A method to assess demand growth vulnerability of travel times on road network links

Many national governments around the world have turned their recent focus to monitoring the actual reliability of their road networks. In parallel there have been major research efforts aimed at developing modelling approaches for predicting the potential vulnerability of such networks, and in forecasting the future impact of any mitigating actions. In practice-whether monitoring the past or planning for the future-a confounding factor may arise, namely the potential for systematic growth in demand over a period of years. As this growth occurs the networks will operate in a regime closer to capacity, in which they are more sensitive to any variation in flow or capacity. Such growth will be partially an explanation for trends observed in historic data, and it will have an impact in forecasting too, where we can interpret this as implying that the networks are vulnerable to demand growth. This fact is not reflected in current vulnerability methods which focus almost exclusively on vulnerability to loss in capacity. In the paper, a simple, moment-based method is developed to separate out this effect of demand growth on the distribution of travel times on a network link, the aim being to develop a simple, tractable, analytic method for medium-term planning applications. Thus the impact of demand growth on the mean, variance and skewness in travel times may be isolated. For given critical changes in these summary measures, we are thus able to identify what (location-specific) level of demand growth would cause these critical values to be exceeded, and this level is referred to as Demand Growth Reliability Vulnerability (DGRV). Computing the DGRV index for each link of a network also allows the planner to identify the most vulnerable locations, in terms of their ability to accommodate growth in demand. Numerical examples are used to illustrate the principles and computation of the DGRV measure

The traveler costs of unplanned transport network disruptions: An activity-based modeling approach

In this paper we introduce an activity-based modeling approach for evaluating the traveler costs of transport network disruptions. The model handles several important aspects of such events: increases in travel time may be very long in relation to the normal day-to-day fluctuations; the impact of delay may depend on the flexibility to reschedule activities; lack of information and uncertainty about travel conditions may lead to under- or over-adjustment of the daily schedule in response to the delay; delays on more than one trip may restrict the gain from rescheduling activities. We derive properties such as the value of time and schedule costs analytically. Numerical calculations show that the average cost per hour delay increases with the delay duration, so that every additional minute of delay comes with a higher cost. The cost varies depending on adjustment behavior (less adjustment, loosely speaking, giving higher cost) and scheduling flexibility (greater flexibility giving lower cost). The results indicate that existing evaluations of real network disruptions have underestimated the societal costs of the events.transport network disruption, delay cost, schedule adjustment, activity-based model, information

The impact of network density, travel and location patterns on regional road network vulnerability

Disruptions in the road transport system can have severe consequences for accessibility and transport costs. These impacts vary depending on in which regions they occur (regional importance), and users may be affected differently depending on where they travel (regional exposure). Some disruptions (caused by, e.g., car crashes, minor landslides and floods) affect only single road links, whereas others (e.g., heavy snowfall, storms and wildfires) disable extended areas of the road network. In this paper we systematically analyze the vulnerability of road networks under both kinds of disruptions. We apply the analysis approach to the Swedish road network using travel demand and network data from the Swedish transport modeling system Sampers. We investigate to what extent regional disparities in vulnerability depend on the network structure and travel and location patterns. For single link failures, we find that the total impacts (measured as travel time increases) depend strongly on the network density and the average traffic load in the region, whereas the average impact per traveler in a region is largely determined by the network density and the average user travel time. For area-covering disruptions, the study shows that the impacts depend strongly on the amount of internal, outbound and inbound travel demand of the affected area itself. As a result, the worst-case impact per traveler in a region is largely determined by the concentration of the population to one central location. Our findings, which should be universal for most road networks of similar scale, reveal that the vulnerability to single link failures and spatially spread events display markedly different regional distributions. Furthermore, these regional disparities stem from fundamental properties of the transport system and the population distribution. Hence, we believe that resource allocation for reducing vulnerability is more an issue of preparedness and mitigation than redundancy-providing infrastructure investments

The path inference filter: model-based low-latency map matching of probe vehicle data

We consider the problem of reconstructing vehicle trajectories from sparse sequences of GPS points, for which the sampling interval is between 10 seconds and 2 minutes. We introduce a new class of algorithms, called altogether path inference filter (PIF), that maps GPS data in real time, for a variety of trade-offs and scenarios, and with a high throughput. Numerous prior approaches in map-matching can be shown to be special cases of the path inference filter presented in this article. We present an efficient procedure for automatically training the filter on new data, with or without ground truth observations. The framework is evaluated on a large San Francisco taxi dataset and is shown to improve upon the current state of the art. This filter also provides insights about driving patterns of drivers. The path inference filter has been deployed at an industrial scale inside the Mobile Millennium traffic information system, and is used to map fleets of data in San Francisco, Sacramento, Stockholm and Porto.Comment: Preprint, 23 pages and 23 figure

