Key factors influencing the global passenger transport dynamics using the AIM/transport model

A bottom-up passenger transport model named AIM (Asia-pacific Integrated Model)/Transport model is developed by incorporating behavioral parameters and transportation technological details. This model is based on discrete based choice modelling covering 17 global regions soft-linked with the AIM/CGE (Computable General Equilibrium) model. In this paper, the model is used to assess the impact of various factors like travel time, energy efficiency improvement, load factor, mode preference along with environmental awareness factors on transport demand, energy and emissions. The modelling assessment results show that travel speed and land-use patterns have significant impact on the travel demand. High occupancy rate and shift towards the mass-transit system result in energy and emissions reduction. Implementation of carbon tax aligned with the two-degree target results in a 22% cumulative emission reduction from 2005 to 2100 relative to the baseline case. However, the reduction potential can be increased to 42% by combining behavioral and technology related mitigation options like mass-transit system speed improvement, transit oriented development, efficiency improvement, preference towards eco-friendly technologies and high vehicle occupancy.     

Sustainability Assessment of Transport Infrastructure Projects: A Review of Existing Tools and Methods

Abstract

Attempts to integrate sustainability in the decision-making process for transport infrastructure projects continue to gain momentum. A number of tools and methodological frameworks are available — such as rating systems, traditional decision-making techniques, checklists, and different evaluation frameworks and models. While these tools are highly valuable, some practical issues remain unsolved. There is also a need for more standardized tools to appraise the sustainability of transport projects. This paper is a presentation of a review on the current assessment tools of sustainability applied to transport infrastructure projects. The preliminary part of the paper is an explanatory and comparative analysis of the tools and methods in terms of their effectiveness to appraise sustainability. The analysis is a critical evaluation of the current state of the art to identify the limitations of existing approaches, point out new areas of research, and propose a sustainability appraisal agenda for the future.     

Evolving Narratives of Low-Carbon Futures in Transportation

Scenarios of low-carbon transport demonstrate that a vast range of different outcomes is possible and contingent on policy, technology and cultural developments. But a closer look indicates that different schools of thought suggest possible pathways diverging in their fine structure. This perspective reveals how three different scientific communities — integrated assessment modelers, transport-sector modelers, and place-based modelers — emphasize distinct solution domains. While integrated assessment models focus on fuel composition, transport-sector models put slightly higher emphasis on efficiency measures; in turn place-based research specifies idiosyncratic behavioral and infrastructural mitigation options that are likely to be beneficial in realizing local co-benefits. These specific local approaches could mitigate urban transport emissions by 20–50%, higher than that revealed in aggregate global models. We discuss differences in approach, possibilities for reconciliation, and the implications of normative assumptions. Targeted three-directional interactions would foster comprehensive understanding of possible low-carbon transportation futures.     

Economic resilience to transportation failure: a computable general equilibrium analysis

This study develops and applies a multimodal computable general equilibrium (CGE) framework to investigate the role of resilience in the economic consequences of transportation system failures. Vulnerability and economic resilience of different modes of transportation infrastructure, including air, road, rail, water and local transit, are assessed using a CGE model that incorporates various resilience tactics including modal substitution, trip conservation, excess capacity, relocation/rerouting, and service recapture. The linkages between accessibility, vulnerability, and resilience are analyzed. The model is applied to the transportation system failures in the aftermath of Hurricane Katrina to illustrate its capabilities. The analytical framework, however, has broader applications and can provide insights for resource allocations to enhance emergent responses to unexpected events and to improve resilient design of transportation infrastructure systems.     

Urban activity pattern classification using topic models from online geo-location data

Location-based check-in services in various social media applications have enabled individuals to share their activity-related choices providing a new source of human activity data. Although geo-location data has the potential to infer multi-day patterns of individual activities, appropriate methodological approaches are needed. This paper presents a technique to analyze large-scale geo-location data from social media to infer individual activity patterns. A data-driven modeling approach, based on topic modeling, is proposed to classify patterns in individual activity choices. The model provides an activity generation mechanism which when combined with the data from traditional surveys is potentially a useful component of an activity-travel simulator. Using the model, aggregate patterns of users’ weekly activities are extracted from the data. The model is extended to also find user-specific activity patterns. We extend the model to account for missing activities (a major limitation of social media data) and demonstrate how information from activity-based diaries can be complemented with longitudinal geo-location information. This work provides foundational tools that can be used when geo-location data is available to predict disaggregate activity patterns.     

