Is the provision of park-and-ride facilities at light rail stations an effective approach to reducing vehicle kilometers traveled in a US context?

Park-and-Ride (PNR) facilities are a commonly used means of making a transit system more widely available. However, given that a PNR passenger must drive for part of the trip, this approach to transit provision has an ambiguous influence on vehicle kilometers traveled (VKT). The impact of PNR on VKT is highly dependent of how PNR users would choose to travel if the PNR facilities were not available. Given that this issue has received little attention in a US context, we use the light rail system in Charlotte, North Carolina as a case study to examine the potential impact of PNR removal on VKT. Using a travel survey of PNR passengers, we estimate the VKT currently generated while driving to and from the rail stations and then estimate how VKT would change under various PNR removal scenarios that assume different behavioral responses. We find that, under the most realistic scenarios, PNR removal would lead the average PNR passenger to increase her driving by 8–15 VKT per round trip.     

Optimisation of parking guidance and information systems display configurations

Operators of parking guidance and information (PGI) systems often have difficulty in determining the best car park availability information to present to drivers in periods of high demand. This paper describes a behavioural model of parking choice incorporating drivers perceptions of waiting times at car parks based on PGI signs. This model was used to predict the influence of PGI signs on the overall performance of the traffic system.Relationships were developed for estimating the arrival rates at car parks based on trip patterns, driver characteristics, car park attributes as well as the car park availability information displayed on PGI signs. Drivers' perceptions of waiting times at car parks were assumed to be influenced by the PGI signs for observers of the signs and actual car park utilisation levels for non-observers. The model assumes that the choice of car park does not change after entering the city centre, even if conditions observed are different from those initially perceived.A mathematical programme was formulated to determine the optimal display PGI sign configuration to minimise queue lengths and vehicle kilometres of travel (VKT). The model was limited to off-street parking choices and illegal parking was not incorporated. A simple genetic algorithm was used to identify solutions that significantly reduced queue lengths and VKT compared with existing practices.These procedures were applied to an existing PGI system operating in Tama New Town near Tokyo. Significant reductions in queue lengths and VKT were predicted using the optimisation model. This would reduce traffic congestion and lead to various environmental benefits.     

Can environmental awareness explain declining preference for car-based mobility amongst generation Y? A qualitative examination of learn to drive behaviours

Preference for private, motorised transportation grew substantially throughout the global North, during the 20th Century. Through this time rates of licencing, and car ownership, and vehicle kilometres travelled (VKT) rose across age groups. This had a range of environmental and social equity implications, and ignited a priority for investment in road infrastructure. The system of automobility was cemented by lock-in through the assemblage of infrastructure, technologies, policies and behaviours supporting, and frequently requiring, car based mobility. Yet recent evidence has shown that generation Y (18–35 year olds) are practicing mobility in different ways to earlier generations. Stabilising and declining rates of VKT, licencing and vehicle ownership have been identified in a range of industrialised countries. Adopting an interdisciplinary approach, this paper draws from theories of social practice and the theory of planned behaviour, as two traditions to examine what people ‘do’, focusing on the social and the individual respectively. It examines the motivations to learn to drive (LTD), and the preference for driving in New Zealand, a highly car-dependent country, empirically drawing from 51 qualitative interviews. A series of meta-themes are presented and used to explain intended and actual behaviour relating to driving practices. The empirical research finds a diversity of highly nuanced interpretations of LTD, some of which reflect individual characteristics, whilst other interpretations are best understood grounded in a wider societal reading of contemporary trends and meanings. Frequently, justification for learning to drive goes beyond the competency and capacity to drive independently. Implications for policy and planning are detailed.     

Impact of license plate restriction policy on emission reduction in Hangzhou using a bottom-up approach

Many emission models have been developed for estimating the impact of transport policies on vehicle emissions. Macroscopic models, such as MOBILE and COPERT, are used for area analysis, while microscopic models, such as CMEM, are applied for corridor analysis. It is well known that driving dynamics are critical for estimating vehicle emissions. MOVES can be used for both macroscopic and microscopic emission analysis, and its advantage lies in the consideration of driving dynamics. Using a bottom-up approach, we study the impact of license plate restriction policy on vehicle emission reduction by localizing the emission rates in MOVES according to the vehicle emission standards in China. We implement the approach to evaluate the impact on the total vehicle emissions in Hangzhou, China before and after the implementation of license plate restriction policy. In the restricted region, the reductions of total Vehicle Kilometer Traveled (VKT) and total emissions are 9.6% and 6.9%, respectively. The result shows that the license plate restriction policy is effective in achieving the targeted emission reduction.     

