Towards Robust Deep Reinforcement Learning for Traffic Signal Control: Demand Surges, Incidents and Sensor Failures

Reinforcement learning (RL) constitutes a promising solution for alleviating the problem of traffic congestion. In particular, deep RL algorithms have been shown to produce adaptive traffic signal controllers that outperform conventional systems. However, in order to be reliable in highly dynamic urban areas, such controllers need to be robust with the respect to a series of exogenous sources of uncertainty. In this paper, we develop an open-source callback-based framework for promoting the flexible evaluation of different deep RL configurations under a traffic simulation environment. With this framework, we investigate how deep RL-based adaptive traffic controllers perform under different scenarios, namely under demand surges caused by special events, capacity reductions from incidents and sensor failures. We extract several key insights for the development of robust deep RL algorithms for traffic control and propose concrete designs to mitigate the impact of the considered exogenous uncertainties.Comment: 8 page

Instruments of Transport Policy.

The material in this Working Paper was generated as input to DETR's Guidance on the Methodology for Multi Modal Studies (GOMMMS). DETR subsequently decided only to provide summary information on transport policy measures, and to leave the consultants involved in individual multi modal studies to make their own assessment of individual policy measures in the context of specific study areas. It has been decided to make this fuller document available as a reference source. The purpose of the review of policy measures was to provide summary information on the range of policy measures available, experience of their use and, based on past studies, their potential contribution to the range of policy objectives specified for GOMMMS. The review was based on an earlier one included in the Institution of Highways and Transportation's Guidelines on Developing Urban Transport Strategies (1996). This material was updated using references published since 1996 and expanded to cover policy measures relevant in inter-urban areas. It had been intended to circulate it for comment before publishing a revised version. However, DETR decided to use an abridged version before this consultation was complete. It should be borne in mind that this document has not, therefore, undergone the peer assessment which had been intended. To avoid unnecessary further work, the material is presented as it had been drafted for the GOMMMS Guidance document. The only modifications have been to change the chapter and paragraph numbers, and to remove the cross references to other parts of the Guidance document

The development and control of traffic jams caused by incidents in rectangular grid networks.

Urban traffic congestion is becoming a central issue in transport planning. If the present growth in car ownership and use continues, traffic jams are likely to increase in frequency and extent, particularly within the central areas of major cities. Whilst it is important to study the impact of congestion in the field, there is an urgent need for a fundamental understanding of the causes of congestion and the way in which it propagates. But, although a number of control schemes for controlling traffic congestion exist, no comprehensive rationale for an effective dispersal strategy has been developed. This research is mainly concerned with the properties of incident-induced traffic jams on rectangular grid networks, and possible measures for preventing and controlling them. The research investigates the underlying structure of such jams using a combination of theoretical and simulation models developed for this purpose. Using these models, gridlock is identified as a crucial stage in the evolution of traffic jams. However, most conventional traffic management measures aim to increase capacity and hence postpone the onset of gridlock and are unsuitable when gridlock has already set in. This thesis develops several alternative strategies for protecting networks from gridlock and dissipating traffic jams once they have formed. The treatment focuses on the installation of bans at specific network locations. The bans come in two forms: turn or ahead. Turn bans are imposed on selected links to break gridlock cycles at the nucleus of the traffic jam. By contrast, ahead bans are implemented around the traffic jam envelope to reduce input into critical sections of the road. The control strategies are tested extensively using the simulation model and as a result, some general control principles have emerged. These are not intended to be immediately applicable to real networks since they incorporate some simplifying assumptions. However, they point to certain characteristics of traffic jam growth and dispersal which would not be accessible in any other way

Transport in the Trans-Pennine Corridor: Present Conditions and Future Options. Interregional Study Working Paper 3.

