The updated methodology for base conditions is simpler than the current HCM 2010 and does not rely on interpolation from tables. Copyright © 2016 John Wiley & Sons, Ltd.     

The speed control effect of highway tunnel sidewall markings based on color and temporal frequency

The low‐luminance monotonous environment in the middle section of highway tunnels offers few reference points and is prone to cause severe visual illusion. Thus, drivers tend to underestimate their driving speed, which can induce speeding behaviors that result in rear‐end collisions. Therefore, discovering low‐cost methods of traffic engineering that reduce this visual illusion and ensure a steady driving speed is an important challenge for current highway tunnel operations. This study analyzes the effects of sidewall markings in typical highway tunnels, specifically observing how their colors and temporal frequencies affect the driver's speed perception in a low‐luminance condition. A three‐dimensional model of the middle section of highway tunnels was built in a driving simulator. Psychophysical tests of speed perception were carried out by the method of limits. The precision of the simulation model was then checked by comparing the results to field test data. The simulation tests studied the stimulus of subjectively equal speed and reaction time in relation to sidewall markings in different colors (red–white combined, yellow–white combined, and blue–white combined). Furthermore, based on the optimal color, the effects of sidewall marking with different temporal frequencies (0.4, 0.8, 1.2, 2, 4, 8, 12, 16, and 32 Hz) on the speed perception of drivers were also analyzed. The test results reveal that the color and temporal frequency of sidewall marking have a significant impact on the driver's stimulus of subjectively equal speed and reaction time. The subjects have the highest speed overestimation and an easy speed judgment with the red–white combined sidewall marking. Within the temporal frequency range of 4.45–7.01 Hz, the subjects have a certain degree of speed overestimation (less than 20%), and the speed perception is sensitive to the temporal frequency changes. Copyright © 2016 John Wiley & Sons, Ltd.     

Modeling traffic operation at signalized intersections without explicit left‐turn yielding rules with an enhanced cell transmission model

This paper presents an enhanced cell transmission model (CTM) to capture traffic operation at signalized intersections without explicit permissive left‐turn yielding rules (i.e. aggressive permissive left‐turn maneuvers may not necessarily yield to opposing through traffic), which can be widely observed in many developing countries. Different from previous studies that focus on traffic dynamics on approaching links, this study contributes to modeling traffic operations within the intersection. A novel cell transmission framework with various types of virtual cells is proposed to model the dynamics of traffic movements from approach to exit. The unique phenomenon of competitive occupying of the conflict point between the left turn and opposing through movements is modeled. The cell state indicating its blockage is proposed to capture the dynamic queue formulation and dissipation and to evaluate the operational traffic performance at the intersection. Field validation results show that the proposed model can capture the operation of traffic at signalized intersections without explicit permissive left‐turn yielding rules with significantly higher level of accuracy than traditional traffic flow models. Copyright © 2016 John Wiley & Sons, Ltd.     

A study of carpooling behaviour using a stated preference web survey in selected cities of India

This paper analyses how people perceive the idea of carpooling and evaluate preferences while making a decision to join a carpool. Analysing data from a web-based stated preference survey in India reveals that cognitive attitudes play a significant role in evaluating the perceived advantages and disadvantages of carpooling whereas intentions to carpool are associated with perceived negative evaluations. A factor analysis identifies two latent attitudinal factors: a ‘time–convenience’ factor that discourages carpooling and a ‘private–public cost’ factor that encourages carpooling. The study analyses the influential attributes – extra travel time, walking time to reach meeting point, waiting time at pickup point and cost savings – as explanatory variables for the utility of carpooling. Cost savings prove to be the most significant attribute when combined with other attributes, followed by extra travel time. The study provides the implications to policy-makers of designing promotional tools to improve the propensity of carpooling among single occupant vehicle drivers.     

Short‐term traffic flow prediction with linear conditional Gaussian Bayesian network

Traffic flow prediction is an essential part of intelligent transportation systems (ITS). Most of the previous traffic flow prediction work treated traffic flow as a time series process only, ignoring the spatial relationship from the upstream flows or the correlation with other traffic attributes like speed and density. In this paper, we utilize a linear conditional Gaussian (LCG) Bayesian network (BN) model to consider both spatial and temporal dimensions of traffic as well as speed information for short‐term traffic flow prediction. The LCG BN allows both continuous and discrete variables, which enables the consideration of categorical variables in traffic flow prediction. A microscopic traffic simulation dataset is used to test the performance of the proposed model compared to other popular approaches under different predicting time intervals. In addition, the authors investigate the importance of spatial data and speed data in flow prediction by comparing models with different levels of information. The results indicate that the prediction accuracy will increase significantly when both spatial data and speed data are included. Copyright © 2016 John Wiley & Sons, Ltd.