A model of bus bunching under reliability-based passenger arrival patterns.

If bus service departure times are not completely unknown to the passengers, non-uniform passenger arrival patterns can be expected. We propose that passengers decide their arrival time at stops based on a continuous logit model that considers the risk of missing services. Expected passenger waiting times are derived in a bus system that allows also for overtaking between bus services. We then propose an algorithm to derive the dwell time of subsequent buses serving a stop in order to illustrate when bus bunching might occur. We show that non-uniform arrival patterns can significantly influence the bus bunching process. With case studies we find that, even without exogenous delay, bunching can arise when the boarding rate is insufficient given the level of overall demand. Further, in case of exogenous delay, non-uniform arrivals can either worsen or improve the bunching conditions, depending on the level of delay. We conclude that therefore such effects should be considered when service control measures are discussed

Bus passenger path choices after consulting ubiquitous real-time information

Ubiquitous real-time passenger information (URTPI) enables public transport (PT) users to make better travel choices at both pre-trip and en-route stages. A significant amount of URTPI usage is evident in the existing literature. This study investigates the impact of URTPI on bus passenger path choice. To this end, a bus passenger survey was conducted in the City of Edinburgh, UK, and a total of 1645 completed responses were collected. More than half of the survey participants used at least one source of ubiquitous information. The survey results reveal that about 55% of the URTPI users changed at least one aspect of their trip. Changing the time of departure from the start and boarding time are the two most popular actions taken by bus passengers after consulting URTPI. Passengers' decisions are influenced by information on bus arrival time, bus route, and walking distance. The study demonstrates the potential impact of the change in passenger choices on PT demand distribution. We find that the demand distribution for bus runs could potentially be changed by 17% and for bus lines by 15%. The overall network demand distribution could be affected in 42% of cases as a result of consulting URTPI. This study advocates that transport planners and operators should take the potential impact of URTPI into account to make better predictions of PT demand distribution

Supporting Urban Consolidation Centres with Urban Freight Transport Policies: A Comparative Study of Scotland and Sweden

This study investigates how supportive urban freight transport (UFT) policies work in conjunction with stakeholder collaboration to support public-led urban consolidation centre (UCC) developments. The methodology was a multiple case study approach, comparing cases in Sweden and Scotland, two countries that are more/less advanced in their approach to UFT policy. The key finding reveals that while UFT policies such as time window restrictions can support successful UCCs, they cannot be considered in isolation from the collaborative UFT policy setting established by the local authority. A successful development also requires a commitment to financially support the UCC over at least the medium term, allowing time for the system to mature and collaborative service offerings to be developed. The findings of this study can be used by local authorities to establish a supportive UFT policy setting, as well as specifically designing policy packages in conjunction with UCC business models

Performance of route suggestions in networks with correlated link congestion.

We evaluate the performance of route suggestions which can be adopted when no real time information is available. We consider that when the available information is limited, risk-aversion, regret and disappointment may play an important role in decision making. The effect of link travel time correlation on heuristic route choice efficiency is also explored. Monte Carlo simulation is used to study the performance of heuristic decision making in the Chicago network under different levels of congestion. We conclude that finding the shortest path is more difficult and more important – and therefore the value of real time information is higher – in the presence of positive correlation. A simple local search considering frustration proves the best a priori strategy in many circumstances

UberPOOL Services – Approaches from Transport Operators and Policymakers in London

Ridesourcing services such as Uber provide a segment of the total daily trips in Urban cities, for instance, its reported that Taxi and Private Hire Vehicle (PHV) mode share were 1.3% of total daily trips in London in 2014 (GLA, 2016) - which includes Ridesourcing - however the adoption of Ridesourcing services is growing rapidly – with Uber reporting 3.5 million users of its services in London – thereby disrupting traditional travel habits in urban areas. The number of PHVs in London has increased by 58% since 2008/09 to over 77,000 in 2016, meanwhile, the number of licensed PHV drivers has increased by 81% over the same period, (TFL, 2017) - these include Uber drivers. However, it is not well known, how much of recent changes in people’s travel habits, is attributed to Ridesourcing or other tech-driven habits.Conventional transport systems have a limited capacity and are becoming increasingly overloaded in urban areas, creating increasing disruption, congestion and emissions in cities around the world. However, new technology-driven, on-demand Ridesourcing business models that provide low-cost alternative transport to car ownership and public transport - such as those provided by Uber and Lyft – are causing unprecedented disruption to the way urban mobility services are provided and used in urban cities around the world. Ridesourcing is part of the wider phenomenon of the ‘sharing economy’ that is making people re-think, how they avail services from different sectors such as the Transport (i.e. Uber) and Hotel (i.e. Airbnb) industries. As a result, new types of on-demand shared mobility services (i.e. UberPOOL), which use advanced mobile technologies and Information & Communication Technologies (ICTs) are becoming popular in cities such as London, UK. Shared Ridesourcing services have the potential to increase positive transport behaviours, including reduced single car occupancy and decreased car ownership. This has triggered debate among policymakers, transport planners and transport authorities; however, the impacts for and consequences of these services on conventional public transport are not well understood.This research provides insights about shared ridesourcing services (i.e. UberPOOL) and potential implications on traditional transport services in an urban context, using Uber operations in London (U.K) as the case study. This paper discusses the current literature on this topic and the key findings from the first phase of multi-phased research that investigates the impacts of shared ridesourcing services on transport policy and operations. Extensive qualitative interview data were collected from policymakers and operators and key findings from the analysed data are discussed in this paper. The results help to answer key research questions and provide a broad appreciation of these new disruptive mobility service

A study of herding behaviour in exit choice during emergencies based on random utility theory.