Interactive travel choices and traffic forecast in a doubly dynamical system with user inertia and information provision

This study models the joint evolution (over calendar time) of travelers’ departure time and mode choices, and the resulting traffic dynamics in a bi-modal transportation system. Specifically, we consider that, when adjusting their departure time and mode choices, travelers can learn from their past travel experiences as well as the traffic forecasts offered by the smart transport information provider/agency. At the same time, the transport agency can learn from historical data in updating traffic forecast from day to day. In other words, this study explicitly models and analyzes the dynamic interactions between transport users and traffic information provider. Besides, the impact of user inertia is taken into account in modeling the traffic dynamics. When exploring the convergence of the proposed model to the dynamic bi-modal commuting equilibrium, we find that appropriate traffic forecast can help the system converge to the user equilibrium. It is also found that user inertia might slow down the convergence speed of the day-to-day evolution model. Extensive sensitivity analysis is conducted to account for the impacts of inaccurate parameters adopted by the transport agency.     

Incorporating Driver Behaviors in Network Design Problems: Challenges and Opportunities

The goal of a network design problem (NDP) is to make optimal decisions to achieve a certain objective such as minimizing total travel time or maximizing tolls collected in the network. A critical component to NDP is how travelers make their route choices. Researchers in transportation have adopted human decision theories to describe more accurate route choice behaviors. In this paper, we review the NDP with various route choice models: the random utility model (RUM), random regret-minimization (RRM) model, bounded rationality (BR), cumulative prospect theory (CPT), the fuzzy logic model (FLM) and dynamic learning models. Moreover, we identify challenges in applying behavioral route choice models to NDP and opportunities for future research.     

A set-covering model for a bidirectional multi-shift full truckload vehicle routing problem

This paper introduces a bidirectional multi-shift full truckload transportation problem with operation dependent service times. The problem is different from the previous container transport problems and the existing approaches for container transport problems and vehicle routing pickup and delivery are either not suitable or inefficient. In this paper, a set covering model is developed for the problem based on a novel route representation and a container-flow mapping. It was demonstrated that the model can be applied to solve real-life, medium sized instances of the container transport problem at a large international port. A lower bound of the problem is also obtained by relaxing the time window constraints to the nearest shifts and transforming the problem into a service network design problem. Implications and managerial insights of the results by the lower bound results are also provided.     

Promoting Cycling for Transport: Research Needs and Challenges

Abstract

Near future travel-time information is one of the most critical factors that travellers consider before making trip decisions. In efforts to provide more reliable future travel-time estimations, transportation engineers have examined various techniques developed in the last three decades. However, there have not been sufficiently systematic and through reviews so far. In order to effectively support various transportation strategies and applications including Intelligent Transportation Systems (ITS), it is necessary to apply appropriate forecasting methods for matching circumstances in a timely manner. This paper conducts a comprehensive review study focusing on literatures, including modern techniques proposed recently, related to travel time and traffic condition predictions that are based on ‘data-driven' approaches. Based on the underlying mechanisms and theoretical principles, different approaches are categorized as parametric (linear regression and time series) and non-parametric approaches (artificial intelligence and pattern searching). Then, the approaches are analysed for their strengths, potential weaknesses, and performances from five main perspectives that are prediction range, accuracy, efficiency, applicability, and robustness.     

Is equilibrium in transport pure Nash,mixed or Stochastic?

The classical theory of transport equilibrium is based on the Wardrop’s first principle that describes a Nash User Equilibrium (UE), where in no driver can unilaterally change routes to improve his/her travel times. A growing number of economic laboratory experiments aiming at testing Nash-Wardrop equilibrium have shown that the Pure Strategy Nash Equilibrium (PSNE) is not able to explain the observed strategic choices well. In addition even though Mixed Strategy Nash Equilibrium (MSNE) has been found to fit better the observed aggregate choices, it does not explain the variance in choices well. This study analyses choices made by users in three different experiments involving strategic interactions in endogenous congestion to evaluate equilibrium prediction. We compare the predictions of the PSNE, MSNE and Stochastic User Equilibrium (SUE). In SUE, the observed variations in choices are assumed to be due to perception errors. The study proposes a method to iteratively estimate SUE models on choice data with strategic interactions. Among the three sets of experimental data the SUE approach was found to accurately predict the average choices, as well as the variances in choices. The fact that the SUE model was found to accurately predict variances in choices, suggests its applicability for transport equilibrium models that attempt to evaluate reliability in transportation systems. This finding is fundamental in the effort to determining a behaviourally consistent paradigm to model equilibrium in transport networks. The study also finds that Fechner error which is the inverse of the scale parameter in the SUE model is affected by the group sizes and the complexity of the cost function. In fact, the larger group sizes and complexity of cost functions increased the variability in choices. Finally, from an experimental design standpoint we show that it is not possible to estimate a noise parameter associate to Fechner error in the case when the choices are equally probable.     