This paper reports on a desk study carried out by the Institute for Transport Studies as part of a wider study of opportunities for inter-regional working in the trans-Pennine corridor, considering economic, environmental and transport issues. It draws together available information on transport and movement flows in the trans-Pennine corridor. These patterns of movement are examined from a broad perspective which considers intra-regional, inter- regional and international movements within and across the study area. The report proposes a regional package approach to transport, based on demand management and modal transfer

Investigación de los efectos de las redes de comunicación 5G sobre la gestión urbana inteligente y el desarrollo económico sostenible

This article, with a global view, explains the necessity of using smart urban technologies in the development of the infrastructure of ICTnetworks and in order to resolve the urban management challenges. Also, by reviewing some smart model in current modern cities, alongwith new generations of high-speed communications, some of the improvements made in this field are being examined. The economicview in this research has a global approach to saving energy and increasing productivity while protecting natural resources and theenvironment through emerging communications technologies. At the end of this research, by challenging some traditional andcostly method in urban management, it is proposed to provide technological solutions to save time and money, as well as urbanbeautification and urbanization. With the hope that the findings of this study, though insignificant, will be the light on urban planningand urban considerations to integrate smart city technologies. It should be noted that the potential of the policymakers in the nearfuture will be effected on creating an appropriate environment for sustainable development of the economy in national dimensions

Review of California Wildfire Evacuations from 2017 to 2019

Between 2017 and 2019, California experienced a series of devastating wildfires that together led over one million people to be ordered to evacuate. Due to the speed of many of these wildfires, residents across California found themselves in challenging evacuation situations, often at night and with little time to escape. These evacuations placed considerable stress on public resources and infrastructure for both transportation and sheltering. In the face of these clear challenges, transportation and emergency management agencies across California have widely varying levels of preparedness for major disasters, and nearly all agencies do not have the public resources to adequately and swiftly evacuate all populations in danger. To holistically address these challenges and bolster current disaster and evacuation planning, preparedness, and response in California, we summarize the evacuations of eleven major wildfires in California between 2017 and 2019 and offer a cross-comparison to highlight key similarities and differences. We present results of new empirical data we collected via an online survey of individuals impacted by: 1) the 2017 October Northern California Wildfires (n=79), 2) the 2017 December Southern California Wildfires (n=226), and 3) the 2018 Carr Wildfire (n=284). These data reveal the decision-making of individuals in these wildfires including choices related to evacuating or staying, departure timing, route, sheltering, destination, transportation mode, and reentry timing. We also present results related to communication and messaging, non-evacuee behavior, and opinion of government response. Using the summarized case studies and empirical evidence, we present a series of recommendations for agencies to prepare for, respond to, and recover from wildfires

The state of the art of cooperative and connected autonomous vehicles from the future mobility management perspective:a systematic review

© 2022 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/futuretransp2030032Cooperative and connected autonomous vehicles (CCAVs) are considered to be a promising solution for addressing congestion and other operational deficiencies, as part of a holistic future mobility management framework. As a result, a significant number of studies have recently been published on this topic. From the perspective of future mobility management, this review paper discusses three themes, which are traffic management, network performance, and mobility management, including congestion, and incident detection using the PRISMA methodology. Three databases were considered for this study, and peer-reviewed primary studies were selected that were published within the last 10 years in the English language, focusing on CCAV in the context of the future transportation and mobility management perspective. For synthesis and interpretation, like-for-like comparisons were made among studies; it was found that extensive research-supported information is required to ensure a smooth transition from conventional vehicles to the CCAVs regime, to achieve the projected traffic and environmental benefits. Research investigations are ongoing to optimize these benefits and associated goals via the setting of different models and simulations. The tools and technologies for the testing and simulation of CCAV were found to have limited capacity. Following the review of the current state-of-the-art, recommendations for future research have been discussed. The most notable is the need for large-scale simulations to understand the impact of CCAVs beyond corridor-based and small-scale networks, the need for understanding the interactions between the drivers of CCAVs and traffic management centers, and the need to assess the technological transition, as far as infrastructure systems are concerned, that is necessary for the progressive penetration of CCAVs into traffic streams.This research was funded by European Union’s Horizon 2020 research and innovation program, grant number 955317.Published onlin