Experience as a conditioning effect on choice: Does it matter whether it is exogenous or endogenous?

Previous choice studies have proposed a way to condition the utility of each alternative in a choice set on experience with the alternatives accumulated over previous periods, defined either as a mode used or not in a most recent trip, or the mode chosen in their most recent trip and the number of similar one-way trips made during the last week. The paper found that the overall statistical performance of the mixed logit model improved significantly, suggesting that this conditioning idea has merit. Experience was treated as an exogenous influence linked to the scale of the random component, and to that extent it captures some amount of the heterogeneity in unobserved effects, purging them of potential endogeneity. The current paper continues to investigate the matter of endogeneity versus exogeneity. The proposed approach implements the control function method through the experience conditioning feature in a choice model. We develop two choice models, both using stated preference data. The paper extends the received contribution in that we allow for the endogenous variable to have an impact on the attributes through a two stage method, called the Multiple Indicator Solution, originally implemented in a different context and for a single (quality) attribute, in which stage two is the popular control function method. In the first stage, the entire utility expression associated with all observed attributes is conditioned on the prior experience with an alternative. Hence, we are capturing possible correlates associated with each and every attribute and not just one selected attribute. We find evidence of potential endogeneity. The purging exercise however, results in both statistical similarities and differences in time and cost choice elasticities and mean estimates of the value of travel time savings. We are able to identify a very practical method to correct for possible endogeneity under experience conditioning that will encourage researchers and practitioners to use such an approach in more advanced non-linear discrete choice models as a matter of routine.

     

Delivering mobility as a service (MaaS) through a broker/aggregator business model

Transportation - Mobility as a service (MaaS) promises a bold new future where bundled public transport and shared mobility options (carsharing, ridesharing, bikesharing and microtransit) will...     

Fuzzy-logic-based incident detection for signalized diamond interchanges

This paper documents a fuzzy-logic-based incident detection algorithm for signalized urban diamond interchanges. The model is capable of detecting lane-blocking incidents whose effects are manifested by patterns of deterioration in traffic conditions that require adjustments in signal control strategies. As a component of a real-time traffic adaptive control system for signalized diamond interchanges, the algorithm feeds an incident report (i.e., the time, location, and severity of the incident) to the system's optimization manager, which uses that information to determine the appropriate signal control strategy.The performance of the model was studied using a simulation of an actual diamond interchange. The simulation study evaluated the model's performance in terms of detection rate, false alarm rate, and mean time to detect. The model's performance was encouraging, and the fuzzy-logic-based approach is considered promising.     

地面注汽管线表面散热损失影响因素分析

文中采用Fluent模拟与理论计算结合比较的方法,研究了不同因素对蒸汽管道散热损失的影响规律,并分析了理论计算模型的相对误差.发现增加注汽管线距地面高度,对其散热损失影响较弱;空气温度升高,注汽管道表面散热损失降低;风速和表面发射率对注汽管线表面热损失影响较大;数值模拟结果与理论计算数据相对误差较大.     

The performance of route modification and demand stabilization strategies in stochastic vehicle routing

A key concern in managing vehicle routing operations under stochastic demands is whether, on the basis of travel distance, route modification yields materially greater logistical efficiency than fixed routes. This research uses statistical calibration as the primary technique to develop a robust and tractable model for estimating this difference in logistical efficiency. Based on features such as the models predictive accuracy and generalizability, it constitutes a substantive improvement over existing models. The present study also expands the range of predictive models relevant to vehicle routing under stochastic demands with models to estimate the transportation and inventory effects of persuading customers to stabilize their ordering patterns.     

Towards measures of affective and eudaimonic subjective well-being in the travel domain

Studies of the connections between transportation and subjective well-being (SWB) require a clear understanding of the conceptual composition of travel-related SWB as well as psychometric instruments to measure these complex topics. Well-established psychological scales for measuring general SWB—including both hedonic (affective and cognitive) and eudaimonic aspects—are difficult to adapt or have yet to be tested in the travel domain. Existing measures of travel liking and travel satisfaction are somewhat inadequate for these purposes, especially for representing eudaimonia. Using a questionnaire survey of 680 commuters in the Portland, Oregon, region, exploratory and confirmatory factor analyses examined responses to a total of 42 items. Results suggested four-factor measurement models of both travel affect (Enjoyment, Attentiveness, Distress, and Fear) and travel eudaimonia (Health, Competence, Autonomy, and Security). Despite some limitations and opportunities for enhancements, these models show promise as ways of measuring affective and eudaimonic SWB in the travel domain for future studies and travel surveys.

     

The influence of parents’ travel patterns,perceptions and residential self-selectivity to their children travel mode shares

Using the UK National Travel Survey from 2002 to 2006, this paper investigates the influence of households’ residential self-selectivity, parents’ perceptions on accessibilities and their travel patterns on their children daily travel mode share. In doing this, this study introduces a model structure that represents the complex interactions between the parents’ travel patterns, their perceptions on public transport services and their reported residential self-selectivity reasons and the children travel mode shares. This structure is analysed with structural equation modelling. The model estimation results show that parents’ residential self-selectivity, parents’ perceptions and satisfactions on accessibilities and their daily travel patterns significantly influence the children’s daily travel mode shares. However, the effects are not uniform across household members. This study has revealed that households’ residential self-selectivity behaviours have more correlations with the children’s non-motorised mode shares, whilst the parents’ perceptions and satisfactions on transport infrastructure and public transport service qualities have more correlations with parents’ mode shares. The results also confirm that parents’ non-motorised modes use in travelling is highly correlated with the children’s physically active travel mode shares. However, at the same time, the results also show that the effects of mothers’ car use to the children travel mode shares is more apparent than fathers’.     

Introduction: Habitual travel choice

In this introduction to the special issue on habitual travel choice, we provide a brief account of the role of habit in travel behaviour, discuss more generally what habitual choice is, and briefly review the issues addressed in the solicited papers. These issues include how habitual travel behaviour should be measured, how to model the learning process that makes travel choice habitual, and how to break and replace car-use habits.