An approach to time dependence and reliability in dynamic route guidance

This paper presents a methodology, in order to increase the reliability of the route suggestions in route guidance systems. Based on the A* path finding algorithm and Chen’s link penalty method, the procedure involves penalising links with a high risk of being congested and obtaining a set of reliable route suggestions. Time-dependence of travel times is considered by adapting the Flow Speed Model technique accordingly. Modifications to the structure of the path finding algorithms are also made, so as to account for real road network features. Finally, experiments using simulated travel time and reliability data are carried out on a road network and the results are discussed

Hyperpaths in network based on transit schedules

The concept of a hyperpath was introduced for handling passenger strategies in route choice behavior for public transit, especially in a frequency-based transit service environment. This model for handling route choice behavior has been widely used for planning transit services, and hyperpaths are now applied in areas beyond public transit. A hyperpath representing more specific passenger behaviors on a network based on transit schedules is proposed. A link-based time-expanded (LBTE) network for transit schedules is introduced; in the network each link represents a scheduled vehicle trip (or trip segment) with departure time and travel time (or arrival time) between two consecutive stops. The proposed LBTE network reduces the effort to build a network based on transit schedules because the network is expanded with scheduled links. A link-based representation of a hypergraph with existing hyperpath model properties that is directly integrated with the LBTE network is also proposed. Transit passenger behavior was incorporated for transfers in the link-based hyperpath. The efficiency of the proposed hyperpath model was demonstrated. The proposed models were applied on a test network and a real transit network represented by the general specification of Google's transit feed

Understanding the role of biodiversity in the climate, food, water, energy, transport and health nexus in Europe

Biodiversity underpins the functioning of ecosystems and the diverse benefits that nature provides to people, yet is being lost at an unprecedented rate. To halt or reverse biodiversity loss, it is critical to understand the complex interdependencies between biodiversity and key drivers and sectors to inform the development of holistic policies and actions. We conducted a literature review on the interlinkages between biodiversity and climate change, food, water, energy, transport and health (“the biodiversity nexus”). Evidence extracted from 194 peer-reviewed articles was analysed to assess how biodiversity is being influenced by and is influencing the other nexus elements. Out of the 354 interlinkages between biodiversity and the other nexus elements, 53 % were negative, 29 % were positive and 18 % contained both positive and negative influences. The majority of studies provide evidence of the negative influence of other nexus elements on biodiversity, highlighting the substantial damage being inflicted on nature from human activities. The main types of negative impacts were land or water use/change, land or water degradation, climate change, and direct species fatalities through collisions with infrastructure. Alternatively, evidence of biodiversity having a negative influence on the other nexus elements was limited to the effects of invasive alien species and vector-borne diseases. Furthermore, a range of studies provided evidence of how biodiversity and the other nexus elements can have positive influences on each other through practices that promote co-benefits. These included biodiversity-friendly management in relevant sectors, protection and restoration of ecosystems and species that provide essential ecosystem services, green and blue infrastructure including nature-based solutions, and sustainable and healthy diets that mitigate climate change. The review highlighted the complexity and context-dependency of interlinkages within the biodiversity nexus, but clearly demonstrates the importance of biodiversity in underpinning resilient ecosystems and human well-being in ensuring a sustainable future for people and the planet.</p

Monitoring Signalized Urban Networks: Dynamic Equilibrium-Free Model Based on a Discrete-Time Optimal Control Formulation

Monitoring traffic operations in a detailed manner and at the network level is a fundamental component in optimal traffic systems control. Especially in the case of urban signalized networks, accurate and reliable systems monitoring is essential for applying a wide range of control strategies, mechanisms, and concepts, such as information provision, signal control, and optimal routing. This paper presents a discrete-time optimal control scheme for monitoring urban signalized networks, augmenting real-time traffic information with a dynamic traffic model. A detailed representation of network traffic based on the cell transmission model was dynamically calibrated with a quasi-Newton nonlinear process that could tackle optimization cases of noncontinuous variables by approximating derivatives and performing a line search. An alternative network loading assumption was tested. The loading process covering all network links’ flows relied not on complex dynamic equilibrium assumptions that could infer unnecessary estimation inaccuracies but on the combined estimation of entry flows and turning proportions at each intersection. Results from the application of the proposed framework on a realistic urban network provide encouraging evidence of its value for monitoring realistic urban traffic systems. © 2017 National Academy of Sciences

Online algorithm for dynamic dial a ride problem and its metrics

In this paper, an online regret based dial-a-ride (OR-DARP) algorithm is introduced and its performance evaluated on an actual demand responsive transit (DRT) system. The innovative part of the algorithm is the design of the optimization engine. A signal communication scheme between the trip dispatcher and the algorithm is used to improve utilization of the available idle time that can then be devoted to the optimization engine. The basic concept is as follows: a. Every trip request is treated as an emergency request demanding an immediate answer, b. The optimization engine runs continuously, thereby consuming every idle time fragment unless interrupted by a new trip request. The trip data are real, and they are sourced from a DRT system operating at a municipality in northern Greece where a static dial-a-ride algorithm was used as the optimization engine. Given the fact that these trips data provide all trip details plus the show-up time (the most important feature for our study), these data are the ideal basis for an "a posteriori" evaluation of the proposed online approach. Another contribution of this paper is the identification of the critical parameters in the trade-off between benefits gained from continuing to optimize an online system versus the losses of non-served demands. This important issue when applying online algorithms has not been studied extensively in the literature so far (to the best of our knowledge). © 2016 The Authors. Published by Elsevier B.V

FORMULATION OF ANALYTICAL TIME-VARYING INTERMODAL PERSON TRIP ASSIGNMENT MODEL

An analytical formulation of the intermodal dynamic traffic assignment problem is presented. The model is a cell transmission-based, single-destination, system optimal integer linear programming formulation for a multimodal network of cars and buses. The computational tests demonstrate interesting insights into the complex interactions between travelers\u27 intermodal path choices and traffic movements. Specifically, as with many analytical time-varying traffic models, the constraints regulate flow, while the objective function provides an incentive for travelers to progress on least-cost paths toward the cost-free trip termination cells. It is found that difficulties relate to this reliance on costs to advance travelers and vehicles; for example, the non-first-in-first-out propagation of buses ahead of automobiles is a result of the higher cost incurred by numerous riders on a single bus vehicle. Similarly, the model\u27s tendency to hold buses at bus stops or force buses to skip bus stops results from a difference in costs incurred by travelers who would be better served by the holding of the bus or by the skipping of a stop. On the basis of the findings on the model\u27s behavior, recommendations are made for the future development of time-varying intermodal routing problems

System optimal signal optimization formulation

A mixed-integer linear programming formulation is proposed to solve the combined system optimal dynamic traffic assignment and signal optimization problem. Traffic conditions are modeled with the cell transmission model, a convergent numerical approximation to the hydrodynamic model of traffic flow. The formulation is suited to respond to oversaturated traffic conditions. It also can be adapted to account for turning movements, protected and permissive phases (gap acceptance), and multiple signal controller types: dynamic (traffic adaptive) and pretimed. Trials with a test network validated the formulation and achieved promising results. Specifically, dynamic signal control proved to be substantially more effective than pretimed control for incident conditions. In addition, potential benefits of rerouting vehicles in both directions of a roadway were revealed even when only one direction is closed