Tradable credits for managing car travel: a review of empirical research and relevant behavioural approaches

Recently, there has been a surge of interest in Tradable Credits (TC) as an alternative measure to manage the growth of personal car use. This paper summarises the results and methodologies of studies that have sought to anticipate the behavioural responses to several proposed TC schemes that target personal travel. In a critical reflection on this work and in an attempt to inspire future research, we argue that future empirical studies on TC behaviours can greatly benefit from insights from the fields of behavioural economics and cognitive psychology. Therefore, in the second part of the paper, we bring together behavioural concepts from these fields that are relevant in a TC decision-making context. Based on observations from current TC studies and the behavioural mechanisms identified in the second part of the paper, we propose promising directions for future research on understanding the impact of TC on personal car travel.     

Bike route choice modeling using GPS data without choice sets of paths

Concerned by the nuisances of motorized travel on urban life, policy makers are faced with the challenge of making cycling a more attractive alternative for everyday transportation. Route choice models can help achieve this objective by gaining insights into the trade-offs cyclists make when choosing their routes and by allowing the effect of infrastructure improvements to be analyzed. We estimate a link-based bike route choice model from a sample of GPS observations in the city of Eugene on a network comprising over 40,000 links. The so-called recursive logit (RL) model (Fosgerau et al., 2013) does not require to sample any choice set of paths. We show the advantages of this approach in the context of prediction by focusing on two applications of the model: link flows and accessibility measures. Compared to the path-based approach which requires to generate choice sets, the RL model proves to make significant gains in computational time and to avoid paradoxical accessibility measure results discussed in previous works, e.g. Nassir et al. (2014).     

Long-term impact of the Shinkansen on rail and air demand: analysis with data from Northeast Japan

This paper analyses how the high-speed rail construction in Northeast Japan (Tohoku) has affected total demand and interregional travel patterns. We use annual interregional passenger data from 1989 to 2012 and apply regression analysis with the demand between Tokyo and the Tohoku prefectures as the dependent variable. We distinguish particularly between the ‘Full-’ and the ‘Mini-’ Shinkansen, where the latter are branch services running with reduced speed. We find that the ‘Full-Shinkansen’ quickly increases rail and total public transport trips and generates additional rail demand year on year. The ‘Mini-Shinkansen’ impacts are less pronounced. Furthermore, our analysis shows that the Shinkansen has shifted some demand from air to rail once it started operation and increased rail share gradually. We therefore suggest that predictions of demand impacts should carefully distinguish immediate from gradual impacts. We also discuss differences in regional demand in that not all prefectures have gained equally from Shinkansen construction.     

Factors influencing travel mode choice among families with young children (aged 0–4): a review of the literature

Life events, such as the birth of a child, disrupt habitual travel behaviour and provide a valuable opportunity to influence the adoption of sustainable transport practices. However, in order for sustainable travel practices to be adopted, an understanding is required of the factors that influence travel mode choice among families with young children. Research in this field is particularly timely given many in the millennial generation, a comparably large cohort, are approaching this life stage. This comprehensive literature review develops a framework of factors influencing travel mode choice among families with young children. The findings reveal a multitude of factors influence decisions about mode choice, and, in particular, encourage travel by car, when travelling with young children. The paper concludes with an agenda for future research about travel among families with young children, a largely overlooked group of transport users.     

Experiment of boundedly rational route choice behavior and the model under satisficing rule

In this paper, we study the boundedly rational route choice behavior under the Simon’s satisficing rule. A laboratory experiment was carried out to verify the participants’ boundedly rational route choice behavior. By introducing the concept of aspiration level which is specific to each person, we develop a novel model of the problem in a parallel-link network and investigate the properties of the boundedly rational user equilibrium (BRUE) state. Conditions for ensuring the existence and uniqueness of the BRUE solution are derived. A solution method is proposed to find the unique BRUE state. Extensions to general networks are conducted. Numerical examples are presented to demonstrate the theoretical analyses.     

集装箱码头800M数字集群通信系统制式的选择

介绍了数字集群通信系统的特点,对数字集群系统两种制式作了比较。分析了集装箱码头对通信系统的要求和目前国内iDEN系统的运行状态。     

港口与运输方式及陆港联合选择的巢式Logit模型

为刻画托运人对港口、运输方式及陆港的联合选择行为,将港口费用、等待时间、班轮频率、货物价值、单次运量、运输成本、运输及通关时间、准班率、陆港服务作为效用变量,构建港口选择位于上层、运输方式及陆港选择位于下层的巢式Logit模型.基于辽宁部分城市集装箱托运人的RP/SP调查数据,对模型参数进行估计和检验.结果表明,低运量倾向选择公路运输,托运人对多式联运的运输成本、运输及通关时间比公路运输的更重视,对公路运输的准班率比多式联运的更重视,陆港服务对多式联运具有显著正向影响,巢式Logit模型比MNL模型具有更优的统计学特征.     

汕尾市新港大桥桥型方案比选

大跨度桥型方案比选。应在技术可行的前提下,对桥梁的经济性、美观性和创新性进行系统的分析、论证与比较,力争找到一个既能突出当地经济特色、人文思想及价值观念,又能表达现当代桥梁的技术水平及蕴涵未来桥梁的发展趋势的最佳方案。     

Key criteria influencing the choice of Arctic shipping: a fuzzy analytic hierarchy process model

As Arctic sea ice shrinks due to global warming, the Northern Sea Route (NSR) and the Northwest Passage (NWP) offer a substantial reduction in shipping distance between Asia and the European and North American continents, respectively, when compared to conventional routes through the Suez and Panama Canals. However, Arctic shipping routes have many problems associated with their use. The main objective of this paper is to identify the key criteria that influence the decisions of shipping operators with respect to using Arctic shipping routes. A multi-criteria decision-making methodology, the Fuzzy Analytic Hierarchy Process, is applied to rank four potential categories of criteria (‘economic’, ‘technical’, ‘political’ and ‘safety’ factors) and their sub-criteria.

The results of the analysis suggest that, on aggregate, ‘economic’ is the most important category of influential factors, followed by ‘safety’, ‘technical’ and ‘political’ factors. The paper concludes, however, that the most influential specific sub-criteria relate to risks that lie mainly within the ‘safety’ and ‘political’ domains and that, especially in combination, these overwhelm the importance which is attached to ‘economic’ factors such as reduced fuel use. Finally, the implications of these findings for the future development of Arctic shipping are addressed at a strategic level.     

Development of railway station choice models to improve the representation of station catchments in rail demand models

ABSTRACT

This paper describes the development of railway station choice models suitable for defining probabilistic station catchments. These catchments can then be incorporated into the aggregate demand models typically used to forecast demand for new rail stations. Revealed preference passenger survey data obtained from the Welsh and Scottish Governments was used for model calibration. Techniques were developed to identify trip origins and destinations from incomplete address information and to automatically validate reported trips. A bespoke trip planner was used to derive mode-specific station access variables and train leg measures. The results from a number of multinomial logit and random parameter (mixed) logit models are presented and their predictive performance assessed. The models were found to have substantially superior predictive accuracy compared to the base model (which assumes the nearest station has a probability of one), indicating that their incorporation into passenger demand forecasting methods has the potential to significantly improve model predictive performance.