Agent based model for dynamic ridesharing

Dynamic ridesharing involves a service provider that matches potential drivers and passengers with similar itineraries allowing them to travel together and share the costs. Centralized (binary integer programming) and decentralized (dynamic auction-based multi-agent) optimization algorithms are formulated to match passengers and drivers. Numerical experiments on the decentralized approach provides near optimal solutions for single-driver, single-passenger cases with lower computational burden. The decentralized approach is then extended to accommodate both multi-passenger and multi-driver matches. The results indicate higher user cost savings and vehicle kilometers traveled (VKT) savings when allowing multi-passenger rides. Sensitivity analysis is conducted to test the impact of the service provider commission rate on revenue and system reliability. While short term revenue can be maximized at a commission rate of roughly 50% of each trip’s cost, the resulting drop in system reliability would be expected to reduce patronage and revenues in the longer term.     

The role of urban form and transit in city car dependence: Analysis of 26 global cities from 1960 to 2000

Car dependence is in decline in most developed cities, but its cause is still unclear as cities struggle with priorities in urban form and transport infrastructure. This paper draws conclusions from analysis of data in 26 cities over the last 40 years of the 20th century. Statistical modelling techniques are applied to urban transport and urban form data, while examining the influence of region, city archetype and individual fixed effects. Structural equation modelling is employed to address causation and understand the direct and indirect effects of selected parameters on per capita vehicle kilometres travelled (VKT). Findings suggest that, while location effects are important, transit service levels and urban density play a significant part in determining urban car use per capita, and causality does flow from these factors towards a city’s levels of private vehicle travel as well as the level of the provision of road capacity.     

Does the income elasticity of road traffic depend on the source of income?

An extensive body of literature addresses the income elasticity of road traffic, in which income is typically treated as a homogenous quantity. Here we report evidence of heterogeneity in cross-sectional estimates of the elasticity of vehicle-kilometres of travel (VKT) with respect to income, when household income is disaggregated on the basis of income source.The results are generally intuitive, and show that the cross-sectional income elasticity of road traffic is not homogeneous as is typically specified in transport planning models. We show that in a number of circumstances the cross-sectional elasticity with respect to aggregate household income is of the opposite sign in comparison to more refined estimates of elasticity disaggregated by income source. If further research confirms that the elasticities we report here are causal in nature, neglecting the elemental effects could result in misleading results affecting practical infrastructure-investment and policy decisions, particularly as the mix of income sources shifts (e.g. if, as society ages, pension income increases as a share of all income).These results are of interest to both researchers and forecasters of travel demand, as well as designers of future travel survey instruments; the latter group must decide how to generate data about respondents’ income. Current expert guidance is to collect a single estimate of aggregate income at the household level. Future travel survey design choices will bound the analyses that can be supported by the resulting survey data, and therefore methodological research to re-visit the trade-offs associated with such choices is warranted.     

Modeling travel mode choice of young people with differentiated E-hailing ride services in Nanjing China

E-hailing ride service (ERS) has become increasingly popular globally and is changing the urban mobility landscape. There is insufficient research effort in understanding the impact of ERS on travel behavior, in particular among young people. This paper aims to start filling that research gap by first collecting mode choice preference data through a stated preference survey in City of Nanjing, China and then applying nested logit (NL) models and a series of post-estimation analysis to address a number of key research questions of mode choice behavior without and with ERS. Three ERS modes are considered in the Chinese context: DiDi Taxi (D-Taxi), DiDi Express (D-Express), and DiDi Premier (D-Premier), all provided by DiDi Chuxing, the dominant ERS service provider in China. The study finds that age makes little difference in mode choice preference when ERS is introduced between the two age groups considered (18–30 and 31–45). The study results also suggest that young travelers are naturally drawn to ERS for what it represents (a technology innovation) and its business (pricing) model. ERS appears to be a competitive alternative to the conventional modes especially when they are under performed. The study also finds that ERS will likely increase vehicle kilometers traveled (VKT) considerably, which will lead to increase in on-road vehicular emissions, unless some mechanism to switch users to ridesharing is in place.     

Implications of current household vehicle ownership and use patterns on the feasibility of electric cars

Electric cars provide the convenience and mobility of internal combustion engine vehicles without their dependence on fossil fuels or their associated environmental problems. While range constraints continue to limit their ultimate market acceptance, recent changes in the automotive marketplace have made American consumers more energy conscious. This paper examines a recently conducted U.S. survey of household travel behavior. The objective of the analysis is to determine the implications of observed vehicle ownership and use patterns on the feasibility of limited performance vehicles. Several factors are identified which serve to enhance the potential market penetration of electric cars. Included here are the recent growth in multiple vehicle ownership, and significant functional specialization in household allocation of vehicle use. On the other hand, it is pointed out that the substitutability of electric cars with the majority of currently owned vehicles is not clear by virtue of either their seating capacity, luggage space, or other specialized characteristics. Moreover, it is shown that the majority of secondary household cars are purchased used, which raises questions on the cost competitiveness of electric cars.The analysis of household daily driving range confirms the finding from previous studies that currently available electric vehicle technology can serve over 95 percent of vehicle travel requirements. However, serious flaws are pointed out in the use of cross sectional travel diaries for such analyses, raising questions as to the validity of the results. Overall, it is concluded that the ultimate potential size of the electric vehicle market with current technology is about one third of U.S. household vehicles, representing approximately one fifth of total non-commercial VKT. However, more research is needed to assess whether functionally feasible electric vehicles can actually be competitive under market conditions.     