Modelling human behaviour in emergencies has become an important issue in safety engineering. Good behavioural models can help increase the safety of transportation systems and buildings in extreme situations like fires or terrorist attacks. Although it is well known that the interaction with other decision makers affects human behaviour, the role of social influences during evacuations still needs to be investigated. This paper contributes to fill this gap by analysing the occurrence of Herding Behaviour (HB) in exit choice. Theoretical explanations of HB are presented together with some modelling approaches used in different fields where HB is relevant. A discrete choice stated preference experiment is then carried out to study the role of HB in the decision-making process concerning exit choice during evacuation. A binary logit model is proposed showing that the occurrences of HB are affected by both environmental and personal factors. In particular, the model shows that the personal aptitude to HB can have a key role in selecting an exit

Bus bunching along a corridor served by two lines

Headway fluctuations and “bus bunching” are well known phenomena on many bus routes where an initial delay to one service can disturb the whole schedule due to resulting differences in dwell times of subsequent buses at stops. This paper deals with the influence of a frequent but so far largely neglected characteristic of bus networks on bus bunching, that is the presence of overtaking and common lines. A set of discrete state equations is implemented to obtain the departure times of a group of buses following the occurrence of an exogenous delay to one bus at a bus stop. Two models are distinguished depending on whether overtaking at stops is possible or not. If two buses board simultaneously and overtaking is not possible, passengers will board the front bus. If overtaking is possible, passengers form equilibrium queues in order to minimise their waiting times. Conditions for equilibrium queues among passengers with different choice sets are formulated. With a case study we then illustrate that, if overtaking is not allowed, the presence of common lines worsens the service regularity along the corridor. Conversely, common lines have positive effects when overtaking is possible. We suggest hence that appropriate network design is important to reduce the negative effects of delay-prone lines on the overall network performance

Influences on urban freight transport policy choice by local authorities

Individual freight transport policies have been investigated in the literature extensively in the last 10–15 years, yet there has surprisingly been very little attention to the process of selecting urban freight transport (UFT) policy measures. This study focuses on UFT policy choice by local authorities, investigating how policy context, resource availability and the need for legitimacy influence how local authorities seek and select UFT specific policies. The methodology is a cross-case analysis of eleven cities across three countries (Sweden, England and Scotland), based on interview and documentary data.Findings reveal that all cities have the same high-level goals, such as reducing emissions and congestion, supporting the economy and improving quality of life. However, in most cases these rather general goals are not broken down into clear objectives with targets that can be measured. Therefore, selected UFT policy measuresare chosen from a pool of common measures (primarily access restrictions such as time windows and weight restrictions), but without monitored targets that determine whether or not they are achieving objectives. This does not necessarily mean that the measures chosen are inappropriate, but that there is a lack of a strategic approach to setting and reviewing measures according to achieving specific policy goals. This is primarily a result of a lack of resources and dedicated UFT personnel, as well as challenges related to public acceptability of restrictive policies

Considerations about the Analysis of ITS Data of Bicycle Sharing Systems.

Handling and managing data automatically collected by Intelligent Transport Systems (ITS) is a major opportunity and challenge for transport professionals nowadays. This study guides the management of smartcard data from public bikes by providing criteria to detect travel patterns that describe the specific use of bike-share systems and which cannot be encountered in other transport modes. The guidelines have been put into practice with data from the TusBic system in Santander, Spain.The major discovery that has resulted from the analysis of the data is the high number of records that describe very short trips that show the same terminal at origin and destination. An algorithm is proposed that assumes the users try and return the bike if this is not working properly, and pick a new one from the same terminal. In such cases, the records are joined to describe a unique trip by considering the origin as the pick-up instant of the first bike, and the destination, the instant at which the second bike has been returned.The indications presented in this article should be considered in future studies of demand and level of service of public bicycle systems since not only they can make a big difference in the accuracy of the results, but also they can provide interesting information regarding the management and design of the system. Therefore, they are of interest for different stakeholders such as politicians and decision makers, service planners, and agencies responsible for the operations and direct management of public bicycle systems

Who is More Likely (Not) to Make Home-Based Work Trips during the COVID-19 Pandemic? The Case of Scotland

In this study, we use survey data (n=6,000) to investigate the work trip patterns of Scottish residents at various points of the COVID-19 pandemic. We focus specifically on the reported patterns of weekly work trips made during the government-enforced lockdown and subsequent phases of restriction easing. This is of particular importance given the widespread changes in work trips prompted by COVID-19, including a significant rise in telecommuting and a reduction in public transport commuting trips. The survey data show that the vast majority of respondents (~85%) made no work trips during lockdown, dropping to ~77% following the easing of some work-related restrictions. Zero-inflated hierarchical ordered probit models are estimated to determine the sociodemographic and behavioral factors affecting the frequency of work trips made during three distinct periods. The model estimation results showed that socioeconomic characteristics of respondents influenced work trips made throughout the pandemic. In particular, respondents in households whose main income earner is employed in a managerial/professional occupation were significantly more likely to make no work trips at all stages of the pandemic. Those with a health problem or disability were also significantly more likely to make no work trips throughout the pandemic. Other interesting findings concern respondents’ gender, as males were more likely to complete frequent work trips than females throughout the pandemic, and differences between densely populated areas and the rest of Scotland, as respondents from a large city (Edinburgh or Glasgow) were significantly more likely to make frequent work trips as restrictions were eased