Vehicle routing problem and driver behaviour: a review and framework for analysis

Vehicle routing problems (VRPs) whose typical objective is to minimise total travel costs over a tour have evolved over the years with objectives ranging from minimising travel times and distances to minimising pollution and fuel consumption. However, driver behaviour continues to be neglected while planning for vehicle routes. Factors such as traffic congestion levels, monotonous drives and fatigue have an impact on the behaviour of drivers, which in turn might affect their speed-choice and route-choice behaviours. The behaviour of drivers and their subsequent decision-making owing to these factors impact the revenue of transport companies and could lead to huge losses in extreme cases. There have been studies on the behaviour of drivers in isolation, without inclusion of the objectives and constraints of the traditional routing problem. This paper presents a review of existing models of VRP, planner behaviour models in the VRP context and driver behaviour models and provides a motivation to integrate these models in a stochastic traffic environment to produce practical, economic and driver-friendly logistics solutions. The paper provides valuable insights on the relevance of behavioural issues in logistics and highlights the modelling implications of incorporating planner and driver behaviour in the framework of routing problems.     

Port choice in container market: a literature review

As a result of the intense changes occurring in port environment over the last decades, new models of competitiveness have been developed, where port authorities try to increase their attractiveness. In this context, one of the most debated issues in this area of research is still the role played by port authorities in defining port competitiveness. The aim of this paper is to provide a review of port choice literature enabling to identify the main port choice’s criteria in order to define the role played by Port Authorities and to point out future lines of research that should be undertaken to fully incorporate current ports’ environment and performance. The results show that although some studies point out the importance of geographical factors in port choice, a larger number of studies defend the increasing role played by port authorities in determining the competitiveness through investing in port infrastructure, improving port efficiency or hinterland accessibility. Despite the existing models contributing on this topic, there are still some gaps in terms of measuring the port performance, including port strategies and studying the port choice for specific industries.     

Evaluation of eco-driving training for vehicle fuel use and emission reduction: A case study in Australia

This study evaluates effectiveness of driver education teaching greater fuel efficiency (Eco-Driving) in a real world setting in Australia. The driving behaviour, measured in fuel use (litres per 100 km of travel) of a sample of 1056 private drivers was monitored over seven months. 853 drivers received education in eco-driving techniques and 203 were monitored as a control group. A simple experimental design was applied comparing the pre and post training fuel use of the treated sample compared to a control sample. This study found the driver education led to a statistically significant reduction in fuel use of 4.6% or 0.51 litres per 100 km compared to the control group.     

Connectivity’s impact on mandatory lane-changing behaviour: Evidences from a driving simulator study

The connected environment provides driving aids to help drivers making efficient and safe driving decisions. The literature to date is devoid of conclusive evidences of the connected environment’s impact on drivers’ mandatory lane-changing (MLC) behaviour. As such, the objective of this study is to examine MLC behaviour through a driving simulator experiment using the CARRS-Q Advanced Driving Simulator. Participants with diverse background performed the experiment in randomised driving conditions: baseline (without the driving aids), connected environment with perfect communication, and connected environment with communication delay. Repeated measure ANOVA in the form of linear mixed model and Generalized Estimation Equation (GEE) are employed to analyse various driving performance indicators during MLC event. We find that drivers in the connected environment tend to wait longer, increase the initial speed, and maintain a larger spacing, compared to when they are driving in the baseline condition. In addition, drivers in the connected environment are likely to reject fewer number of gaps and select relatively bigger gap sizes. Furthermore, post-encroachment time (PET) in the connected environment is higher across different gap sizes, indicating that the connected environment makes MLC safer. The GEE model on gap acceptance suggests that the perfect communication and communication delay has positive and negative impact on the accepted gap size, respectively, and the GEE model on lane-change duration indicates that lane-change duration tends to increase in the connected environment.     

