Urban Transportation Mode Choice and Trip Complexity: Bicyclists Stick to Their Gears

Preferences of public transit commuters: Evidence from smart card data in Singapore

The purpose of this study is to identify the characteristics of freight mode choices made by shippers and carriers with the introduction of a new freight transport system. We set an area in which actual freight transport takes place as the analysis scope and performed a survey of the shippers and carriers that transport containers to identify their stated preference (SP) regarding the new freight mode. The SP survey was carried out through an experimental design and this study considered the three factors of transport time, transport cost, and service level. This study compared and analyzed the models by distance using an individual behavior model. The results of estimating the model showed that the explanatory power of the model classified by distance and the individual parameters have statistical significance. The hit ratio was also high, which confirms that the model was estimated properly. In addition, the range of elasticity and the value of travel time analyzed using the model were evaluated to be appropriate compared to previous studies. The findings of the elasticity analysis show that strategies for reducing the transport cost are effective to increase the demand for the new transport mode. The value of travel time of freight transport was found to be higher than the current value generally applied in Korea. Considering that the value of travel time currently used is based on road freight transport, further research is required to apply a new value of travel time that reflects the characteristics of the new transport mode in the future.

Between-mode-differences in the value of travel time: Self-selection or strategic behaviour?

It is often found that the value of travel time (VTT) is higher for car drivers than for public transport passengers. This paper examines the possible explanation that the difference could be due to a selection effect. The result is an inability to measure the effect of a mode difference, e.g., comfort, among transport modes. We specify a model that captures the mode difference through a mode dummy and use econometric techniques that allow treatment of the mode dummy as the result of an individual choice and hence endogenous. Using first a standard logit model we find a large and significant difference between the VTT for bus and car. When we control for endogeneity using instruments, the mode dummy becomes smaller and just significant. Our investigation is novel in that it allows for endogeneity in the estimation of VTT but like other applications using instruments the results indicate that we have difficulty in finding good instrumental variables.

Value of travel time and travel time reliability

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

Over the years, researchers have been studying the effects of weather and context data on transport mode choices. Existing research studies are predominantly designed around travel surveys, but the accuracy of their findings relies on how travelers give accurate and honest answers. The proliferation of smartphones, however, now offers the possibility of utilizing GPS positioning data as an alternative information source, opening the potential to accurately model and better understand factors which influence transport mode choices, compared to travel surveys. The objective of this work is to develop a model to predict the transport mode choices based on GPS trajectories, weather and context data. We use 2671 GPS trajectories from the Geolife GPS trajectories dataset, weather data, such as temperature and air quality, and context data, such as rush hour, day/night time and onetime events, such as the Olympics. In the statistical analysis, we apply both descriptive and statistical models, such as the multinomial logit and probit models. We find that temperature has the most prominent effect among weather conditions. For instance, for temperatures greater than 25 °C, the walking share increases by 27%, and the bike share reduces by 21%, which is line with the results from several survey-based studies. In addition, the evidence of government policy on transport regulation is revealed when the air quality becomes hazardous, as people are encouraged to use environmentally friendly transport mode choices, such as the bike instead of the bus or car, which are known CO2 emitters. Our conclusion is that GPS trajectories can be used as a means to model passenger behavior, e.g. the choice of transport mode, in a quantitative way, which will support transport mode operators and policy makers in their efforts to design and plan the transport mode infrastructure to best suit the passengers’ needs.

Modelling life trajectories and mode choice using Bayesian belief networks

On the impact of vehicle automation on the value of travel time while performing work and leisure activities in a car: Theoretical insights and results from a stated preference survey

U.S. transportation agencies have invested more than $300 million in dynamic message sign (DMS) systems for communicating important messages to travelers, including weather conditions, incidents, construction, and homeland security and AMBER alerts. Recent FHWA policy encourages states to use their DMS infrastructure more effectively by displaying reliable travel-time information along freeway corridors. The Oregon Department of Transportation (ODOT), which maintains a freeway surveillance system in the Portland metropolitan area, calculates and reports travel-time estimates derived from inductive loop detector data. These estimates can be reported via 18 DMS and other traveler information systems but are displayed on a limited basis at key junction points during peak periods. Results are presented of an evaluation of ODOT's travel-time reporting capabilities by comparing the ODOT travel-time estimates with probe vehicle (ground truth) travel times. The freeway network was divided into 17 key corridors, and 87 probe vehicle runs were collected under various traffic conditions with handheld Global Positioning System devices. This evaluation used the regional transportation data archive, Portland Regional Transportation Archive Listing, to generate the ODOT travel-time estimates. Probe estimates were compared to travel estimates on the corridors with a paired t-test. The evaluation found that travel times on a majority of links were reasonably accurate under most traffic conditions but were affected by the presence of an incident or by poor detector placement.