'Resilience thinking' in transport planning

Resilience has been discussed in ecology for over forty years. While some aspects of resilience have received attention in transport planning, there is no unified definition of resilience in transportation. To define resilience in transportation, I trace back to the origin of resilience in ecology with a view of revealing the essence of resilience thinking and its relevance to transport planning. Based on the fundamental concepts of engineering resilience and ecological resilience, I define "comprehensive resilience in transportation" as the quality that leads to recovery, reliability and sustainability. Observing that previous work in resilience analysis in transportation has focussed on addressing engineering resilience rather than ecological resilience, I conclude that transformability has been generally overlooked and needs to be incorporated in the analysis framework for comprehensive resilience in transportation

Quantitative maritime security assessment: a 2020 vision

Maritime security assessment is moving towards a proactive risk-based regime. This opens the way for security analysts and managers to explore and exploit flexible and advanced risk modelling and decision-making approaches in maritime transport. In this article, following a review of maritime security risk assessment, a generic quantitative security assessment methodology is developed. Novel mathematical models for security risk analysis and management are outlined and integrated to demonstrate their use in the developed framework. Such approaches may be used to facilitate security risk modelling and decision making in situations where conventional quantitative risk analysis techniques cannot be appropriately applied. Finally, recommendations on further exploitation of advances in risk and uncertainty modelling technology are suggested with respect to maritime security risk quantification and management

Shared e-scooter micromobility: review of use patterns, perceptions and environmental impacts

Recently, a new shared micromobility service has become popular in cities. The service is supplied by a new vehicle, the e-scooter, which is equipped with a dockless security system and electric power assistance. The relatively unregulated proliferation of these systems driven by the private sector has resulted in numerous research questions about their repercussions. This paper reviews scientific publications as well as evaluation reports and other technical documents from around the world to provide insights about these issues. In particular, we focus on mobility, consumer perception and environment. Based on this review, we observe several knowledge needs in different directions: deeper comprehension of use patterns, their function in the whole transport system, and appropriate policies, designs and operations for competitive and sustainable shared e-scooter services.Peer ReviewedPostprint (published version

User inequity implications of road network vulnerability

JTLU vol. 2, no. 3, (2010) pp. 57-73An important purpose of the road transport system is to allow people to commute in efficient and reliable ways. For various undesired reasons, however, link capacities are sometimes reduced or links are closed completely. To assess and reduce the risk of such events, a key issue is to identify road links that are particularly important, i.e. roads where disruptions would have particularly severe consequences. This paper presents a method for incorporating user equity considerations into a road link importance measure. As a complement to measuring the total increase in vehicle travel time, we also measure the disparity in the distribution among individual users. These two components are combined to form an equity-weighted importance measure. We study the properties of this measure both analytically and in a full-scale case study of the Swedish road network. A main result is that increasing the weight put on the equity aspect transfers importance from the main roads to smaller local roads. The use of the measure in transport policy and planning is discussed

An adaptive route choice model for integrated fixed and flexible transit systems

Over the past decade, there has been a surge of interest in the transport community in the application of agent-based simulation models to evaluate flexible transit solutions characterized by different degrees of short-term flexibility in routing and scheduling. A central modeling decision in the development of an agent-based simulation model for the evaluation of flexible transit is how one chooses to represent the mode- and route-choices of travelers. The real-time adaptive behavior of travelers is intuitively important to model in the presence of a flexible transit service, where the routing and scheduling of vehicles is highly dependent on supply-demand dynamics at a closer to real-time temporal resolution. We propose a utility-based transit route-choice model with representation of within-day adaptive travel behavior and between-day learning where station-based fixed-transit, flexible-transit, and active-mode alternatives may be dynamically combined in a single path. To enable experimentation, this route-choice model is implemented within an agent-based dynamic public transit simulation framework. Model properties are first explored in a choice between fixed- and flexible-transit modes for a toy network. The framework is then applied to illustrate level-of-service trade-offs and analyze traveler mode choices within a mixed fixed- and flexible transit system in a case study based on a real-life branched transit service in Stockholm, Sweden.Comment: 33 pages, 9 figures, preprin