Vehicle kilometers traveled reduction impacts of Transit-Oriented Development: Evidence from Shanghai City

The role of residential self-selection has become a major subject in the debate over the relationships between the built environment and travel behavior. Numerous previous empirical studies on this subject have provided valuable insights into the associations between the built environment and travel behavior. However, the vast majority of the studies were conducted in North American and European cities; yet this research is still in its infancy in most developing countries, including China, where residential and transport choices are likely to be more constrained and travel-related attitudes quite different from those in the developed world. Using the data collected from 2038 residents currently living in TOD neighborhoods and non-TOD neighborhoods in Shanghai City, this paper aims to partly fill the gaps by investigating the causal relationship between the built environment and travel behavior in the Chinese context. More specifically, this paper employs Heckman’s sample selection model to examine the reduction impacts of TOD on personal vehicle kilometers traveled (VKT), controlling for self-selection. The results show that whilst the effects of residential self-selection are apparent; the built environment exhibits the most significant impacts on travel behavior, playing the dominant role. These findings produce a sound basis for local policymakers to better understand the nature and magnitude toward the impacts of the built environment on travel behavior. Providing the government department with reassurance that effective interventions and policies on land use aimed toward altering the built environment would actually lead to meaningful changes in travel behavior.     

Assessing the accuracy of the Sydney Household Travel Survey with GPS

Over the past few years, GPS has been used in a number of surveys in the US to assess the accuracy of household travel surveys. The results have been somewhat alarming in that most of these exercises have shown that the standard trip-based CATI survey conducted in the US under-reports travel by about 20–25%. It was decided to use GPS to assess the accuracy of the Sydney Household Travel Survey, a continuous survey conducted by face-to-face interviewing. The procedure used was for the interviewers to recruit households for the household travel survey in the normal manner, and then, if the household met certain criteria, to endeavour to recruit the household to also undertake a GPS survey. A small sample of about 50 households was obtained, and GPS devices successfully retrieved that measured data on the same day as the travel diary was completed. In addition, participants in the GPS survey completed a prompted recall survey a week or two later, using maps and tabulations of travel obtained from the GPS devices, to identify mode, purpose and occupancy for trips measured by the GPS, and also to check for accuracy in defining trip ends and total number of trips. Based on the analysis of the GPS compared to the diary results, it was found that respondents under-reported their travel by about 7%, which is much less than in the US CATI results. Respondents were also found to under-report travel distances and over-report travel times. There was also a high incidence of non-reporting for VKT.

Estimating transboundary economic damages from climate change and air pollution for subnational incentives for green on-road freight

Subnational incentives to adopt zero emission vehicles (ZEVs) are critical for reducing the external economic damages posed by transportation to air quality and the climate. Few studies estimate these damages for on-road freight, especially at scales relevant for subnational policies requiring cross-border cooperation. Here, we assess the damages to US receptors from emissions of air pollutants (PM_2.5, NO_x, SO₂, NH₃), and greenhouse gases (CO₂, CH₄, N₂O) from medium and heavy duty freight trucking, and the benefits of ZEV adoption by census division in the Province of Ontario. We develop an integrated modelling framework connecting a travel demand model, a mobile emissions simulator, and a regression based marginal damages model of air pollutants and climate change. We estimate $1.9 billion (2010 USD) in annual cross-border damages, or $0.16/VKT, resulting from scaled up atmospheric emissions from a ‘typical day’ of medium and heavy duty truck traffic volume for Ontario in 2012. This implies approximately $8000 per truck per year in damages, which could inform an economic incentive for emission reduction. The provincial goal of 5% ZEV adoption would reduce GHG emissions in 2012 by 800 ktCO₂e, yielding $89 Million (2010 USD) in cross-border benefits annually, with air quality co-benefits of $83/tCO₂e. This result varies between −19% and 22% based on sensitivity analysis for travel and emissions models, though economic damages are likely the largest uncertainty source. Such advances in subnational scale integrated modeling of the environmental impacts of freight can offer insights into the sustainable design of clean freight policy and programs.     

