Modeling road traffic fatalities in India: Smeed's law,time invariance and regional specificity

Mathematical formulations linking road traffic fatalities to vehicle ownership, regional population, and economic growth continue to be developed against the backdrop of Smeed and Andreassen models. Though a few attempts were made, Smeed's law has not been fully tested in India. Using the 1991–2009 panel data from all states, this work (a) developed the generalized Smeed and Andreassen models; (b) evaluated if traffic fatalities were impacted by structural changes; and (c) examined if – in relation to the generalized model – the individual (time and regional) models are more relevant for application. Seven models (Smeed: original, generalized, time-variant, state-variant; and Andreassen: generalized, time-variant, state-variant) were developed and tested for fit with the actual data. Results showed that the per vehicle fatality rate closely resembled Smeed's formulation. Chow-test yielded a significant F-stat, suggesting that the models for four pre-defined time-blocks are structurally different from the 19-year generalized model. The counterclockwise rotation of the log-linear form also suggested lower fatality rates. While the new government policies, reduced vehicle operating speeds, better healthcare, and improved vehicle technology could be the factors, further research is required to understand the reasons for fatality rate reductions. The intercept and gradients of the time-series models showed high stability and varied only slightly in comparison to the 19-year generalized models, thus suggesting that the latter are pragmatic for application. Regional formulations, however, indicate that they may be more relevant for studying trends and tendencies. This research illustrates the robustness of Smeed's law, and provides evidence for time-invariance but state-specificity.     

Users of a regional telephone-based traveler information system – a study of TravInfo™ users in the San Francisco Bay Area

This paper reports the results of a 1998 survey carried out among a small sample of people who had called the TravInfo Travel Advisory Telephone System (TATS) in April 1997 looking for current information about traffic conditions in the San Francisco Bay Area. The survey employed a series of tradeoff questions designed to identify the specific attributes of the information that the respondents felt to be most important, and to estimate the relative values that these users had for various possible information improvements. Despite the small size of the sample, it proved feasible to investigate how the implicit valuations placed on each attribute of the service (update frequency, extent of road coverage, and level of customization) varied among different user segments. For the most part, respondents appeared to value basic enhancements – those that establish an initial quality differential above the baseline set by free broadcast traffic information – more than they value further subsequent improvements. Overall, more frequent information updates are the highest priority among the range of possible enhancements explored in the survey, followed by an extension of coverage to include major arterials in addition to freeways. However, the evidence suggests relatively little value in door-to-door coverage – that is, coverage of streets beyond the freeway and major arterial networks. This research produced some estimates of the average monetary values ("willingness to pay") that the sample of current users attached to information improvements of various kinds. While these values varied among subgroups in ways that fit a priori expectations, it is not clear whether they provide an unbiased picture of the users' absolute levels of willingness to pay, such that they could be used reliably to inform (for example) information pricing decisions. The value of this research lies more clearly in the light it sheds on the relative structure of user preferences, and on the variations in preferences between information attributes and market segments. Overall, the authors conclude that the prospects for self-sustaining ATIS services are unclear. In response to a direct question, a majority of users (perhaps influenced by a strategic bias) indicated that they were unwilling to pay for ATIS services; some of these same people, however, indicated later that they might indeed be willing to buy a particular enhanced ATIS package, in direct competition with free broadcast services.     

Short‐term prediction of traffic parameters—performance comparison of a data‐driven and less‐data‐required approaches

The travel decisions made by road users are more affected by the traffic conditions when they travel than the current conditions. Thus, accurate prediction of traffic parameters for giving reliable information about the future state of traffic conditions is very important. Mainly, this is an essential component of many advanced traveller information systems coming under the intelligent transportation systems umbrella. In India, the automated traffic data collection is in the beginning stage, with many of the cities still struggling with database generation and processing, and hence, a less‐data‐demanding approach will be attractive for such applications, if it is not going to reduce the prediction accuracy to a great extent. The present study explores this area and tries to answer this question using automated data collected from field. A data‐driven technique, namely, artificial neural networks (ANN), which is shown to be a good tool for prediction problems, is taken as an example for data‐driven approach. Grey model, GM(1,1), which is also reported as a good prediction tool, is selected as the less‐data‐demanding approach. Volume, classified volume, average speed and classified speed at a particular location were selected for the prediction. The results showed comparable performance by both the methods. However, ANN required around seven times data compared with GM for comparable performance. Thus, considering the comparatively lesser input requirement of GM, it can be considered over ANN in situations where the historic database is limited. Copyright © 2016 John Wiley & Sons, Ltd.     

