A study of factors influencing the severity of road crashes involving drunk drivers and non drunk drivers

In this study, an attempt has been made to develop Multinomial Logit (MNL) model by analysing the drunken and non drunken drivers involved in road crashes on Indian highways. Multinomial Logit model has been deployed to assess the influence of various parameters like vehicular, environment and geometric factors on the set of drivers who were found to be drunk at the time of getting involved in the road crash and those who were not under the influence of alcohol at the time of meeting with the road crash. The total economic cost of road crashes in the case of non-drunk driver road crash is Rs. 1046.27 million whereas in the case of drunk driver road crashes it is estimated to be Rs. 204.50 million. Further, it can be observed that economic cost of drunk driver road crashes is varying from 13 to 19 % across different types of road crashes.     

A Multi-Spoke, Three Plane Tyre Model for Simulation of Transient Behaviour

Based on the multi-spoke, single-plane, steady-state tyre model, a transient multi-spoke, three-plane tyre model is presented. This model involves updating the states of all the spokes under consideration to t+dt from the corresponding states at t. Also, a spoke base, which has lateral and longitudinal flexibilities relative to wheel hub, is included. By adding two extra planes of spokes to the original one, the effect of tyre width is built into the model. The three planes are equally spaced across the width of the tyre. The interaction with the ground of the spokes on these three planes is used to represent that of tyre elements at different locations across the width. Analytical results show good qualitative agreement with published experimental data. This model can be used to illustrate transient tyre behaviour and in simulations in which a generic tyre will suffice.     

Advanced Control Methods for Automotive Applications

This paper reviews key developments in applications of advanced control methods to automotive systems. Such applications appear in many aspects of vehicle controls. We will examine representative application areas, which include engines, suspension systems, traction systems, steering systems and those for automated highway systems (AHS). Each area is examined from the viewpoint of modeling and control algorithm development. Useful control theories for automotive application are briefly reviewed for better understanding of the applicability of these theories.     

Damper Models for Heavy Vehicle Ride Dynamics

A laboratory rig for testing hydraulic dampers using the 'hardware-in-the-loop' method is described, and the accuracy of the test method is investigated. A mathematical model of a hydraulic shock absorber is then developed. The model is suitable for vehicle simulations and has seven parameters which can be determined by simple dynamic measurements on a test damper. The shock absorber model is validated under realistic operating conditions using the test rig, and the relative importance of various features of the model on the accuracy of vehicle simulations is investigated.     

Determining the Characteristics of Helical Springs for Application in Suspensions of Railway Vehicles

This study concerns the theoretical calculation of the characteristics of helical springs used, particularly, for the primary and secondary suspensions of railway vehicles: the static characteristics will be determined by an exact method where as the dynamic characteristics will be determined with the help of an approximate method whose precision is, however, sufficient to make a valid evaluation of the dynamic behavior of the vehicles themselves.

The first part of the study is presented here, while a second part will appear in the next issue of “Vehicle System Dynamics”.     

An Optimal Self-Tuning Controller for an Active Suspension

An optimal self-tuning control algorithm is presented for vehicle suspension design. The controller, incorporating a weighting controller, state observer and parameter estimator, is designed according to linear optimal control (LQG) theory. Based on the updated estimates of vehicle parameters and states, and the adapted weighting parameters, the LQG controller provides the optimal set of gains over different operating conditions. The feasibility and effectiveness of the proposed self-tuning system was investigated and proved by simulation studies.     

Special issue: Importance of public transport

The transport demand in most major cities around the world can only be met with a high‐quality public transport system. The requirements on bus, rail, underground and tram systems are manifold with reliability and efficiency as the key factors. The service operating hours and the size of the network are often extended in order to serve the needs better. Further, most metropolitan areas are trying to provide more incentives for citizens to leave the car at home and use the local transit systems instead. The reasons are well known. Not only does a public transport system only make economical sense if it is well used, but most urban areas with a high car‐dependency face at least three major problems; safety, congestion, and pollution (noise and air pollution, land separation, etc.). It is generally recognised that to decrease car usage and to increase public transport usage a stick & carrot approach is needed. The London congestion‐charging scheme is an example since all revenues collected by the scheme are put into the improvement of bus and underground services.     

Hubris or humility? Accuracy issues for the next 50 years of travel demand modeling

This study reviews the 50-year history of travel demand forecasting models, concentrating on their accuracy and relevance for public decision-making. Only a few studies of model accuracy have been performed, but they find that the likely inaccuracy in the 20-year forecast of major road projects is ±30 % at minimum, with some estimates as high as ±40–50 % over even shorter time horizons. There is a significant tendency to over-estimate traffic and underestimate costs, particularly for toll roads. Forecasts of transit costs and ridership are even more uncertain and also significantly optimistic. The greatest knowledge gap in US travel demand modeling is the unknown accuracy of US urban road traffic forecasts. Modeling weaknesses leading to these problems (non-behavioral content, inaccuracy of inputs and key assumptions, policy insensitivity, and excessive complexity) are identified. In addition, the institutional and political environments that encourage optimism bias and low risk assessment in forecasts are also reviewed. Major institutional factors, particularly low local funding matches and competitive grants, confound scenario modeling efforts and dampen the hope that technical modeling improvements alone can improve forecasting accuracy. The fundamental problems are not technical but institutional: high non-local funding shares for large projects warp local perceptions of project benefit versus costs, leading to both input errors and political pressure to fund projects. To deal with these issues, the paper outlines two different approaches. The first, termed ‘hubris’, proposes a multi-decade effort to substantially improve model forecasting accuracy over time by monitoring performance and improving data, methods and understanding of travel, but also by deliberately modifying the institutional arrangements that lead to optimism bias. The second, termed ‘humility’, proposes to openly quantify and recognize the inherent uncertainty in travel demand forecasts and deliberately reduce their influence on project decision-making. However to be successful either approach would require monitoring and reporting accuracy, standards for modeling and forecasting, greater model transparency, educational initiatives, coordinated research, strengthened ethics and reduction of non-local funding ratios so that localities have more at stake.     

The Alternative Motor Fuels Act, alternative-fuel vehicles, and greenhouse gas emissions

The corporate average fuel economy (CAFE) standard is the major policy tool to improve the fleet average miles per gallon of automobile manufacturers in the US. The Alternative Motor Fuels Act (AMFA) provides special treatment in calculating the fuel economy of alternative-fuel vehicles to give manufacturers CAFE incentives to produce more alternative-fuel vehicles. AMFA has as its goals an increase in the production of alternative-fuel vehicles and a decrease in gasoline consumption and greenhouse gas emissions. This paper examines theoretically the effects of the program set up under AMFA. It finds that, under some conditions, this program may actually increase the production of fuel-inefficient gasoline vehicles, gasoline consumption and greenhouse gas emissions.     

地下铁道车站设计乘降客流量的确定法

本文根据运营地铁积累的客流调查以及规划地铁可行性研究报告中,理论预测提供 的资料,经统计分析,应用预测理论和方法,提出供实际应用的设计乘降最的方法,此 法可简化客流规划工作量,省时,省费用.