What cognitive mechanisms predict travel mode choice? A systematic review with meta-analysis

Reduced private car use can limit greenhouse gas emissions and improve public health. It is unclear, however, how promotion of alternative transport choices can be optimised. A systematic review and meta-analysis was conducted to identify potentially modifiable cognitive mechanisms that have been related to car use and use of alternative transport modes. A qualitative synthesis of measures of potentially modifiable mechanisms based on 43 studies yielded 26 conceptually distinct mechanism categories. Meta-analyses of associations between these mechanisms and car use/non-use generated 205 effects sizes (Pearson’s r) from 35 studies. The strongest correlates of car use were intentions, perceived behavioural control, attitudes and habit. The strongest correlates of alternative transportation choices were intentions, perceived behavioural control and attitudes. Implications for researchers and policy implementation are discussed.     

Symbolic transport choice across national cultures: theoretical considerations for research design

A recently empirically isolated latent variable in transport choice is symbolism, which examines what people believe their transport choices say to others about them and how they are judged in a social context. Whilst it is well established that symbolism differs vertically across different socio-economic groups within a country, very little work has been done on how symbolism in transport may differ between similar individuals across nations as a function of national cultural values, and how this may manifest itself in transport choices. If significant differences were to be found then this could have impacts for transport policy formulation and transfer. This paper explores and discusses these issues and concludes that the initial goal of any research into symbolic transport choices across cultures is theoretical fertility, and this is best achieved by adopting Lakatosian research programmes, using theory-driven thematic analysis to develop theoretical models for testing.     

Free public transport: A socio-cognitive analysis

In this study, the modal shift potential of introducing a free alternative (free public transportation) and of changing the relative prices of transportation is examined. The influence of a cognitive analysis on the zero-price effect is also analyzed. The data used for the analysis stem from a stated preference survey with a sample of approximately 670 respondents that was conducted in Flanders, Belgium. The data are analyzed using a mixed logit model. The modeling results yield findings that confirm the existence of a zero-price effect in transport, which is in line with the literature. This zero-price effect is increased by the forced cognitive analysis for shopping trips, although not for work/school or recreational trips. The results also demonstrate the importance of the current mode choice in hypothetical mode choices and the importance of car availability. The influence of changing relative prices on the modal shift is found to be insignificant. This might be partially because the price differences were too small to matter. Hence, an increase in public transport use can be facilitated by the introduction of free public transport, particularly when individuals evaluate the different alternatives in a more cognitive manner. These findings should be useful to policy makers evaluating free public transport and considering how best to target and promote relevant policy.     

Statistical models of discrete choice processes

A number of problems studied in the transportation literature, such as automobile choice, motorist route choice, and transportation mode choice, involve an agent who makes a series of discrete choices over time. This paper presents statistical models and estimation methods for such discrete choice processes, and illustrates potential applications of these methods to the transportation literature.     

A methodological approach for developing and assessing business models for flexible transport systems

Flexible transport services include a wide range of demand responsive transport systems that provide non-conventional passenger and freight transportation services. Several alternative business models varying according to the local market conditions, the socio-economic, legal, and institutional framework may be developed for the provision of Flexible Transport Systems (FTS). The objective of this paper is twofold: first to present an integrated methodological framework for developing and assessing alternative FTS business models and second to demonstrate its applicability to a case study regarding the prioritization of alternative FTS business models for the provision of flexible passenger transport services in Helsinki.

Land Transport Policy and Public Transport in Singapore

Singapore has a sophisticated and efficient system of land transport to serve a growing demand for transportation. Constrained by limited space, a comprehensive set of land transport policies has been in place to balance the growth in transport demand and the effectiveness and efficiency of the land transport system. A multi-pronged approach has been used to achieve the objective of a world-class transportation system. These include integration of urban and transport planning, expansion of the road network and improvement of the transport infrastructure, harnessing the latest technology in network and traffic management, managing vehicle ownership and usage, and improvement and regulations of public transport (Ministry of Transport (MOT) (2003) Policy and Regulations, Land Transport, Available: www.mot.gov.sg, Date of Access: 15 September 2003). Singapore was the first country in the world to introduce various new techniques, notably the Area License Scheme (ALS) in 1975 and the Vehicle Quota System (VQS) in 1990. An Electronic Road Pricing (ERP) system replaced the ALS in 1998 to take the role of congestion management, the experience of which has also drawn particular attention from many large cities in the world. In 2003, the world’s first and only fully automatic heavy rail Mass Rapid Transit system was opened to the public, marking a new chapter in Singapore’s innovative approach to solving its land transport problem. This paper reviews the land transport policy implemented in Singapore and pays special emphasis to its public transportation systems.     

