Users’ perceptions and willingness to pay in interurban toll roads: identifying differences across regions from a nationwide survey in Spain

Users’ acceptability is considered one of the key drivers for the successful implementation of transport policy measures. This is especially crucial in the case of toll roads since they are financed through drivers’ contributions. Previous literature in this field has mainly focused on measuring users’ attitudes towards urban congestion pricing strategies. However limited research has been developed concerning interurban toll roads. Previous research shows that socioeconomic variables are not conclusive to explain users’ perceptions towards tolls. By contrast, other drivers such as regional differences seem to play a more important role, especially when charging conditions within the same nation greatly vary across regions. This paper analyzes regional differences in users’ attitudes within an asymmetrical distribution of the toll road network across regions. Based on a nationwide survey conducted to road users in interurban toll roads in Spain, we develop both a binomial logit and a censored regression (tobit) model to explore drivers’ perceptions and willingness to pay. The research concludes that users from regions with a more extensive tolled network generally show a more negative attitude towards charges, but not necessarily a lower willingness to pay. The paper also points out that an asymmetrical distribution of toll roads across regions may result in negative perceptions among those users perceiving to be unfairly treated when compared to citizens in other regions.     

An activity-based approach of investigating travel behaviour of older people

The paper presents the results of an investigation on daily activity-travel scheduling behaviour of older people by using an advanced econometric model and a household travel survey, collected in the National Capital Region (NCR) of Canada in 2011. The activity-travel scheduling model considers a dynamic time–space constrained scheduling process. The key contribution of the paper is to reveal daily activity-travel scheduling behaviour through a comprehensive econometric framework. The resulting empirical model reveals many behavioural details. These include the role that income plays in moderating out-of-home time expenditure choices of older people. Older people in the highest and lowest income categories tend to have lower variations in time expenditure choices than those in middle-income categories. Overall, the time expenditure choices become more stable with increasing age, indicating that longer activity durations and lower activity frequency become more prevalent with increasing age. Daily activity type and location choices reveal a clear random utility-maximizing rational behaviour of older people. It is clear that increasing spatial accessibility to various activity locations is a crucial factor in defining daily out-of-home activity participation of older people. It is also clear that the diversity of out-of-home activity type choices reduces with increasing age and older people are more sensitive to auto travel time than to transit or non-motorized travel time.     

Bicycle mode share in China: a city-level analysis of long term trends

In the past 15 years, cities in China have experienced big changes in socioeconomic and traffic conditions, resulting in a long term change in bicycle use. This study aims to quantify the changes in bicycle mode share in Chinese cities and explore the potential causes. Based on data from 51 cities, it is found that bicycle mode share at the city level decreased gradually in the past. Conventional bicycle mode share decreased with a rate of 3 % per year, but electric bicycle mode share increased with a rate of 2 % per year. The correlations between city features such as demographics and built environments and bicycle mode share at different city sizes are compared. The generalized linear models are estimated to relate the changes in the share of different trip modes to various city-level factors. The results show that the bicycle mode share in a city is impacted by factors including city area size, population density, number of cars, percentage of local road mileage among all roads, and trip purpose. Possible reasons for the changes in bicycle uses in Chinese cities are explored and policy implications are discussed.     

Cost and time damping: evidence from aggregate rail direct demand models

There is a significant body of evidence from both disaggregate choice modelling literature and practical travel demand forecasting that the responsiveness to cost and possibly to time diminishes with journey length. This has, in Britain at least, been termed ‘Cost Damping’, and is recognised in guidance issued by the UK Department for Transport. However, the consistency of the effect across modes and data types has not been established. Cost damping, if it exists, affects both the forecasting of demand and our understanding of behaviour. This paper aims to investigate the evidence for cost and time damping in rail demand using aggregate rail ticket sales data. The rail ticket sales data in Britain has, for many years, formed the basis of analysis of a wide range of impacts of rail demand. It records the number of tickets sold between station pairs, and it is generally felt to provide a reasonably accurate reflection of travel demand. However, the consistency of these direct demand models with choice modelling and highway demand model structures has not been investigated. Rail direct demand models estimated by ticket sales data indicate only slight variation in the fare elasticity with distance, as is evidenced in the largest meta-analysis of price elasticities conducted to date (Wardman in J Transp Econ Policy 48(3):367–384, 2014). This study of UK elasticities shows strong variation between urban and inter-urban trips, presumably a segmentation at least in part by purpose, but less remaining variation by trip length. A lack of variation by length supports the hypothesis of cost damping, because constant cost sensitivity would imply that fare elasticity would increase strongly with distance, because of the increasing impact of higher fares at longer distances. In this paper we indicate that rail direct demand models have some consistency of behavioural paradigm with utility based choice models used in highway planning. We go on to use rail demand data to estimate time and fare elasticities in the context of various cost damping functions. Our empirical contribution is to estimate time elasticities on a basis directly comparable with cost elasticities and to show that the phenomenon of cost damping is strongly present in ticket sales data. This finding implies that cost damping should be included in models intended for multimodal analysis, which may otherwise give incorrect predictions.     

