391 research outputs found
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
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
Floating Car and Camera Data Fusion for Non-parametric Route Travel Time Estimation
AbstractTraffic management centers take advantage of various data collection systems ranging from stationary sensors e.g. automated vehicle identification systems to mobile sensors e.g. fleet management systems. Each type of data collection system has its own advantages and disadvantages. Stationary sensors has less measurement noise than mobile sensors but their network coverage is limited. On the other hand, mobile sensors cover expand areas of road networks but they have less penetration rate and frequency of reports. Traffic state estimation can benefit from fusion of data from various sources as they complement each other. This paper introduces a route travel time estimation method that aggregates data from two traffic data sources, automated number plate recognition system and floating car data
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
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
Real Time Holding Control for Multiline Networks
We introduce a rule based multiline holding criterion for regularity in branch and trunk networks accounting for all passenger groups. On the shared transit corridor, we consider synchronization at the merging or the diverging stop. The decision between holding for regularity or synchronization is taken by comparing the expected passenger cost of each control action. The proposed criterion is tested through simulation in a synthetic double fork network with different shares of transferring passengers, control schemes for regularity and synchronization. The results show that multiline control outperforms the state of the art schemes at the network level, stemming from benefits occurring at the first part of the route and the shared transit corridor and a 3.5% more stable joint headway compared to the other schemes. Additionally, it is advised to perform the synchronization at the diverging stop, as it proves to result in a more stable transferring time equal to the joint frequency of the corridor while reducing the transfer time variability up to -42.7%
'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
Autonomous vehicle fleets for public transport: scenarios and comparisons
Autonomous vehicles (AVs) are becoming a reality and may integrate with existing public transport systems to enable the new generation of autonomous public transport. It is vital to understand what are the alternatives for AV integration from different angles such as costs, emissions, and transport performance. With the aim to support AV integration in public transport, this paper takes a typical European city as a case study for analyzing the impacts of different AV integration alternatives. A transport planning model considering AVs is developed and implemented, with a methodology to estimate the costs of the transport network. Traffic simulations are conducted to derive key variables related to AVs. An optimization process is introduced for identifying the optimal network configuration based on a given AV integration strategy, followed by the design of different AV integration scenarios, simulation, and analyses. With the proposed method, a case study is done for the city of Uppsala with presentation of detailed cost results together with key traffic statistics such as mode share. The results show that integrating AVs into public transport does not necessarily improve the overall cost efficiency. Based on the results and considering the long transition period to fully autonomous vehicles, it is recommended that public transport should consider a gradual introduction of AVs with more detailed analysis on different combination and integration alternatives of bus services and AVs.Peer ReviewedPostprint (published version
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