Effect of attitudes, habit and affective appraisal on mode choice: an application to university workers

Traditionally, car use and modal choice, in general, have been studied under the random utility framework, assuming that individuals choose a particular mode based on their own socio-economic characteristics and the attributes describing the available options. This approach has originated useful models which have been able to explain modal split. However, at the same time, it has received critics because of its poor characterization of human behaviour and the weakness of its assumptions. Research has suggested that socio-psychological factors could help to understand better the choice process. In this paper, attitudinal theory and its link to human behaviour were used to select attitudes, habit and affective appraisals as explanatory variables. They were measured using ad-hoc instruments, which were combined with a revealed preference questionnaire, in order to obtain information about the traveller and the chosen mode. This instrument was applied to a sample extracted from staff members of the University of Concepcion, Chile. Analyses of attitudinal variables showed that car use habit was positively correlated to attitude and positive emotions towards car, implying that breaking the vicious circle of car use through persuasive techniques might be difficult. Estimation of discrete choice models showed that attitudinal variables presented a significant contribution to modal utility, and helped to improve both fitness and statistical significance. Results showed that choice can be influenced by factors related to attitudes and affective appraisal, and that their study is necessary in order to achieve an effective car use reduction.

Modelling daily activity program generation considering within-day and day-to-day dynamics in activity-travel behaviour

This paper presents a comprehensive econometric modelling framework for daily activity program generation. It is for day-specific activity program generations of a week-long time span. Activity types considered are 15 generic categories of non-skeletal and flexible activities. Under the daily time budget and non-negativity of participation rate constraints, the models predict optimal sets of frequencies of the activities under consideration (given the average duration of each activity type). The daily time budget considers at-home basic needs and night sleep activities together as a composite activity. The concept of composite activity ensures the dynamics and continuity of time allocation and activity/travel behaviour by encapsulating altogether the activity types that are not of our direct interest in travel demand modelling. Workers’ total working hours (skeletal activity and not a part of the non-skeletal activity time budget) are considered as a variable in the models to accommodate the scheduling effects inside the generation model of non-skeletal activities. Incorporation of previous day’s total executed activities as variables introduces day-to-day dynamics into the activity program generation models. The possibility of zero frequency of any specific activity under consideration is ensured by the Kuhn-Tucker optimality conditions used for formulating the model structure. Models use the concept of random utility maximization approach to derive activity program set. Estimations of the empirical models are done using the 2002–2003 CHASE survey data set collected in Toronto.

Gender differences in travel behaviour and willingness to adopt sustainable behaviour

This paper presents pioneering research on gender differences in travel behaviour in southeastern Europe. The study analyses the socio-economic and main travel characteristics (particularly parking) of men and women. Additionally, it examines the influence of parking demand management measures on their behaviour, in terms of the willingness of men and women to reduce car use and to adopt more sustainable behaviour. The results reveal significant differences between genders in most of the characteristics examined. Moreover, it is shown that women are less car dependent and more sensitive to parking pricing and, therefore, more willing to replace a car journey with public transport. These findings suggest that gender should be an essential parameter when user behaviour is examined and modelled. Furthermore, the results indicate that gender differences must be considered when transport policy is created to affect the behaviour of men and women equally. The achievement of social equality is one of the primary objectives of sustainable development.     

Exploring gendered cycling behaviours within a large-scale behavioural data-set

Analysing over 10 million journeys made by members of London's Cycle Hire Scheme, we find that female customers' usage characteristics are demonstrably different from those of male customers. Usage at weekends and within London's parks characterises women's journeys, whereas for men, a commuting function is more clearly identified. Some of these variations are explained by geo-demographic differences and by an atypical period of usage during the first three months after the scheme's launch. Controlling for each of these variables brings some convergence between men and women. However, many differences are preserved. Studying the spatio-temporal context under which journeys are made, we find that women's journeys are highly spatially structured. Even when making utilitarian cycle trips, routes that involve large, multi-lane roads are comparatively rare, and instead female cyclists preferentially select areas of the city associated with slower traffic streets and with cycle routes slightly offset from major roads.