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.     

Non-local simulation of the stable boundary layer with a third order moments closure model

A new higher order closure model for the stable boundary layer is presented and compared with Large Eddy Simulation data. The model includes numerical solutions for the mean values, second and third order moments equations. A satisfactory agreement is found between the calculated vertical profiles of the turbulent quantities with those provided by the LES. Furthermore the new model results are compared with profiles obtained with a lower order closure model in order to verify the effective importance of including third order dynamical equations in the model.     

An algorithm for oceanic front detection in chlorophyll and SST satellite imagery

An algorithm is described for oceanic front detection in chlorophyll (Chl) and sea surface temperature (SST) satellite imagery. The algorithm is based on a gradient approach: the main novelty is a shape-preserving, scale-sensitive, contextual median filter applied selectively and iteratively until convergence. This filter has been developed specifically for Chl since these fields have spatial patterns such as chlorophyll enhancement at thermohaline fronts and small- and meso-scale chlorophyll blooms that are not present in SST fields. Linear Chl enhancements and localized (point-wise) blooms are modeled as ridges and peaks respectively, whereas conventional fronts in Chl and SST fields are modeled as steps or ramps. Examples are presented of the algorithm performance using modeled (synthetic) images as well as synoptic Chl and SST imagery. After testing, the algorithm was used on > 6000 synoptic images, 1999–2007, to produce climatologies of Chl and SST fronts off the U.S. Northeast.     

On the numerical accuracy of the prediction of resistance coefficients in ship stern flow calculations

This article presents a study on the accuracy of the numerical determination of the friction and pressure resistance coefficients of ship hulls. The investigation was carried out for the KVLCC2 tanker at model- and full-scale Reynolds numbers. Gravity waves were neglected, i.e., we adopted the so-called double-model flow. Single-block grids with H–O topology were adopted for all the calculations. Three eddy viscosity models were employed: the one-equation eddy viscosity and the two-equation models proposed by Menter and the TNT version of the two-equation k-ω model. Verification exercises were performed in sets of nearly geometrically similar grids with different densities in the streamwise, normal, and girthwise directions. The friction and pressure resistance coefficients were calculated for different levels of the iterative error and for computational domains of different size. The results show that on the level of grid refinement used, it is possible to calculate the viscous resistance coefficients in H–O grids that do not match the ship contour with a numerical uncertainty of less than 1%. The differences between the predictions of different turbulence models were larger than the numerical uncertainty; however, these differences tended to decrease with increases in the Reynolds number. The pressure resistance was remarkably sensitive to domain size and far-field boundary conditions. Either a large domain or the application of a viscous–inviscid interaction procedure is needed for reliable results. This work was presented in part at the International Conference on Computational Methods in Marine Engineering—MARINE 2007, Barcelona, June 3–4, 2007.     

Workspace analysis to generate a collision-free torch path for a ship welding robot

We propose a method to determine the optimal initial location and to generate torch paths for a ship welding robot with 6 degrees of freedom (DOF). The optimal initial location is determined using an objective function, which is set up by combining constraints on the torch posture, manipulability, and the range of each joint angle to avoid collisions. A genetic algorithm (GA) is used to optimize the objective function because it does not require additional derivatives. After the initial location is determined, torch paths are generated by interpolating the starting point, endpoints and torch postures using inverse kinematics. Our method can be applied to automate the welding job for each block during ship building, irrespective of the shape of the robots, by changing the objective function.     

Coastal Tourist Interest in Value-Added,Aquaculture-Based,Culinary Tourism Opportunities

Despite increasing focus on sustainable aquaculture investment in the U.S. coastal zones, the aquaculture industry continues to face skepticism among consumers due to perceived negative environmental impacts, and health and food safety concerns. Partnering with culinary tourism and local food promotion efforts has potential for improving public outreach about the benefits of aquaculture, especially in coastal destinations where sustainable marine aquaculture and tourism are both occurring. Culinary tourism implies that local foods reflect the local livelihood and culture, and may be important to the tourist's experience. Aquaculture is becoming increasingly valuable to coastal destinations for assuring the steady availability of local seafood to meet demand and retaining commercial fisheries as a means to differentiate themselves to tourists. This study examined the role of subjective knowledge and attitude about aquaculture, and their effect on intention to participate in value-added culinary aquaculture tourism experiences. The study found that tourists' subjective knowledge and attitude about aquaculture influenced intentions to participate in culinary aquaculture tourism. In order for farmers or tour operators to be successful in diversifying with value-added culinary aquaculture, attention needs to be paid to educating consumers, which may be possible through strategic partnerships with tourism organizations, chefs, and restaurants.