Inter-temporal variation in the travel time and travel cost parameters of transport models

The parameters for travel time and travel cost are central in travel demand forecasting models. Since valuation of infrastructure investments requires prediction of travel demand for future evaluation years, inter-temporal variation of the travel time and travel cost parameters is a key issue in forecasting. Using two identical stated choice experiments conducted among Swedish drivers with an interval of 13 years, 1994 and 2007, this paper estimates the inter-temporal variation in travel time and cost parameters (under the assumption that the variance of the error components of the indirect utility function is equal across the two datasets). It is found that the travel time parameter has remained constant over time but that the travel cost parameter has declined in real terms. The trend decline in the cost parameter can be entirely explained by higher average income level in the 2007 sample compared to the 1994 sample. The results support the recommendation to keep the travel time parameter constant over time in forecast models, but to deflate the travel cost parameter with the forecasted income increase among travellers and the relevant income elasticity of the cost parameter. Evidence from this study further suggests that the inter-temporal and the cross-sectional income elasticities of the cost parameter are equal. The average elasticity is found to be ?0.8 to ?0.9 in the present sample of drivers, and the elasticity is found to increase with the real income level, both in the cross-section and over time.     

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.     

A repeated cross-sectional evaluation of car ownership

This paper studies changes in the relationship between household car ownership and income by household type. Ordered response probit models of car ownership are estimated for a sample of households repeatedly at six time points to track the evolution of income elasticities of car ownership over time. Elasticities of car ownership are found to change over time, questioning the existence of a unique equilibrium point between demand and supply that is implicitly assumed in traditional cross-sectional discrete choice car ownership models. Moreover, different household types and households that underwent household type transitions showed differing patterns of change in elasticities. Observed trends in car ownership and income clearly show behavioral asymmetry where the elasticity of procuring an additional car is greater than that of disposing a car. This too shows the inadequacy of traditional cross-sectional models of car ownership which tend to predict symmetry in behavior. The study suggests the importance of incorporating dynamic trends into the forecasting process, which can be accomplished through the use of longitudinal data.     

Catching the tail: Empirical identification of the distribution of the value of travel time

Recent methodological advances in discrete choice analysis in combination with certain stated choice experiments have allowed researchers to check empirically the identification of the distribution of latent variables such as the value of travel time (VTT). Lack of identification is likely to be common and the consequences are severe. E.g., the Danish value of time study found the 15% right tail of the VTT distribution to be unidentified, making it impossible to estimate the mean VTT without resorting to strong assumptions with equally strong impact on the resulting estimate. This paper analyses data generated from a similar choice experiment undertaken in Sweden during 2007-2008 in which the range of trade-off values between time and money was significantly increased relative to the Danish experiment. The results show that this change allowed empirical identification of effectively the entire VTT distribution. In addition to informing the design of future choice experiments, the results are also of interest as a validity test of the stated choice methodology. Failure in identifying the right tail of the VTT would have made it difficult to maintain that respondents’ behaviour is consistent with utility maximisation in the sense intended by the experimenter.     

Accuracy of the Gothenburg congestion charges forecast

This paper explores the accuracy of the transport model forecast of the Gothenburg congestion charges, implemented in 2013. The design of the charging system implies that the path disutility cannot be computed as a sum of link attributes. The route choice model is therefore implemented as a hierarchical algorithm, applying a continuous value of travel time (VTT) distribution. The VTT distribution was estimated from stated choice (SC) data. However, based on experience of impact forecasting with a similar model and of impact outcome of congestion charges in Stockholm, the estimated VTT distribution had to be stretched to the right. We find that the forecast traffic reductions across the cordon and travel time gains were close to those observed in the peak. However, the reduction in traffic across the cordon was underpredicted off-peak. The necessity to make the adjustment indicates that the VTT inferred from SC data does not reveal the travellers’ preferences, or that there are factors determining route choice other than those included in the model: travel distance, travel time and congestion charge.     

Empirical estimation of price and income elasticities of air cargo demand: The case of Hong Kong

This paper estimates the price and income elasticities of air cargo demand and examines how they may change after the 2008 financial crisis. Using a set of time series data, we simultaneously estimate the aggregated demand and supply functions of air cargo at Hong Kong International Airport (HKIA). We find that during the entire sampling period of 2001–2013, the price elasticity for air cargo transport demand at HKIA ranges from −0.74 to −0.29, suggesting that air cargo demand in Hong Kong reacts negatively to price (as expected) but does not appear to be very sensitive to price. The income elasticity ranges from 0.29 to 1.47 and appears sensitive to seasonality adjustment approaches. However, in terms of the speed of changes, air cargo demand changes much faster than overall economy, indicating the presence of a pro-cyclical pattern of air cargo traffic with respect to the overall economy. Our analysis shows that air cargo demand becomes more sensitive to changes in both price and income after 2008.     