Public sector comparators for UK PFI roads: inside the black box

A public sector comparator (PSC) represents the hypothetical, risk-adjusted cost of a project—such as a road scheme—when that project is financed, owned and implemented by government. A PSC is commonly used in public procurement decision-making as a yardstick against which private investment proposals are evaluated. Using original material released by the UK Highways Agency for the first time, the author recreated the PSCs used for the evaluation of the first eight road projects to be promoted under the UK’s private finance initiative (PFI). Alternative assumptions regarding project risks were modelled using different levels of optimism-bias uplift, and the impact on value-for-money of using different discount rates was evaluated. Public sector comparators have attracted considerable attention in the literature as they retain a pivotal role in the policy decision to use—or not use—private finance. However the fact that their detail is usually kept confidential by public sector procuring agencies—because of commercial sensitivities—has restricted informed discussion and open debate. Now the architecture of these comparators is laid bare for critical examination. It has generally been assumed that any reduction in the discount rate used in PSC calculations will favour conventional procurement over PFI-type contracting arrangements. The research reported in this paper demonstrates that the relationship between the discount rate and the attractiveness of using private finance is not as simple as has been assumed, and the outcome in terms of value-for-money is not as predictable as has previously been reported.     

Optimal choice of capacity,toll and government guarantee for build-operate-transfer roads under asymmetric cost information

The private provision of public roads via the build-operate-transfer (BOT) mode has been increasingly used around the world. By viewing a BOT contract as a combination of road capacity, toll and government guarantee, this paper investigates optimal concession contract design under both symmetric and asymmetric information about the marginal maintenance cost of private investors. Under asymmetric information, the government guarantee serves as an instrument to induce a private investor to reveal his true cost information. Compared with the situation under symmetric information, the government will suffer a loss of social welfare; the private investor will charge a higher toll that increases in his reported marginal maintenance cost, and specify a lower capacity that decreases with the reported cost. The results also show that the private investor obtains extra information rent beyond the reservation level of return and the rent decreases with his reported cost. However, the resulting volume-capacity ratios of the BOT road under both information structures are the same.     

Over-reporting vs. overreacting: Commuters’ perceptions of travel times

In a large-scale, real-life peak avoidance experiment, we asked participants to provide estimates of their average in-vehicle travel time during their morning commute. After comparing the reported travel times with the actual corresponding travel times, we found that the average travel times were overstated by a factor of 1.5. We showed that driver- and link-specific characteristics partially explained these exaggerations. Using the stated and revealed preference data, we investigated whether the driver-specific reporting errors were consistent with the drivers’ scheduling behaviors in reality and in hypothetical choice experiments. In both cases, we found no robust evidence that drivers behave as if they misperceive travel times to a similar extent as those they misreported, thereby implying that the reported travel times did not represent the actual or perceived travel times in a truthful manner. The results of this study suggest that caution should be recommended when reported travel time data are used in an uncritical manner during transport research and when determining policy.     

Characterising and predicting car ownership using rough sets

This paper applies the relatively new knowledge discovery technique of Rough set analysis to identify the factors that influence the level of car ownership in a household. The study uses the detailed Great Britain National Travel Survey data set which contains information on both household and individual travel behaviour. The knowledge extraction is done using the theory of Rough sets and is presented in the form of easily understood if-then statements or rules which reveal how each attribute influences car ownership behaviour. These rules can then be used to predict household car ownership from information held about previously unseen households and the classification performance of the rules can be assessed. The performance of this classification task is shown to be on a par with other reported studies in this area.     

Large-scale network distribution of pooled empty freight cars over time,with limited substitution and equitable benefits

A set of models and procedures is described for finding the optimal distribution of empty freight cars owned by the railroads participating in a pooling agreement. A distinction is drawn between a system focus, in which the emphasis is on minimizing total cost, and a company focus, in which the benefits of the agreement to the individual railroads are emphasized. Limited car substitution is accounted for by combining interchange costs with distribution costs, and incorporating interchange possibilities and prohibitions into the network structure. Temporal variations in car supply and demand levels are also taken into account. A large-scale network algorithm is used in conjunction with decomposition to obtain solutions which show for a given time horizon how much equity can be achieved in the balance of savings among the railroads involved and at what cost. Results using actual operating data are reported.     

Real-time traveler information for urban arterials: a method for selecting metropolitan routes of significance

Although multi-criteria analysis (MCA) has been commonly used to guide transportation decisions related to traditional infrastructure, limited applications are reported for intelligent transportation systems. The objective of this study is to apply MCA for selecting arterial routes for real-time traveler information, to conform with recent US federal regulations. This study applies the method in two metropolitan areas and the paper describes which criteria were chosen and how important each were considered. In all, this study guided the selection of seven arterial routes for deployment of real-time traveler information collection and dissemination. This study demonstrates how a transportation agency can apply MCA for traveler information planning and the method provides value for other agencies seeking to come into compliance with traveler information regulations.