Approaches and Techniques for Modelling CO2 Emissions from Road Transport

Abstract

Transport accounts for around a quarter of CO₂ emissions globally. Transport modelling provides a useful means to explore the dynamics, scale and magnitude of transport-related emissions. This paper explores the modelling tools available for analysing the emissions of CO₂ from transport. Covering a range of techniques from transport microsimulation to global techno-economic models, this review provides insights into the various advantages and shortcomings of these tools. The paper also examines the value of having a broad range of perspectives for analysing emissions from transport. The paper concludes by suggesting that the broad range of models creates a rich environment for exploring a spectrum of policy questions around the emissions from transport, and the potential for combining modelling approaches further enhances the understanding that can be attained.     

Performance evaluation and obstacle factors analysis of urban public transport priority

ABSTRACT

Through the comprehensive consideration of four subsystems – overall development level, infrastructure construction, public transportation service level and policy support – an index system of public transport priority performance evaluation is established. A performance evaluation of bus priority implementation in Wuhan City from 2007 to 2016 is carried out by applying the difference coefficient CRITIC-TOPSIS model. The obstacle factor model is also used to diagnose the factors affecting the priority performance of urban public transport. The research results show that, during this decade, the comprehensive performance of Wuhan City’s public transport priority developed from poor to medium, then to good and finally to excellent. The overall development level and infrastructure construction performance subsystems have the highest obstacle degree, followed by public transportation service levels and policy support performance subsystems. The research idea and method of this paper provide a realistic basis for promoting the priority performance of urban public transport.     

Capturing correlation with a mixed recursive logit model for activity-travel scheduling

Representing activity-travel scheduling decisions as path choices in a time–space network is an emerging approach in the literature. In this paper, we model choices of activity, location, timing and transport mode using such an approach and seek to estimate utility parameters of recursive logit models. Relaxing the independence from irrelevant alternatives (IIA) property of the logit model in this setting raises a number of challenges. First, overlap in the network may not fully characterize perceptual correlation between paths, due to their interpretation as activity schedules. Second, the large number of states that are needed to represent all possible locations, times and activity combinations imposes major computational challenges to estimate the model. We combine recent methodological developments to build on previous work by Blom Västberg et al. (2016) and allow to model complex and realistic correlation patterns in this type of network. We use sampled choices sets in order to estimate a mixed recursive logit model in reasonable time for large-scale, dense time-space networks. Importantly, the model retains the advantage of fast predictions without sampling choice sets. In addition to estimation results, we present an extensive empirical analysis which highlights the different substitution patterns when the IIA property is relaxed, and a cross-validation study which confirms improved out-of-sample fit.     

Prospect Theory for joint time and money consequences in risk and ambiguity

Transport users face complex decisions. Not only are the consequences of their choices uncertain, but they generally involve several attributes, such as time and money. Time-money tradeoffs have been studied in depth in transport economics, and research is now paying increasing attention to the role of uncertainty and information in transport decisions. This paper aims to measure the impact of uncertainty and information on multi-attribute decisions using Prospect Theory. In doing so, the study makes two contributions to transportation literature: one methodological and the other empirical. First, we propose a fast and tractable method for measuring Prospect Theory parameters that capture attitudes towards probabilities (probability weighting function) and attitudes towards losses (loss aversion). The elicitation method does not require the elicitation of the utility function. This makes it particularly suitable in complex multi-attribute decisions where the shape of the utility function is unknown. Second, we present the results of an experiment that uses the proposed method to measure, at the individual level, probability weighting in decisions involving joint time and money consequences in two decision contexts: risk (where probabilities are given) and ambiguity (where the probability distribution is unknown). An experimental setup that exposes subjects to real gains and losses for money and time has been built for this purpose. We observe inverse S-shaped probability weighting and loss aversion for risk. Probability weighting is even more pronounced in ambiguity, where subjects do not have precise information about the probability distribution. We explain how these results and the analysis of ambiguity attitudes in general can offer a better understanding of travelers’ route or transport mode choices.