The impact of weather conditions on bikeshare trips in Washington,DC

Bicycle usage can be affected by colder weather, precipitation, and excessive heat. The research presented here analyzes the effect of weather on the use of the Washington, DC, bikeshare system, exploiting a dataset of all trips made on the system. Hourly weather data, including temperature, rainfall, snow, wind, fog, and humidity levels are linked to hourly usage data. Statistical models linking both number of users and duration of use are estimated. Further, we evaluate trips from bikeshare stations within one quarter mile of Metro (subway) stations at times when Metro is operating. This allows us to determine whether Metro serves as a back-up option when weather conditions are unfavorable for bicycling. Results show that cold temperatures, rain, and high humidity levels reduce both the likelihood of using bikeshare and the duration of trips. Trips taken from bikeshare stations proximate to Metro stations are affected more by rain than trips not proximate to Metro stations and less likely when it is dark. This information is useful for understanding bicycling behavior and also for those planning bikeshare systems in other cities.     

Causal linkages between highways and sector-level employment

While transport infrastructure investments have usually been viewed to have long-term impacts on employment, what is perhaps not immediately clear is the direction of causality. This paper has sought to disentangle the causal relationship between highway infrastructure and employment, using panel data for the 48 contiguous US states from 1984 to 1997. Of particular emphasis in this analysis is the sectoral differences in the causal and spatial effects of highway capacity expansions for employment growth in alternative sectors of the economy. The results indicate that lane-mile additions of own-state major highways could increase state employment growth in the services sector while reducing growth in manufacturing. However, the causal relationship is also found to work the other way around. That is, both the rapid growth in services employment and the slowdown in manufacturing jobs temporally lead to increases in roadway capacity of non-interstate major roads. Our analysis also shows that highway infrastructure could produce both positive and negative employment spillovers across states. We find that improvements in non-interstate major roads outside the state border are beneficial to the manufacturing sector which generally serves regional and national markets. For the services sector, however, employment gains from interstate highways in the same state may come at the expense of other states as there is clear evidence of negative employment spillovers from interstate lane-mile additions.     

The vehicle emissions and performance monitoring system: analysis of tailpipe emissions and vehicle performance

This paper describes tailpipe emission results generated by the Vehicle Performance and Emissions Monitoring system (VPEMS). VPEMS integrates on‐board emissions and vehicle/driver performance measurements with positioning and communications technologies, to transmit a coherent spatio‐temporally referenced dataset to a central base station in near real time. These results focus on relationships between tailpipe emissions of CO, CO₂, NO_x and speed and acceleration. Emissions produced by different driving modes are also presented. Results are generally as one would expect, showing variation between vehicle speed, vehicle acceleration and emissions. Data is based upon a test run in central London on urban streets with speeds not exceeding about 65 km/h. The results presented demonstrate the capabilities of the system. Various issues remain with regard to validation of the data and expansion of the system capability to obtain additional vehicle performance data.     

Do Public Transport Improvements Increase Agglomeration Economies? A Review of Literature and an Agenda for Research

Public transport improvements may increase economic productivity if they enable the growth and densification of cities, downtowns, or industrial clusters and thereby increase external agglomeration economies. It has been argued that the potential agglomeration benefits are large; if so, understanding them better would be useful in making funding decisions about public transport improvements. We reviewed theoretical and empirical literature on agglomeration as well as a small number of articles on transportation's role in agglomeration. The theoretical literature is useful in understanding possible avenues by which transportation improvements might affect agglomeration, although there is little discussion of public transport specifically. Relevant empirical studies tend to focus on metropolitan regions and use a generalized measure of transportation cost. But public transport impacts on agglomeration are likely to be different from road investment impacts. We identified several ways of conducting research building on this literature that would help evaluate the agglomeration impacts of public transport proposals: tracing the links between transport, agglomeration, and productivity; better motivating research using theories of agglomeration mechanisms; taking scale and redistribution into account; exploring the functional form of agglomeration economies; accounting for endogeneity in model structure; and considering development context.     

Walking frequency, cars, dogs, and the built environment

To explain walking propensity or frequency, empirical studies have generally used two sets of explanatory variables, namely, socio-demographic variables and built environment variables. They have generally shown that both socio-demographic characteristics and built environment characteristics are associated with walking propensity. We examine the traditional walkability variables that encompass density, mix of uses, and network connectivity in New Jersey, using a statewide sample including an oversample of Jersey City. We estimate a two-stage least squares model using a conditional mixed process that combines an ordered probit model of walking frequency in the second stage based on a truncated regression of car ownership in the first stage. Our results show that built environment variables have some small effects, mainly from better network connectivity associated with increased walking frequency. One of our key findings is that built environment features also work indirectly via how they influence car ownership. In general, we find sufficient evidence that suggests fewer cars are owned in areas with more walkable built environment features. The other key variable that we control for is whether a household owns a dog. This also proved to be strongly associated with walking suggesting that dog ownership is a necessary control variable to understand the frequency of walking.     

Analysis of Metropolitan Highway Capacity and the growth in vehicle miles of travel

A number of recent studies have examined the hypothesis of induced travel in an attempt to quantify the phenomenon (Hansen & Huang 1997; Noland, forthcoming). No study has yet attempted to adjust for potential simultaneity bias in the results. This study addresses this issue by the use of an instrumental variable (two stage least squares) approach. Metropolitan level data compiled by the Texas Transportation Institute for their annual congestion report is used in the analysis and urbanized land area is used as an instrument for lane miles of capacity. While this is not an ideal instrument, results still suggest a strong causal relationship but probably that most previous work has had an upward bias in the coefficient estimates. The effect of lane mile additions on VMT growth is forecast and found to account for about 15% of annual VMT growth with substantial variation between metropolitan areas. This effect appears to be closely correlated with percent growth in lane miles, suggesting that rapidly growing areas can attribute a greater share of their VMT growth to growth in lane miles.     

The effect of the London congestion charge on road casualties: an intervention analysis

The introduction of the congestion charge in central London on the 17th of February, 2003, led to a reduction in congestion. One factor that has not been fully analysed is the impact of the congestion charge on traffic casualties in London. Less car travel within the charging zone may result in fewer traffic collisions, however, as the number of pedestrians, cyclists, and motorcyclists increased after the introduction of the congestion charge, the number of traffic casualties associated with these groups may also have increased. Reductions in congestion can also lead to faster speeds. Therefore, there could be increases in injury severity for those crashes that do occur. An intervention analysis was conducted to investigate the effect of the congestion charge on traffic casualties for motorists, pedestrians, cyclists, and motorcyclists, both within the charging zone and in areas of London outside the zone. This was done for killed and serious injuries (known as KSI in British terminology) and for slight injuries to examine whether there were any shifts in severity outcomes. Our results suggest no statistically significant effect for total casualties in London, but within the charging zone there has been a statistically significant drop in motorist casualties, and possibly an increase in cyclist casualties. There is an associated effect of an increase in casualties of motorcyclists and cyclists in some areas outside the charging zone, suggesting that changes in the design of the congestion charge may be needed to achieve reductions in casualties.