National road mortality reduction targets under European Union road safety policy: 2011–2020

The European Union (EU) has proposed renewing the target for halving the number of road fatalities in the period 2011–2020. In this paper, a nonlinear distribution method for dynamic fatality reduction targets is applied for the purpose of finding individual national mortality reduction targets for each of the 27 member countries in the EU. Weighting is undertaken for four scenarios based on the following indicators: road mortality rates, fatality rates, fatality risks, and fatality density. Results are presented for four proposals to reduce the number of fatalities in each Member State, based on the original situation of the indicators considered in the study. The results seek to provide policy-makers with a broader vision with regard to the achievement of the goals of EU road safety policy.     

基于理念更新的城市公共交通优先发展制度框架

破除发展理念误区与分歧、提升理念认识深度是加快推进中国城市公共交通优先(以下简称"公交优先")发展制度建设的首要任务。首先从公民权利和城市发展两方面总结了国际城市公交优先理念的基本内涵,并结合基本国情归纳了对中国城市公交优先理念的基本认识。接着,分析了国际城市公交优先不同制度与措施的战略出发点与实施效果,将公交优先理念划分为需求引导、品质吸引与效率提升三个层次。然后针对现状中国制度建设推进面临的问题,从核心价值、制度安排、工具与技术、绩效评价四个层次对城市公交优先发展的制度框架进行设计,提出制度建设在不同层面与不同阶段的任务、重点以及相关措施、建议。     

Evolution of coastal hazards policies in the United States

The ocean and Great Lakes coasts of the United States are experiencing widespread economic and environmental damage from coastal flooding and erosion. During this century, public response to such coastal hazards has evolved haphazardly in response to particular disasters. Over time, however, the range of response has broadened as research has helped to refine public understanding of physical coastal processes, and specific disasters have been studied before longer term forms of institutional response have been formulated. Earlier reliance on engineered shoreline protection has been supplemented by beach nourishment, flood insurance, building and land use regulations, coastal zone planning, and other approaches. This article interprets the evolution of such public policy innovations in terms of a model that depicts the interaction of spatially differentiated systems of physical, legal, and cultural phenomena in the coastal context.     

A volatile relationship: The effect of changing gasoline prices on public support for mass transit

The determinants of public opinion toward public transit is a little-researched topic, though a better understanding of what makes consumers willing to support transit may reveal which attributes of transit consumers value most. One determinant of people’s willingness to support investments in mass transit may be the price of fuel for transit’s principal competition, the private automobile. In this paper, I examine the relationship between the cost of gasoline and stated willingness to invest public money in mass transit improvements. I hypothesize that fuel price volatility—in addition to price itself—is a determinant of support for more mass transit funding, controlling for other factors. As the price of gasoline becomes more uncertain, the public should, all else equal, support investment in mass transportation, a form of transportation that may provide some measure of protection from the price of fuel. Results suggest a strong effect of price volatility on consumers’ willingness to support transit expenditures.     

User perspectives in public transport timetable optimisation

The present paper deals with timetable optimisation from the perspective of minimising the waiting time experienced by passengers when transferring either to or from a bus. Due to its inherent complexity, this bi-level minimisation problem is extremely difficult to solve mathematically, since timetable optimisation is a non-linear non-convex mixed integer problem, with passenger flows defined by the route choice model, whereas the route choice model is a non-linear non-continuous mapping of the timetable. Therefore, a heuristic solution approach is developed in this paper, based on the idea of varying and optimising the offset of the bus lines. Varying the offset for a bus line impacts the waiting time passengers experience at any transfer stop on the bus line.In the bi-level timetable optimisation problem, the lower level is a transit assignment calculation yielding passengers’ route choice. This is used as weight when minimising waiting time by applying a Tabu Search algorithm to adapt the offset values for bus lines. The updated timetable then serves as input in the following transit assignment calculation. The process continues until convergence.The heuristic solution approach was applied on the large-scale public transport network in Denmark. The timetable optimisation approach yielded a yearly reduction in weighted waiting time equivalent to approximately 45 million Danish kroner (9 million USD).     

Will a driving restriction policy reduce car trips?—The case study of Beijing,China

A driving restriction policy, as one of the control-and-command rationing measures, is a politically acceptable policy tool to address traffic congestion and air pollution in some countries and cities in the world. Beijing is the first city in China to implement this policy. A one-day-a-week driving restriction scheme was expected to take 20% of cars off the road every week day. Using household survey and travel diary data, we analyze the short-term effect of this driving restriction policy on individual travel mode choice. The data also allow us to identify which demographic groups are more likely to break the restriction rule. The estimates reveal that the restriction policy in Beijing does not have significant influence on individuals’ decisions to drive, as compared with the policy’s influence on public transit. The rule-breaking behavior is constant and pervasive. We found that 47.8% of the regulated car owners didn’t follow the restriction rules, and drove “illegally” to their destination places. On average, car owners who traveled during peak hours and/or for work trips, and whose destinations were farther away from the city center or subway stations, were more likely to break the driving restriction rules. Therefore, Beijing is probably in need of more comprehensive and palatable policy instruments (e.g., a combination of congestion tolls, parking fees, fuel taxes, and high-speed transit facilities) to effectively alleviate traffic congestion and air pollution.     

