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.     

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.     

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.     

Urban form,travel time,and cost relationships with tour complexity and mode choice

The primary purpose of this study was to investigate how relative associations between travel time, costs, and land use patterns where people live and work impact modal choice and trip chaining patterns in the Central Puget Sound (Seattle) region. By using a tour-based modeling framework and highly detailed land use and travel data, this study attempts to add detail on the specific land use changes necessary to address different types of travel, and to develop a comparative framework by which the relative impact of travel time and urban form changes can be assessed. A discrete choice modeling framework adjusted for demographic factors and assessed the relative effect of travel time, costs, and urban form on mode choice and trip chaining characteristics for the three tour types. The tour based modeling approach increased the ability to understand the relative contribution of urban form, time, and costs in explaining mode choice and tour complexity for home and work related travel. Urban form at residential and employment locations, and travel time and cost were significant predictors of travel choice. Travel time was the strongest predictor of mode choice while urban form the strongest predictor of the number of stops within a tour. Results show that reductions in highway travel time are associated with less transit use and walking. Land use patterns where respondents work predicted mode choice for mid day and journey to work travel.

Integrated Control Methodologies for Road Vehicles

Summary This paper considers the scope, methodologies and architectures for the design and development of interacting control systems in road vehicles. The increasing use of electronic controls leads inevitably to an increase in overall system complexity. Given the time and economic constraints of the modern automotive industry, it is not feasible to synthesise and validate the full set of vehicle controls in the form of a unified and centralized controller. On the other hand a fully decentralized approach to control system development and operation will induce performance limitations from un-modelled or unexpected interactions; at worst, such interactions can cause instability and loss of function. There is now increasing pressure to achieve control coordination whilst maintaining a modular approach to the overall system design. With this in mind, the paper provides a framework to review current practice in integrated vehicle control, assesses recent developments in control integration methodologies that are most relevant to the vehicle application, and formulates an enhanced multi-layer architecture that includes explicit coordination functionality. Overall emphasis is placed on the role of control system architecture, the resulting flow of control information and the implications for control system design. An example from handling dynamics is presented, demonstrating the viability of new and flexible approaches. In conclusion a number of outstanding research problems are highlighted.     

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.     

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.     

An analysis of the commuter departure time decision

Transportation planners and transit operators alike have become increasingly aware of the need to diffuse the concentration of peak period travel in an effort to improve gasoline economy and reduce peak load requirements. An evaluation of the potential effectiveness of strategies directed to achieve this end requires an understanding of factors which affect commuter trip timing decisions. The research discussed in this article addresses this particular problem through the development and estimation of a commuter departure time (to work) choice model.A number of conclusions were drawn based on the departure time model results and related analyses. It was found that work schedule flexibility, mode, occupation, income, age, and transportation level of service all influence departure time choice. The uncertainty in work arrival time and the consequences of various work arrival times may also be determinants of commuter departure time choice.The estimated model represents improvements over previous work in that it more explicitly considers work arrival time uncertainty and travelers' perceived loss associated with varying work arrival times, and additional socio-demographic factors which can potentially affect departure time choice. Furthermore, the estimated model includes consideration of transit commuters, in addition to single occupant auto and carpool work travelers. The inclusion of transit commuters represents a particularly important contribution for policy analysis, since the model could potentially be used to study the effect of service and employment policies on transit system peak load requirements.     

Research contributions to managing transit service reliability

Service reliability problems are a major concern shared by transit system users and operators. Unreliable service leads to additional vehicle requirements and higher operating costs; passengers suffer increased wait time and higher travel time uncertainty, leading to a general dissatisfaction with service and the possibility of seeking other means of transport. Because of the significance of this problem, considerable research attention has been focused in recent years on developing ways to improve service reliability. This paper examines contributions which have been made to managing transit service reliability. This topic encompasses the subjects of vehicle run time, run time variation, headway variation, passenger wait time, and reliability control. Both theoretical and empirical approaches have been undertaken, and each has contributed to our knowledge in addressing the overall problem. Significant contributions to the state-of-the-art are reported and the implications on present practice are discussed.     

The valuation and demand impacts of the worthwhile use of travel time with specific reference to the digital revolution and endogeneity

Transportation - The research reported here is concerned with how the worthwhile use of travel time might impact on the value of travel time savings (VTTS) and on demand set in the context of the...