Urban single-lane roundabouts: A new analytical approach using multi-criteria and simultaneous multi-objective optimization of geometry design,efficiency and safety

Building safe and effective roundabouts requires optimizing traffic (operational) efficiency (TE) and traffic safety (TS) while taking into account geometric factors, traffic characteristics and local constraints. Most existing simulation-based optimization models do not simultaneously optimize all these factors. To capture the relationship among geometry, efficiency and safety, we put forward a model formulation in this paper. We present a new multi-criteria and simultaneous multi-objective optimization (MOO) model approach to optimize geometry, TE and TS of urban unsignalized single-lane roundabouts. To the best of our knowledge, this is the first model that uses the multi-criteria decision-making method known as analytic hierarchy process to evaluate and rank traffic parameters and geometric elements of urban single-lane roundabouts. The model was built based on comprehensive review of the research literature and existing roundabout simulation software, a field survey of 61 civil and traffic expert engineers in Croatia, and field studies of roundabouts in the Croatian capital city of Zagreb. We started from the basis of Kimber’s capacity model, HCM2010 serviceability model, and Maycock and Hall's accident prediction model, which we extended by adding sensitivity analysis and powerful MOO procedures of the bounded objective function method and interactive optimization. Preliminary validation of the model was achieved by identifying the optimal and most robust of three geometric alternatives (V.1-V.3) for an unsignalized single-lane roundabout in Zagreb, Croatia. The geometric parameters in variant V.1 had significantly higher values than in the existing design V.0, while approaches 1 and 3 in variant V.2 were enlarged as much as possible within allowed spatial limits and Croatian guidelines, reflecting their higher traffic demand. Sensitivity analysis indicated that variant V.2 showed the overall highest TE and TS across the entire range of traffic flow demand and pedestrian crossing flow demand at approaches. At the same time, the number of predicted traffic accidents was similar for all three variants, although it was lowest overall for V.2. The similarity in predicted accident frequency for the three variants suggests that V.2 provides the greatest safety within the predefined constraints and parameter ranges explored in our study. These preliminary results suggest that the proposed model can optimize geometry, TE and TS of urban single-lane roundabouts.     

Passenger oriented railway disruption management by adapting timetables and rolling stock schedules

In passenger railway operations, unforeseen events require railway operators to adjust their timetable and their resource schedules. The passengers will also adapt their routes to their destinations. When determining the new timetable and rolling stock schedule, the railway operator has to take passenger behavior into account. The operator should increase the capacity of trains for which the operator expects more demand than on a regular day. Furthermore, the operator could increase the frequency of the trains that serve stations with an additional demand.This paper describes a real-time disruption management approach which integrates the rescheduling of the rolling stock and the timetable by taking the changed passenger demand into account. The timetable decisions are limited to additional stops of trains at stations at which they normally would not call. Several variants of the approach are suggested, with the difference in how to determine which additional stops should be executed.Real-time rescheduling requires fast solutions. Therefore a heuristic approach is used. We demonstrate the performance of the several variants of our algorithm on realistic instances of Netherlands Railways, the major railway operator in the Netherlands.     

Commuter ride-sharing using topology-based vehicle trajectory clustering: Methodology,application and impact evaluation

This paper illustrates a ride matching method for commuting trips based on clustering trajectories, and a modeling and simulation framework with ride-sharing behaviors to illustrate its potential impact. It proposes data mining solutions to reduce traffic demand and encourage more environment-friendly behaviors. The main contribution is a new data-driven ride-matching method, which tracks personal preferences of road choices and travel patterns to identify potential ride-sharing routes for carpool commuters. Compared with prevalent carpooling algorithms, which allow users to enter departure and destination information for on-demand trips, the proposed method focuses more on regular commuting trips. The potential effectiveness of the approach is evaluated using a traffic simulation-assignment framework with ride-sharing participation using the routes suggested by our algorithm. Two types of ride-sharing participation scenarios, with and without carpooling information, are considered. A case study with the Chicago tested is conducted to demonstrate the proposed framework’s ability to support better decision-making for carpool commuters. The results indicate that with ride-matching recommendations using shared vehicle trajectory data, carpool programs for commuters contribute to a less congested traffic state and environment-friendly travel patterns.     