Meta-analysis of UK values of travel time: An update

Numerous travel demand studies have been carried out over the past five decades, many of which produce estimates of the value of travel time. This includes a rich body of largely unpublished evidence, which can provide valuable insights into the impact of variables such as GDP, travel distance, purpose and mode on this critical parameter for transport modelling and appraisal. The work reported in this paper updates and extends our previous meta-analyses of UK values of time ( [Wardman, 1998], [Wardman, 2001a] and [Wardman, 2004]) by adding recent studies and widening the range of explanatory variables included. Our current research covers 226 studies carried out between 1960 and 2008, yielding a total of 1749 valuations (a 50% increase relative to our previous work) and making this the largest data set of its kind to the best of our knowledge. This is also the most comprehensive study to date of parameters other than in-vehicle time and includes valuations of walk, wait, headway, congested, free flow, late, departure time shift and search time. Exploratory analysis of the data set provides interesting insights into methodological trends in travel demand modelling.For each valuation, over thirty quantitative and categorical variables were recorded and then included in a multivariate regression model to explain variations in the value of time. A large number of statistically significant effects were obtained from this meta-analysis, some of which are in marked contrast with, or not present in, our previous work. One finding that stands out is that the estimated elasticity of the value of time with respect to GDP per capita is 0.9 and highly significant, a much closer correspondence to the widely used convention of a unit income elasticity over time than we have previously obtained. The ratio between walk and wait time and in-vehicle time was found to be substantially lower than the commonly used value of two. We also found large and significant differences between the results from studies based on different types of Stated Preference survey presentation. Other important effects include variations by mode used, mode valued, travel purpose, attribute type and distance. It is envisaged that the results are of direct relevance in the British context, as inputs to appraisal or for benchmarking, whilst the methodological implications are of broader interest and the results, in terms of time equivalents and variations in values of time, can be transferred to other contexts.     

VTT or VTTS: a note on terminology for value of travel time work

Transportation - The value of travel time (VTT) can be said to be the most important number in transport economics, and its estimation has been the topic of extensive academic and applied work....     

The determinants of long distance travel in Great Britain

This study analyses of the determinants of long distance travel in Great Britain using data from the 1995-2006 National Travel Surveys (NTSs). The main objective is to determine the effects of socio-economic, demographic and geographic factors on long distance travel. The estimated models express the distance travelled for long distance journeys as a function of income, gender, age, employment status, household characteristics, area of residence, size of municipality, type of residence and length of time living in the area. A time trend is also included to capture common changes in long distance travel over time not included in the explanatory variables. Separate models are estimated for total travel, travel by each of four modes (car, rail, coach and air), travel by five purposes (business, commuting, leisure, holiday and visiting friends and relatives (VFRs)) and two journey lengths (<150 miles and 150+ miles one way), as well as the 35 mode-purpose-distance combinations.The results show that long distance travel is strongly related to income: air is most income-elastic, followed by rail, car and finally coach. This is the case for most journey purposes and distance bands. Notable is the substantial difference in income elasticities for rail for business/commuting as opposed to holiday/leisure/VFR. In addition, the income elasticity for coach travel is very low, and zero for the majority of purpose-distance bands, suggesting coach travel to be an inferior mode in comparison to car, rail and air. Regarding journey distance, we find that longer distance journeys are more income elastic than shorter journeys.For total long distance travel, the study indicates that women travel less than men, the elderly less than younger people, the employed and students more than others, those in one adult households more than those in larger households and those in households with children less than those without. Long distance travel is also lowest for individuals living in London and greatest for those in the South West, and increases as the size of the municipality declines.     

Aggregate expenditure elasticity for transport and communication in Australia

For the purpose of estimating Engel elasticity, one needs to find the best functional form among various alternatives. In this paper, a new function, which is called the double semi-log Engel function turns out to be the best functional form for the transport and communication items in Australia on the basis of the distance function (D²) criterion, and the non-nested hypothesis testing procedure. This function is then used to estimate total expenditure elasticity, and the percentage change in consumer demand due to changes in total expenditure and total expenditure inequalities; using the 1975–76 Household Expenditure Survey data. The results of the analyses demonstrate that transport and communication is a necessary item in Australia on the basis of two criteria, viz., its elasticity is not significantly greater than unity, and the percentage change in demand increases with a decrease of the total expenditure inequality [emphasised by Iyengar (I960)]. Policy implication of the analyses has also been discussed.     

