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

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%

Emergence of a urban traffic macroscopic fundamental diagram

This paper examines mild conditions under which a macroscopic fundamental diagram (MFD) emerges, relating space-averaged speed to occupancy in some area. These conditions are validated against empirical data. We allow local speed-occupancy relationships and , in particular, require no equilibrating process to be in operation. This means that merely observing the stable relationship between the space-averages of speed, flow and occupancy are not sufficient to infer a robust relationship and the emerging MFD cannot be guaranteed to be stable if traffic interventions are implemented

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

Emergence of a urban traffic macroscopic fundamental diagram

This paper examines mild conditions under which a macroscopic fundamental diagram (MFD) emerges, relating space-averaged speed to occupancy in some area. These conditions are validated against empirical data. We allow local speed-occupancy relationships and , in particular, require no equilibrating process to be in operation. This means that merely observing the stable relationship between the space-averages of speed, flow and occupancy are not sufficient to infer a robust relationship and the emerging MFD cannot be guaranteed to be stable if traffic interventions are implemented

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