A planning tool for evaluating vehicles miles travelled and traffic safety forecasts of growth management scenarios: A case study of Baton Rouge and New Orleans

This study describes an adaptable planning tool that examines potential change in vehicle miles travelled (VMT) growth and corresponding traffic safety outcomes in two urbanized areas, Baton Rouge and New Orleans, based on built environment, economic and demographic variables. This model is employed to demonstrate one aspect of the potential benefits of growth management policy implementation aimed at curbing VMT growth, and to establish targets with which to measure the effectiveness of those policies through a forecasting approach. The primary objective of this research is to demonstrate the need to break with current trends in order to achieve future goals, and to identify specific policy targets for fuel prices, population density, and transit service within the two study regions. Models indicate based on medium growth scenarios, Baton Rouge will experience a 9 percent increase in VMTs and New Orleans will experience 10 percent growth. This translates to corresponding increases in crashes, injuries and fatalities. The paper provides forecasts for planners and engineers to consider an alternative future, based on desired goals to reduce VMTs and therefore improve safety outcomes. A constrained-forecast model shows a cap on VMTs and crash rates is achievable through policy that increases fuel prices, population density and annual transit passenger miles per capita at reasonable levels through a growth management approach.     

Climate change behaviors related to purchase and use of personal cars: Development and validation of eco-socially conscious consumer behavior scale

A constantly changing environment and global warming are issues that are recognized at all global forums. One of the major reasons for global warming is the emission of greenhouse gasses which is primarily caused by use of personal cars as means of transport. This study reports on the development of an eco-socially conscious consumer behavior (ESCCB) scale specific to purchase and use of personal cars, based on samples of actual automobile customers in Pakistan. Using mixed method approaches, the results of 3 studies yield a 9-item three-dimensional scale (eco-social conservation, eco-social use, and eco-social purchase) with satisfactory reliability, construct validity and nomological validity. Second-order factor analysis revealed that eco-social purchase was the most important dimension, followed by eco-conservation and eco-social use. A test of nomological behavior shows that the scale is positively associated with a related construct: environmental concern. This study advances the literature on pro-environmental behaviors by introducing a conceptual definition of ESCCB related to personal car purchase and use, developing a measure for the ESCCB concept and validating the scale in the context of an emerging economy, Pakistan. The scale provides important insights for marketers in the automobile industry for remodelling marketing plans, as well as for environmentalists focusing on strategies to bring change in consumer behavior.     

实现改进和加强财会规范化管理的途径探析

分析了财会运营过程中的常见问题,针对这些问题,提出加强财会规范化管理的途径。     

关于木材运输船安全运输的几点分析

木材船海上运输具有一定的风险,一旦积载和绑扎不当或管理不妥,造成货物滚动、移位、货垛倒塌,就会引发安全事故甚至导致船舶倾覆。因此,加强木材船的安全管理,落实各项安全保障措施,是确保木材船安全运输生产的重要举措。     

浅谈合同管理在公路工程建设管理中的作用

合同管理贯穿于公路工程建设的整个过程,阐述了合同管理在招投标、施工等工程建设管理、造价控制中的作用。     

Dynamic demand estimation and prediction for traffic urban networks adopting new data sources

Nowadays, new mobility information can be derived from advanced traffic surveillance systems that collect updated traffic measurements, both in fixed locations and over specific corridors or paths. Such recent technological developments point to challenging and promising opportunities that academics and practitioners have only partially explored so far.The paper looks at some of these opportunities within the Dynamic Demand Estimation problem (DDEP). At first, data heterogeneity, accounting for different sets of data providing a wide spatial coverage, has been investigated for the benefit of off-line demand estimation. In an attempt to mimic the current urban networks monitoring, examples of complex real case applications are being reported where route travel times and route choice probabilities from probe vehicles are exploited together with common link traffic measurements.Subsequently, on-line detection of non-recurrent conditions is being recorded, adopting a sequential approach based on an extension of the Kalman Filter theory called Local Ensemble Transformed Kalman Filter (LETKF).Both the off-line and the on-line investigations adopt a simulation approach capable of capturing the highly nonlinear dependence between the travel demand and the traffic measurements through the use of dynamic traffic assignment models. Consequently, the possibility of using collected traffic information is enhanced, thus overcoming most of the limitations of current DDEP approaches found in the literature.     

Formal scientific research of traffic collision data utilizing GIS

This paper explores the tenuous link between speeding behavior and accident causation, one that has not been well established in the international literature to date. Taking advantage of established engineering conventions and formulae, we were able to set up an a priori hypothesis suitable for testing. Utilizing this formal scientific method (which GIS researchers have been criticised for not using) we establish a statistical link for this relationship. Our methodology can be used to support all police intervention strategies, including the controversial photo radar systems. The results from our research have been entered into a GIS in order to create a map for spatial display. This map illustrates the relative probability or risk of collision occurrence resulting from speeding at all intersections and interchanges within the scope of the study. It is suggested that this methodology could easily be maintained with periodic updates of data, thus creating a dynamic model from which to monitor traffic safety within the city. Furthermore, this model can be utilized to study specific strategies, allowing for the scrutiny of before, during and after effects. The study area is the entire city of Calgary, Alberta, Canada, and includes all traffic collisions occurring during the year of 1994.