Bicycling renaissance in North America? An update and re-appraisal of cycling trends and policies

This paper reviews trends in cycling levels, safety, and policies in Canada and the USA over the past two decades. We analyze aggregate data for the two countries as well as city-specific case study data for nine large cities (Chicago, Minneapolis, Montréal, New York, Portland, San Francisco, Toronto, Vancouver, and Washington). Cycling levels have increased in both the USA and Canada, while cyclist fatalities have fallen. There is much spatial variation and socioeconomic inequality in cycling rates. The bike share of work commuters is more than twice as high in Canada as in the USA, and is higher in the western parts of both countries. Cycling is concentrated in central cities, especially near universities and in gentrified neighborhoods near the city center. Almost all the growth in cycling in the USA has been among men between 25-64 years old, while cycling rates have remained steady among women and fallen sharply for children. Cycling rates have risen much faster in the nine case study cities than in their countries as a whole, at least doubling in all the cities since 1990. They have implemented a wide range of infrastructure and programs to promote cycling and increase cycling safety: expanded and improved bike lanes and paths, traffic calming, parking, bike-transit integration, bike sharing, training programs, and promotional events. We describe the specific accomplishments of the nine case study cities, focusing on each city’s innovations and lessons for other cities trying to increase cycling. Portland’s comprehensive package of cycling policies has succeeded in raising cycling levels 6-fold and provides an example that other North American cities can follow.     

利用OBDⅡ系统进行排放检测

OBD Ⅱ系统很快将取代标准排气管检测排放污染。在美国己制订了相应的法规,马克·沃伦先生在本文中解释这项法规涉及的内容以及与排气管检测的区别。通过本文,读者可了解排放检测的最新技术。     

An approach to estimation of near-surface turbulence and CO2 transfer velocity from remote sensing data

The air–sea CO₂ exchange is primarily determined by the boundary-layer processes in the near-surface layer of the ocean since it is a water-side limited gas. As a consequence, the interfacial component of the CO₂ transfer velocity can be linked to parameters of turbulence in the near-surface layer of the ocean. The development of remote sensing techniques provides a possibility to quantify the dissipation of the turbulent kinetic energy in the near-surface layer of the ocean and the air–sea CO₂ transfer velocity on a global scale. In this work, the dissipation rate of the turbulent kinetic energy in the near-surface layer of the ocean and its patchiness has been linked to the air–sea CO₂ transfer velocity with a boundary-layer type model. Field observations of upper ocean turbulence, laboratory studies, and the direct CO₂ flux measurements are used to validate the model. The model is then forced with the TOPEX POSEIDON wind speed and significant wave height to demonstrate its applicability for estimating the distribution of the near-surface turbulence dissipation rate and gas transfer velocity for an extended (decadal) time period. A future version of this remote sensing algorithm will incorporate directional wind/wave data being available from QUIKSCAT, a now-cast wave model, and satellite heat fluxes. The inclusion of microwave imagery from the Special Sensor Microwave Imager (SSM/I) and the Synthetic Aperture Radar (SAR) will provide additional information on the fractional whitecap coverage and sea surface turbulence patchiness.     

Decision support for risk assessment of mid-air collisions via population-based measures

Specifying proximity warning functions for aircraft in managed airspace has received considerable attention. However, similar functions for aircraft operating in unmanaged airspace have received comparatively little analysis despite the fact that these functions are stressed to a greater physical degree, and perhaps more frequently, than in managed airspace. The mid-air collision hazard and its associated risk are re-examined from both an historical and a systematic engineering modelling viewpoint. Historic measures of this transport risk in managed airspace have been based on fatalities normalized by flight hours or flight movements. However some of these data may not be available in unmanaged airspace. Another approach to measurement directs attention to populations at risk where several measures are now well known: collective risk, individual risk and the frequency of occurrence of the hazards that give rise to such risk. A decision support methodology is presented that relates both transport and population-based approaches. A cohesive and consistent set of aspired goals for various stakeholder groups can be set taking into account the different stakeholder needs. A case study is drawn from historic mid-air collision data to illustrate the process. A consistent basis for national-level policy decisions harmonised with proactive engineering design requirements is achieved. The strengths, limitations and implications of this approach for engineering design purposes are discussed.     

Valuation of improved railway rolling stock: A review of the literature and new evidence

The paper provides a comprehensive review of a large amount of previously unpublished British evidence about the valuation of new railway rolling stock and its effects on demand. An important conclusion is that incentives to bias Stated Preference responses and unfamiliarity with the rolling stock being considered have led to inflated values. This has broader implications for the use of Stated Preference techniques. Also provided is fresh empirical evidence for a range of different types of rolling stock and specific rolling stock attributes. A novel aspect of the research was the use of disaggregate Revealed Preference choice data. The estimated rolling stock values are much lower than those obtained from previous studies.     

The impact of planned disruptions on rail passenger demand

Transportation - Disruptions to rail journeys are experienced by rail passengers on a daily basis throughout the world, with the impacts on passengers ranging from minimal to major. Such...     

Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities

The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.     

Aggregating mobile object trajectories: cumulative time geographic density estimation for GPS data

We present new approaches that expand upon the time geographic density estimation (TGDE) framework previously employed to estimate potential path trees. In the past, TGDE metrics have identified possible locations an individual moving object may have passed between, given known origin and destination points. This paper utilizes a new form of TGDE to investigate taxicab GPS traces over a specified time horizon with position ‘gaps’. To this end, we propose a new extension to the TGDE framework, TGDE-C, which is used to determine the cumulative TGDE values for a group of GPS traces, at a given location. These metrics are applied to multiple taxis and allow for time of day analysis. Additionally, we combine these new extensions with existing TGDE metrics that allow us to determine how accessible individual or groups of vehicles are to urban opportunities.     

Genetics of traffic assignment models for strategic transport planning

This paper presents a review and classification of traffic assignment models for strategic transport planning purposes by using concepts analogous to genetics in biology. Traffic assignment models share the same theoretical framework (DNA), but differ in capability (genes). We argue that all traffic assignment models can be described by three genes. The first gene determines the spatial capability (unrestricted, capacity restrained, capacity constrained, and capacity and storage constrained) described by four spatial assumptions (shape of the fundamental diagram, capacity constraints, storage constraints, and turn flow restrictions). The second gene determines the temporal capability (static, semi-dynamic, and dynamic) described by three temporal assumptions (wave speeds, vehicle propagation speeds, and residual traffic transfer). The third gene determines the behavioural capability (all-or-nothing, one shot, and equilibrium) described by two behavioural assumptions (decision-making and travel time consideration). This classification provides a deeper understanding of the often implicit assumptions made in traffic assignment models described in the literature. It further allows for comparing different models in terms of functionality, and paves the way for developing novel traffic assignment models.     

Approximate algorithms for the discrete network design problem

The discrete network design problem is one of finding a set of feasible actions (projects) from among a collection of possible actions, that when implemented, optimizes some objective function(s). This is a combinatorial optimization problem that is very expensive to solve exactly. This paper proposes two algorithms for obtaining approximate solutions to the discrete network design problem with much less computational effeort. The computational savings are achieved by approximating the original problem with a new formulation which is easier to solve. The first algorithm proposed solves this approximate problem exactly, while the second is even more efficient, but provides only a near-optimal solution to the approximate problem. Experience with test problems indicates that these approximations can reduce the computational effort by a factor of 3–5, with little loss in solution accuracy.