Solving the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP): A model to explore the impacts of self-driving vehicles on urban mobility

Interest in vehicle automation has been growing in recent years, especially with the very visible Google car project. Although full automation is not yet a reality there has been significant research on the impacts of self-driving vehicles on traffic flows, mainly on interurban roads. However, little attention has been given to what could happen to urban mobility when all vehicles are automated. In this paper we propose a new method to study how replacing privately owned conventional vehicles with automated ones affects traffic delays and parking demand in a city. The model solves what we designate as the User Optimum Privately Owned Automated Vehicles Assignment Problem (UO-POAVAP), which dynamically assigns family trips in their automated vehicles in an urban road network from a user equilibrium perspective where, in equilibrium, households with similar trips should have similar transport costs. Automation allows a vehicle to travel without passengers to satisfy multiple household trips and, if needed, to park itself in any of the network nodes to benefit from lower parking charges. Nonetheless, the empty trips can also represent added congestion in the network. The model was applied to a case study based on the city of Delft, the Netherlands. Several experiments were done, comparing scenarios where parking policies and value of travel time (VTT) are changed. The model shows good equilibrium convergence with a small difference between the general costs of traveling for similar families. We were able to conclude that vehicle automation reduces generalized transport costs, satisfies more trips by car and is associated with increased traffic congestion because empty vehicles have to be relocated. It is possible for a city to charge for all street parking and create free central parking lots that will keep total transport costs the same, or reduce them. However, this will add to congestion as traffic competes to access those central nodes. In a scenario where a lower VTT is experienced by the travelers, because of the added comfort of vehicle automation, the car mode share increases. Nevertheless this may help to reduce traffic congestion because some vehicles will reroute to satisfy trips which previously were not cost efficient to be done by car. Placing the free parking in the outskirts is less attractive due to the extra kilometers but with a lower VTT the same private vehicle demand would be attended with the advantage of freeing space in the city center.     

Mining factors affecting taxi drivers’ incomes using GPS trajectories

Taxis provide essential transport services in urban areas. In the taxi industry, the income level remains a cause of concern for taxi drivers as well as regulators. Mining underlying factors affecting the income level will not only benefit the newcomers and low-income drivers but also assist in developing effective optimization algorithms for taxi operations. This paper intends to disclose the factors affecting incomes along with their quantitative influence by mining over 167 million GPS records from nearly 8000 taxis in Shanghai. We first identify a marked difference in drivers’ incomes and categorize drivers into three income levels accordingly. We next investigate the overall search-delivery process, thereby defining several factors that may affect the income level. We then develop a generalized multi-level ordered logit (GMOL) model to find the significant factors that influence incomes. Finally, we compute the elasticity for those significant factors and present their contributions, as well as challenge some preconceived ideas regarding how to earn high incomes.     

装配式管线等价弹性模量的计算方法研究

装配式管线用连接器连接,用胶圈密封。胶圈属于弹性元件,其长度短、弹性模量比钢管小5个数量级,但使用的数量较多,对整条管线弹性模量的影响不可忽略。文中提出将胶圈的弹性模量计入钢管弹性模量中,推导了等价弹性模量的计算公式,并用算例分析了密封胶圈对压力波速的影响。由于装配式管线的规格尺寸均已制式化,故得出的等价弹性模量值可在以后的设计计算中直接使用,方便快捷。     

A distribution-fitting-free approach to calculating travel time reliability ratio

Empirical studies have revealed that travel time variability (TTV) can significantly affect travelers’ behaviors and planners’ cost-benefit assessment of transportation projects. It is therefore important to systematically quantify the value of TTV (VTTV) and its impact. Recently, Fosgerau’s valuation method makes this quantification possible by converting the value of travel time (VTT) and the VTTV into monetary unit. Travel time reliability ratio (TTRR), defined as a ratio of the VTTV to the VTT, is a key parameter in Fosgerau’s valuation method. Calculating TTRR involves an integral of the inverse cumulative distribution function (CDF) of the standardized travel time distribution (STTD), i.e., the mean lateness factor. Using a well-fitted STTD is a straightforward way to calculate TTRR. However, it will encounter the following challenges: (1) determination of a well-fitted STTD; (2) non-existence of an algebraic expression for the CDF and its inverse CDF; and (3) lack of a closed-form expression to efficiently calculate TTRR. To circumvent the above issues, this paper proposes a distribution-fitting-free analytical approach based on the Cornish-Fisher expansion as an alternative way to calculate TTRR without the need to fit the whole CDF. The validity domain is rigorously derived for guaranteeing the accuracy of the proposed method. Realistic travel time datasets that cover 17 links are used to systematically explore the feature and accuracy of the proposed method in estimating TTRR. The comparative results demonstrate that the proposed method can efficiently and effectively estimate TTRR. When travel time datasets satisfy the validity domain, the proposed method outperforms the distribution fitting method in estimating TTRR.     

