Torts - Assumption of Risk

A California Court of Appeals has held that a person\u27s status as a trespasser is now largely immaterial and no longer determines that he assumed the risk of personal injuries caused by a possessor\u27s negligence. Beard v. Atchison, Topeka and Santa Fe Railway Company, 4 Cal. App. 3d 130, 84 Cal. Rptr. 449 (1970)

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

The Right to Treatment - Alternative Rationales [Note]

That which is most clear in any debate over proper care for the mentally ill is the need for an immediate solution. Understaffed and poorly maintained hospitals with doctor-patient ratios as high as one to 950 are no less than a national shame. To ask where the blame lies is a waste of time. The important concern is what must be done

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

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

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

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

The joint effect of weather and lighting conditions on injury severities of single-vehicle accidents

This study seeks to identify and analyze variations in the effect of contributing factors on injury severities of single-vehicle accidents across various lighting and weather conditions. To that end, injury-severity data from single-vehicle, injury accidents occurred in Scotland, United Kingdom in 2016 and 2017 are statistically modeled. Upon the conduct of likelihood ratio tests, separate models of accident injury severities are estimated for various combinations of weather and lighting conditions taking also into account the presence and operation of roadside lighting infrastructure. To account for the possibility of unobserved regimes underpinning the injury-severity mechanism, the zero-inflated hierarchical ordered probit approach with correlated disturbances is employed. The approach also relaxes the fixed threshold restriction of the traditional ordered probability models and captures systematic unobserved variations between the underlying regimes. The model estimation results show that a wide range of accident, vehicle, driver, trip and location characteristics have varying impacts on injury severities when different weather and lighting conditions are jointly considered. Even though several factors are identified to have overall consistent effects on injury severities, the simultaneous impact of unfavorable weather and lighting conditions is found to introduce significant variations, especially in the effect of vehicle- and driver-specific characteristics. The findings of this study can be leveraged in vehicle-to-infrastructure or in-vehicle communication technologies that can assist drivers in their responses against hazardous environmental conditions

Changes in the frequency of shopping trips in response to a congestion charge

This paper presents an analysis of shopping trips into London’s central shopping district (Oxford Street area) before and after the introduction of the congestion charging scheme in February 2003. In collaboration with a major department store, three surveys have been conducted in order to understand the changes in shopping frequency and the reasons for so doing. The analysis is based on tabulations of the raw data, binary logit models to analyse which customer groups have reduced their shopping frequency and ordered logit models to analyse which groups have reduced their shopping more than others. The outcome shows that within the sample surveyed the congestion charging scheme has caused a significant number to shop less often in central London and only a few to shop more often in the Oxford Street area. Negative experiences with the congestion charging scheme or a generally bad perception of the scheme are the main reasons for this. Other events, such as the Central Line closure or terrorist threats occurring at the same time also have a temporary influence on the shopping frequency in central London. Evidence from other travel demand measures on city centre shopping activities suggest that the long-term effects of the congestion charge could be more positive