A cognitive framework to plan for the future of transportation

ABSTRACT

Automated, connected, electrified, and shared mobility will be cornerstones of the transportation future. Research to quantify the potential benefits and drawbacks of practice, and to identify barriers to adoption, is the first step in any strategic plan for their adoption. However, uncertainties, complexity, interdependence, and the multidisciplinary nature of emerging transportation technologies make it difficult to organize and identify focused research. The contribution of this work is a cognitive framework to help planners and policymakers organize broad topics, reveal challenges, discover ideas for solutions, quantify potential impacts, and identify implications to guide preparation strategies. The authors provide example cognitive frameworks for connected, automated, and electrified vehicles.     

中央政府在城市交通可持续发展中的角色

中国城市交通问题已经不仅仅是拥堵、噪音、尾气等地方层面的问题,它涉及宏观经济发展、农田保护、金融体系稳定、能源安全、碳排放等国家甚至国际层面的问题。由于这些溢出问题的存在,中央政府应重新审视其在城市交通方面的作用与职责。对此,世界银行提出,中央政府可从城市交通政策导向、公交发展支持、最佳实践奖励、交通绩效标杆与评估系统、交通投融资体制改革以及城市交通示范项目等方面发挥作用。大力发展高效的公共交通是中国可持续城市交通战略的核心工作,要在有效的商业运营前提下满足社会目标、保证服务质量。保持民营部门与公共部门之间的合作互补关系是中央和地方政府所应共同做出的努力。     

Closed form models to assess railroad technology investments

ABSTRACT

Class I railroads in North America collectively invested USUS$11.2 billion to comply with a U.S. federal mandate to deploy positive train control as a form of train protection system. This amount dwarfs the potential savings from accidents the technology could prevent. Therefore, railroads must seek additional benefits. This research contributes simple closed-form models to inform strategies that can leverage the technology deployment by estimating the annual additional net benefits, internal rate of return, and benefit-cost ratio needed for a desired payback period.     

Road traffic crashes and risk groups in India: Analysis,interpretations, and prevention strategies

Current literature does not adequately discuss India's quickly changing transportation scenario, especially road traffic crash (RTC) concerns. The objectives of this work were to (a) present the national RTC framework and a case study of Andhra Pradesh (AP); (b) analyze and identify risk types; (c) discuss trends and data deficiencies; and (d) recommend prevention strategies. During the period 1970–2009, the nation's road length increased at a compounded annual growth rate (CAGR) of 3.2%, whereas the number of registered vehicles, RTCs, and fatalities grew at 12%, 3.8%, and 5.7% CAGR respectively. Exposure risk dropped from 103 to 11 fatalities per 10 000 vehicles but increased from 2.7 to 10.8 fatalities per 100 000 people.     

Modeling wrong-way crashes and fatalities on arterials and freeways

Wrong way driving (WWD) research and mitigation measures have primarily focused on limited access facilities. This is most likely due to the higher incidence of fatal WWD crashes with dramatic consequences on freeways, media attention, and a call for innovative solutions to address the problem. While public agencies and published literature address WWD incidence on freeway systems, the crash analyses on non-limited access facilities, i.e., arterial corridors, remains untouched. This research extends previous works and attempts to provide many new perspectives on arterial WWD incidence. In particular, one work showed that while WWD fatalities are more likely to occur on freeways, the likelihood of these crashes is higher on arterials. Hence this work with univariate and multivariate analyses of WWD and non-WWD crashes, and fatal and non-fatal WWD incidents. Results show the impressive negative impacts of alcohol use, driver defect, nighttime and weekend incidence, poor street lighting, low traffic volumes, rural geography, and median and shoulder widths. The objective here is to highlight the need for paying greater attention to WWD crashes on arterial corridors as is done with fatal WWD incidents on freeway systems. It suffices to say that while engineering countermeasures should evolve from the traditional signing and pavement markings to connected vehicle technology applications, there is a clear and compelling need to focus on educational campaigns specifically targeting drunken driving, and enforcement initiatives with an objective to mitigate WWD in the most efficient manner possible.     

Campus parking supply impacts on transportation mode choice

Parking demand is a significant land-use problem in campus planning. The parking policies of universities and large corporations with facilities located in small urban areas shape the character of their campuses. These facilities will benefit from a simplified methodology to study the effects of parking availability on transportation mode mix and impacts on recruitment and staffing policies. This paper, based on a case study of North Dakota State University in the United States, introduces an analytical framework to provide planners with insights about how parking supply and demand affects campus transportation mode choice. The methodology relies only on aggregate mode choice data for the special generator zone and the average aggregate volume/capacity ratio projections for all external routes that access the zone. This reduced data requirement significantly lowers analysis cost and obviates the need for specialized modelling software and spatial network analysis tools. Results illustrate that the framework is effective for analysing mode choice changes under different scenarios of parking supply and population growth.