Asymmetry in transport fuel demand: Evidence from household level data

Models for gasoline demand for transportation activities generally assume that demand is perfectly reversible with respect to gasoline price (and income). The small literature which relaxes the reversibility assumption in gasoline demand argues technological fixation leads to this asymmetry and utilizes aggregate time-series model to find evidence in favour of asymmetry. In this research it is suggested that there could also be behavioural factors behind this asymmetric response, possibly due to the loss aversion nature of human beings as described in the prospect theory. For the first time, household level data was used to understand asymmetry in gasoline demand in response to changes in gasoline price and income. There was statistical evidence that gasoline price and income both can induce asymmetric changes in gasoline demand among households. Specifically, elasticity with respect to rising prices and falling income is larger than the elasticity with respect to falling prices and rising income respectively, which is consistent with loss aversion in gasoline purchase behaviour. There was also some evidence of heterogeneity in the asymmetric responses between urban and rural households. The results have implications for transport-related energy tax policies or subsidies, while the method can be applied directly for non-energy goods as well.     

Elasticities for taxicab fares and service availability

This study utilizes a unique dataset from New York City to examine the effects of taxi fare increases on trip demand and the availability of taxi service. The elasticity of trip demand with respect to fares is estimated to be –0.22; the elasticity of service availability with respect to the taxi fare is 0.28; and the elasticity of service availability with respect to total supply of service is near 1.0. These results have important implications for taxi regulatory decisions. First, fare increases do substantially increase industry revenues but at a lesser rate than the percentage increase in the fare. The implication for policy-makers is that fare elasticities must be carefully considered to obtain desired improvements in drivers' earnings. Second, service availability -- an important aspect of service quality that is generally overlooked during fare policy debates -- should be a central consideration in fare setting, given the considerable impact of fares on availability. Finally, where the supply of cabs needs to be expanded, the number of cabs can be significantly increased without harming the revenue stream of existing operators. This finding alleviates a major industry objection to issuing additional taxicab licenses.     

Petrol expenditure and redistributive effects of its taxation in Spain

The objective of this paper is to estimate a petrol expenditure function for Spain and to evaluate the redistributive effects of petrol taxation. We use micro data from the Spanish Household Budget Survey of 1990/91 and model petrol expenditure taking into account the effect that income changes may have on car ownership levels, as well as the differences that exist between reported expenditure and real consumption during the week of reference. Our results show the importance that household structure, place of residence and income have on petrol expenditure patterns. We are able to compute income elasticities of petrol expenditure, both conditional and unconditional on the level of car ownership. Non-conditional elasticities, while always very close to unit values, are lower for higher income households and for those living in rural areas or small cities. When car ownership levels are taken as fixed, the conditional elasticity obtained is around one half the value of the non-conditional ones. As regards the redistributive effects of petrol taxation, we observe that for the lowest income deciles the share of petrol expenditure increases with income, and thus the tax can be regarded as progressive. However, after a certain income level the tax proves to be regressive.     

An artificial neural network based method to uncover the value-of-travel-time distribution

Transportation - This study proposes a novel Artificial Neural Network (ANN) based method to derive the Value-of-Travel-Time (VTT) distribution. The strength of this method is that it is possible...     

Impact of fuel price on vehicle miles traveled (VMT): do the poor respond in the same way as the rich?

The effects of fuel price on travel demand for different income groups reveal the choices and constraints they are faced with. The first purpose of this study is to understand these underlying choices and constraints by examining the variation of fuel price elasticity of vehicle miles travelled (VMT) across income groups. On the other hand, the rebound effect—increase in VMT as a result of improvement in fuel efficiency may offset the negative effect of fuel price on VMT. The second purpose of this study is to compare the relative magnitudes of the fuel price elasticity of VMT and the rebound effect. A system of structural equations with VMT and fuel efficiency (MPG, miles per gallon) as endogenous variables is estimated for households at different income levels from 2009 National Household Travel Survey. Higher income households show greater fuel price elasticity than lower income households. Fuel price elasticities are found to be ?0.41 and ?0.35 for the two highest income groups, while an elasticity of ?0.24 for the lowest income group is identified. The rebound effect is found to be only significant for the lowest income households as 0.7. These findings suggest the potential ability of using fuel price as a tool to affect VMT. The study results also suggest possible negative consequences faced by lower income households given an increase in fuel price and call for more studies in this area.