Evolution of the household vehicle fleet: Anticipating fleet composition, PHEV adoption and GHG emissions in Austin, Texas

In today’s world of volatile fuel prices and climate concerns, there is little study on the relationship between vehicle ownership patterns and attitudes toward vehicle cost (including fuel prices and feebates) and vehicle technologies. This work provides new data on ownership decisions and owner preferences under various scenarios, coupled with calibrated models to microsimulate Austin’s personal-fleet evolution.Opinion survey results suggest that most Austinites (63%, population-corrected share) support a feebate policy to favor more fuel efficient vehicles. Top purchase criteria are price, type/class, and fuel economy. Most (56%) respondents also indicated that they would consider purchasing a Plug-in Hybrid Electric Vehicle (PHEV) if it were to cost $6000 more than its conventional, gasoline-powered counterpart. And many respond strongly to signals on the external (health and climate) costs of a vehicle’s emissions, more strongly than they respond to information on fuel cost savings.Twenty five-year simulations of Austin’s household vehicle fleet suggest that, under all scenarios modeled, Austin’s vehicle usage levels (measured in total vehicle miles traveled or VMT) are predicted to increase overall, along with average vehicle ownership levels (both per household and per capita). Under a feebate, HEVs, PHEVs and Smart Cars are estimated to represent 25% of the fleet’s VMT by simulation year 25; this scenario is predicted to raise total regional VMT slightly (just 2.32%, by simulation year 25), relative to the trend scenario, while reducing CO₂ emissions only slightly (by 5.62%, relative to trend). Doubling the trend-case gas price to $5/gallon is simulated to reduce the year-25 vehicle use levels by 24% and CO₂ emissions by 30% (relative to trend).Two- and three-vehicle households are simulated to be the highest adopters of HEVs and PHEVs across all scenarios. The combined share of vans, pickup trucks, sport utility vehicles (SUVs), and cross-over utility vehicles (CUVs) is lowest under the feebate scenario, at 35% (versus 47% in Austin’s current household fleet). Feebate-policy receipts are forecasted to exceed rebates in each simulation year.In the longer term, gas price dynamics, tax incentives, feebates and purchase prices along with new technologies, government-industry partnerships, and more accurate information on range and recharging times (which increase customer confidence in EV technologies) should have added effects on energy dependence and greenhouse gas emissions.     

Innovative systems for the transportation disadvantaged: Toward more efficient and operationally usable planning tools

When considering innovative forms of public transport for specific groups, such as demand responsive services, the challenge is to find a good balance between operational efficiency and 'user friendliness' of the scheduling algorithm even when specialized skills are not available. Regret insertion-based processes have shown their effectiveness in addressing this specific concern. We introduce a new class of hybrid regret measures to understand better why the behaviour of this kind of heuristic is superior to that of other insertion rules. Our analyses show the importance of keeping a good balance between short- and long-term strategies during the solution process. We also use this methodology to investigate the relationship between the number of vehicles needed and total distance covered - the key point of any cost analysis striving for greater efficiency. Against expectations, in most cases decreasing fleet size leads to savings in vehicle mileage, since the heuristic solution is still far from optimality.     

Turning Off the Heat: Impacts of Power Plant Decommissioning on Green Turtle Research in San Diego Bay

Green turtles (Chelonia mydas) are among the most high profile species in San Diego Bay, California, and understanding impacts of coastal development and industry is essential to the management and conservation of this local population. Here we describe power plant changing energy production and its impact on turtle habitat use and our ability to research and manage this population. For over 20 years, green sea turtles have been captured, assessed, and tagged near the South Bay Power Plant (SBPP) in the San Diego Bay; from 2002–2011, 104 turtles were captured on 212 occasions. As the 50-year-old SBPP generates less energy, effluent patterns change and water temperatures decrease, presumably to more natural conditions. There has been a concurrent decrease in turtle-capture success, perhaps due to lesser visitation to the effluent site where nets are tended. Seasonal catch-per-unit-effort declined from a high of 4.14 turtles per monitoring day, to a nine-year low of 1.33 during the 2010–2011 season. It is already apparent that management decisions related to energy policy are affecting the habitat and behavior of this stock of endangered turtles. Green turtles are expected to remain in the San Diego Bay after the SBPP becomes inoperative and continuing research will monitor future impacts and distribution shifts resulting from the expected changes in thermal pattern within south San Diego Bay. Research efforts to study this population (i.e., capture methods and locations) will require modification in response to these changes. Lessons learned here are applicable to the immediate coastal development of San Diego, as well as at similar interactions between marine turtles and industrial thermal effluent discharge throughout Southern California, the United States, and beyond.     

The value of service reliability

This paper studies the impact of service frequency and reliability on the choice of departure time and the travel cost of transit users. When the user has (α, β, γ) scheduling preferences, we show that the optimal head start decreases with service reliability, as expected. It does not necessarily decrease with service frequency, however. We derive the value of service headway (VoSH) and the value of service reliability (VoSR), which measure the marginal effect on the expected travel cost of a change in the mean and in the standard deviation of headways, respectively. The VoSH and the VoSR complete the value of time and the value of reliability for the economic appraisal of public transit projects by capturing the specific link between headways, waiting times, and congestion. An empirical illustration is provided, which considers two mass transit lines located in the Paris area.