Trip generation of vulnerable populations in three Canadian cities: a spatial ordered probit approach

This paper provides an analysis of trip generation of three vulnerable groups: single-parent families, low income households, and the elderly. It compares the mobility of these groups to that of the general population in three Canadian urban areas of Hamilton, Montreal and Toronto, based on data from large-sample metropolitan transport surveys. An ordered probit model with spatially expanded coefficients is used for the analysis. Spatial expansion shows that there are spatial mobility trends for elderly populations and low-income populations even after socio-economic attributes are accounted for. Such spatial differences are not generally found for single parent families. This novel spatial analysis provides clues as to where vulnerable populations may experience greater degrees of social exclusion. It provides information to help prioritize transportation infrastructure projects or other social programs to take into account the needs of vulnerable populations with the lowest levels of mobility.     

Costs of air pollutants from shipping: a meta-regression analysis

ABSTRACT

This study estimated the external cost of air pollution from shipping by means of a meta-regression analysis, which has not been made before. Three pollutants, which were included in most of the primary studies, were considered: nitrogen oxides (NO_x), sulphur dioxides (SO₂) and particulate matters with a diameter of max 2.5 micrometres (PM_2.5). All primary studies included damages of health and a majority added impacts on agriculture and estimated the cost of air pollutants by transferring cost estimates from studies on costs of air emissions from transports in Europe. Different regression models and estimators were used and robust results were found of statistically significant emission elasticities of below one, i.e. total external costs increase by less than 1% when emissions increase by 1%. There was a small variation between the pollutants, with the highest elasticity for PM_2.5 and lowest for NO_x. Calculations of the marginal external cost of the pollutants showed the same pattern, with this cost being approximately six times higher for PM_2.5 than for the other pollutants. Common to all pollutants was that the marginal external cost decreases when emission increases. Another robust result was a significant increase in the cost of studies published in journals compared with other publication outlets. These findings point out some caution when transferring constant external unit cost of air pollutant from shipping, which is much applied in the literature, and the cost functions estimated in this study could thus provide a complementary transfer mechanism.     

An exploratory analysis of joint-activity participation characteristics using the American time use survey

This paper presents a detailed exploratory analysis of joint activity participation characteristics using the American Time Use Survey (ATUS). As a very large nationwide survey that explicitly elicited information on both household and non-household companions for each activity episode, the ATUS is ideally suited for this analysis. Several intuitive and interesting results are obtained. Joint episodes are found to be of longer durations, significantly likely to take place at the residence of other people, and often confined to certain time periods of the weekday. In addition, important differences in these characteristics are also observed based on activity purpose, companion type, and the day of the week. These findings are intended to provide the basis for the justification of detailed collection of joint activity–travel participation information in household activity–travel surveys, and also as a stimulant for further empirical analysis and modeling of joint activity participation behavior.

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.

Simulating the impacts of household travel on greenhouse gas emissions,urban air quality,and population exposure

This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately 2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving meaningful reductions in GHGs and air pollution.     

Evaluation of general aviation management at Denver Stapleton airport

The potential benefits of general aviation management at a major airport is examined in this paper. The three general aviation management techniques investigated are volume reduction, runway segregation and time restriction.

First, a methodology for analyzing these techniques is discussed. The various effects on each user group are quantified for economic comparison between each management technique attempted. A computer simulation model was used to measure the delay effects. Then, these techniques are applied to Denver Stapleton Airport to measure their effects in present and future scenarios.

The results show that the best general aviation management technique is volume restriction. The use of peak‐hour pricing mechanism provided better results than random rejection, particularly if only a small degree of diversion is desired. The construction of a new general aviation runway provided equivalent results to the best technique tested.     

Optimization of transport investment and pricing policies: the role of transport pricing in network design

This paper investigates the role of transport pricing in network design and describes two facts about flow pattern in a transportation system. The first, illustrated by an example of Braess paradox, is that adding a new link to the network does not necessarily minimize the total travel time. The second is that introducing of appropriate toll pricing may reduce not only the total network time but also the travel time for each individual traveller. It follows with the investigations of different system objectives and different pricing policies (only toll pricing and distance‐based pricing are considered), and shows how they affect the system performance and flow pattern. Lastly, a systematic optimization process is proposed for integrated planning of transport network and pricing policies.     

Isolating high-priority metro and feeder bus transfers using smart card data

Fixed-rail metro (or ‘subway’) infrastructure is generally unable to provide access to all parts of the city grid. Consequently, feeder bus lines are an integral component of urban mass transit systems. While passengers prefer a seamless transfer between these two distinct transportation services, each service’s operations are subject to a different set of factors that contribute to metro-bus transfer delay. Previous attempts to understand transfer delay were limited by the availability of tools to measure the time and cost associated with passengers’ transfer experience. This paper uses data from smart card systems, an emerging technology that automatically collects passenger trip data, to understand transfer delay. The primary objective of this study is to use smart card data to derive a reproducible methodology that isolates high priority transfer points between the metro system and its feeder-bus systems. The paper outlines a methodology to identify transfer transactions in the smart card dataset, estimate bus headways without the aid of geographic location information, estimate three components of the total transfer time (walking time, waiting time, and delay time), and isolate high-priority transfer pairs. The paper uses smart card data from Nanjing, China as a case study. The results isolate eight high priority metro-bus transfer pairs in the Nanjing metro system and finally, offers several targeted measures to improve transfer efficiency.     

Modeling the interactions between car and bicycle in heterogeneous traffic

In this paper, a new cellular automata model is proposed to simulate the car and bicycle heterogeneous traffic on urban road. To capture the complex interactions between these two types of vehicles, a novel occupancy rule is adopted in the proposed model to consider the variable lateral distances of mixed vehicular traffic. Based on massive simulations, microscopic fundamental diagrams under different bicycle densities are devised. With these, the bicycle's spilling behavior is then investigated and discussed. In order to reflect the interference of a bicycle on a car, the interference transformation from friction state to block state is modeled explicitly. Finally, different simulation results under different occupancy rules indicate that the constant and fixed occupancy rule adopted in the previous studies might lead to overestimation of car flux in the heterogeneous traffic flows with different bicycle densities. Copyright © 2013 John Wiley & Sons, Ltd.     

Influence of vehicle driving parameters on the noise caused by passenger cars in urban traffic

In this work, a sample of vehicles has been instrumented to measure of variables that influence vehicle noise emissions in Madrid. A circuit reproducing a normal travel pattern in large city is traveled by a fleet of vehicle models representing the fleets of cars in a European city. A sample of drivers covers the test track under different traffic conditions. Driving parameters and noise emitted have been recorded in each test and average values have been extracted. These data have been analyzed to define the noise emissions produced by a vehicle in real driving conditions and to identify the noisiest driving behaviors.