This paper studies intertemporal changes in the value of travel time (VTT) and investigates whether the change of VTT over time can be studied based on national VTT data, collected at two points in time. We use repeated national VTT data from the Netherlands and Sweden, collected 13 and 14 years apart. The results show mostly a declining VTT for a given income level. The results show also a large within-country heterogeneity across modes and purposes, in the cross-sectional income elasticity of the VTT, and in its development over time. The explanation most consistent with our results and those of others is that the VTT has in fact increased due to income increases, but that the repeated stated choice data cannot detect this given the data, methodology and population changes. In particular, it seems that the response rate has dropped considerably in the later surveys partly due to a higher share of (busy) respondents declining to be recruited. The main contribution of this paper is to document the differences between the studies carried out in different years, indicating the reasons why it is difficult to identify temporal changes in the VTT.

Due to an increasingly competitive market, transportation mode of petroleum products is usually considered as one of the major bottlenecks in the supply chain of white petroleum. Liberalization of the petroleum industry saw an end to Kenya Pipeline Companys (KPC) monopoly in transportation of white petroleum fuels in the country. As a result, oil marketing companies (OMCs) are free to choose preferred modes of transportation, which can either be pipeline, rail or road. This study establishes the choice of transportation mode for white petroleum by OMCs in Nairobi, Kenya by looking at determinants such as company profile, time, quality, safety and storage facilities, as well as the influence of these on the choice of transportation mode. This was a descriptive research design conducted among oil marketers in Kenya. Kenya has about 58 oil-marketing companies that participate in the importation of white petroleum products and the study covered 50% of the total OMCs in Nairobi. Data collected was purely quantitative and it was analyzed by descriptive analysis. The data was analyzed using statistical package for social sciences (SPSS) version 18 and Microsoft Excel to generate quantitative reports through tabulations, percentages, and measures of central tendency. The study found out that cost of service, quality of petroleum products delivered and environmental factors on health, safety and security are the key determinants of choice of transportation mode of white petroleum products by OMCs in Nairobi. The study also found out that the company profile of the OMCs does not influence their choice of transportation mode, while turnaround time is an important factor but considered alongside other factors when determining the choice of transportation mode of white petroleum as it is considered alongside other factors.

This paper considers logistics decision support system which deals with transportation mode selection considering transportation and carbon emission cost. Transportation and carbon emission costs vary with the choice of transportation modes and to become competitive companies need to find proper transportation modes for their logistics services. However, due to the restricted capacity of transportation modes, it is difficult to balance transportation and carbon emission costs when designing logistics network including transportation mode choice for each service. Therefore this paper aims to analyze the trade-off relationship between transportation and carbon emission cost in mode selection of intermodal transportation and to provide optimal green logistics strategy. In this paper, the logistics decision support system is designed based on mixed integer programming model. To understand the trade-off relationship of transportation and carbon emission cost, the system is tested with various scenarios including transportation of containers between Seoul and Busan. The analysis results show that, even though sea transportation combined with trucking is competitive in carbon emission per unit distance travelled, the total cost of carbon emission and transportation for the sea transportation may not have competitive advantage over other transportation modes including rail and truck transportation modes. The sea-based intermodal logistics service may induce detours which have negative impacts on the overall carbon emission. The proposed logistics decision support system is expected to play key role in green logistics and supply chain management.

The use of E-moped increases commute satisfaction and subjective well-being: Evidence from Shanghai, China

A prerequisite for any monetary estimation of economic losses arising from traffic congestion is a reliable estimate of the value of travel time. Although the available evidence from abroad reveals significant differences in the values of individual components of time travel, specific valuations of travel time are rather rare in the Czech Republic. The aim of this paper is to expand the data base in the Czech Republic by presenting selected estimates of the travel time components for Czech drivers and passengers. Specifically, we elaborate on the value of travel time and time spent in congestion for medium-long domestic routes (represented by the Prague-Brno route). The results of our valuation study (N = 602) show that the value of travel time spent in congestion is almost twice as high as the value of travel time in free-flow traffic and suggest that the reduction of congestion and of the variation in travel time in general will bring significant economic benefits compared to shortening travel time in free-flow traffic. This evidence confirms the importance of distinguishing between different components of travel time when assessing the benefits of transport infrastructures. Importantly, our estimates of the value of travel time are much lower than those officially endorsed by Czech Ministry of Transport (MoT) for analysing benefits of new transport infrastructure.