A comparison of the sustainability of public and private transportation systems: Study of the Greater Toronto Area

A macroscopic assessment of the impacts of private and public transportation systems on the sustainability of the Greater Toronto Area (GTA) is undertaken from economic, environmental and social perspectives. The methodology draws upon the urban metabolism and sustainability indicators approaches to assessing urban sustainability, but compares modes in terms of passenger-kms. In assessing the economic sustainability of a city, transportation should be recognized as a product, a driver and a cost. In 1993, the traded costs of automobile use in the GTA were approximately balanced by the value of the automobile parts and assembly industry. But local transit costs 1/3 to 1/6 of the auto costs per person-km, in traded dollars, mainly because local labour is the primary cost.Public transportation is more sustainable from an environmental perspective. Automobile emissions are a major contributor to air pollution, which is a serious contemporary environmental health problem in Toronto. Public transportation modes are less energy intensive (including indirect energy consumption) and produce CO₂ at an order of magnitude lower, although these benefits are partially undermined by under-utilization of transit capacity and the source of electricity generation.The social benefits of automobile use are likely more significant than costs in determining GTA residents' preferential mode choice. The speed and access of auto use provide important economic benefits, e.g. relating to employment and product choice. Nevertheless, offsetting the service attributes of private transportation are large social costs in terms of accidents. The costs of automobile insurance provide one tangible measure of such negative impacts.In order to improve the sustainability of the GTA, innovative approaches are required for improving the performance level of public transportation or substantially reducing the need for the service level provided by automobiles. Efforts such as greater integration of bicycles with public transit, or construction of light-rail systems in wide roadways, might be considered. But to be sustainable overall, a transportation system has to be flexible and adaptable and so must combine a mixture of modes.     

Will autonomous vehicles change auto commuters’ value of travel time?

This paper examines the potential impact of autonomous vehicles on commuters’ value of travel time (VOTT). In particular, we focus on the effect on auto commuters in small and medium-sized metropolitan areas, concerning the spatial variability across urban areas, suburbs, and rural areas. We design a stated choice experiment to elicit potential changes in 1,881 auto commuters’ valuation of travel time in autonomous vehicles and apply a mixed logit model to quantify the changes in the value of travel time if taking autonomous vehicles. The results of this study suggest that the effect of autonomous vehicles on the VOTT is spatially differentiated. We find that riding in a private autonomous vehicle reduces the commuting VOTT of suburban, urban, and rural drivers by 32%, 24%, and 18%, respectively, compared to 14%, 13%, and 8% for riding in a shared autonomous vehicle. Finally, we discuss the implications of these lower values of time on transportation and land use planning.     

Discussing the “positive utilities” of autonomous vehicles: will travellers really use their time productively?

ABSTRACT

Autonomous vehicles (AVs) are expected to reshape travel behaviour and demand in part by enabling productive uses of travel time—a primary component of the “positive utility of travel” concept—thus reducing subjective values of travel time savings (VOT). Many studies from industry and academia have assumed significant increases in travel time use and reductions in VOT for AVs. In this position paper, I argue that AVs’ VOT impacts may be more modest than anticipated and derive from a different source. Vehicle designs and operations may limit activity engagement during travel, with AV users feeling more like car passengers than train riders. Furthermore, shared AVs may attenuate travel time use benefits, and productivity gains could be limited to long-distance trips. Although AV riders will likely have greater activity participation during travel, many in-vehicle activities today may be more about coping with commuting burdens than productively using travel time. Instead, VOT reductions may be more likely to arise from a different “positive utility”—subjective well-being improvements through reduced stresses of driving or the ability to relax and mentally transition. Given high uncertainty, further empirical research on the experiential, time use, and VOT impacts of AVs is needed.     

Measuring community reaction to urban transportation impacts using Von Neumann‐Morgenstern utility theory

This paper attempts to measure the impacts of urban transportation system improvements or changes on the community. The community's perceptions of the impacts are represented by its utilities (or disutilities) over various ranges of values of the multiple attributes representing these impacts. The utility technique used in the evaluation is based upon von Neumann‐Morgenstern (vN‐M, 1947) Utility Theory, and is applied using Raiffa's (1970) Fractile Method.

The paper specifically applies the technique to model the perceptions of five subgroups within a community to the impact of a new light rail transit system that is being incorporated in the transportation system of the City of Calgary.

Results of the modeling indicate explicitly how the community changes its perception over ranges of values of the attributes evaluated. Biases of various subgroups within the community over these attributes are also shown. Statistical tests indicate that aggregated utility perceptions can represent the utility perceptions of the individual subgroups quite reasonably.     

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.     

Decomposing travel times measured by probe-based traffic monitoring systems to individual road segments

In probe-based traffic monitoring systems, traffic conditions can be inferred based on the position data of a set of periodically polled probe vehicles. In such systems, the two consecutive polled positions do not necessarily correspond to the end points of individual links. Obtaining estimates of travel time at the individual link level requires the total traversal time (which is equal to the polling interval duration) be decomposed. This paper presents an algorithm for solving the problem of decomposing the traversal time to times taken to traverse individual road segments on the route. The proposed algorithm assumes minimal information about the network, namely network topography (i.e. links and nodes) and the free flow speed of each link. Unlike existing deterministic methods, the proposed solution algorithm defines a likelihood function that is maximized to solve for the most likely travel time for each road segment on the traversed route. The proposed scheme is evaluated using simulated data and compared to a benchmark deterministic method. The evaluation results suggest that the proposed method outperforms the bench mark method and on average improves the accuracy of the estimated link travel times by up to 90%.     

Space,money, life-stage,and the allocation of time

Demographic, socioeconomic, seasonal, and scheduling factors affect the allocation of time to various activities. This paper examines those variables through exploration of the 1990 Nationwide Personal Transportation Survey, which has been inverted to track activity duration. Two key issues are considered. First, how much can activity duration and frequency explain travel duration? The analysis shows activity duration has positive and significant effects on travel duration, supporting recent arguments in favor of activity based models. Second, which recent trend is the main culprit in the rise in travel: suburbanization, rising personal incomes, or female labor force participation? This paper examines the share of time within a 24-hour budget allocated to several primary activities: home, work, shop, and other. The data suggest that income and location have modest effects on time allocation compared with the loss of discretionary time due to working.