Development of Model-based Transit Signal Priority Control for local Arterials

AbstractThis paper presents a transit signal priority (TSP) model designed to benefit both bus riders and passenger-car users. Most of conventional priority methods are applied at the isolated intersection. However, this kind of control strategies may failed to reduce the travel time since the prioritized buses have to stop at the downstream intersections. Therefore, along the line of headway-based research, this study intends to develop a new TSP control approach with the concerns of bus passenger delay on the entire arterial. Moreover, a basic method for queue length estimation is presented to evaluate the impacts of TSP control on passenger cars. The control objective is to minimize bus passenger waiting time at the downstream bus stop, simultaneously ensuring the total person delay of entire intersection is not increased. Using the microscopic simulation, the proposed strategy has shown its benefits in reducing bus passenger waiting time and total intersection delay

Decentralized Traffic Management: A Synchronization-Based Intersection Control

International audienceControlling the vehicle traffic in large networks remains an important challenge in urban environments and transportation systems. Autonomous vehicles are today considered as a promising approach to deal with traffic control. In this paper, we propose a synchronization-based intersection control mechanism to allow the autonomous vehicle-agents to cross without stopping, i.e., in order to avoid congestions (delays) and energy loss. We decentralize the problem by managing the traffic of each intersection independently from others. We define control agents which are able to synchronize the multiple flows of vehicles in each intersection, by alternating vehicles from both directions. We present experimental results in simulation, which allow to evaluate the approach and to compare it with a traffic light strategy. These results show the important gain in terms of time and energy at an intersection and in a network

Croisement synchronisé de flux de véhicules autonomes dans un réseau

National audienceLes véhicules autonomes sont aujourd'hui considérés comme une approche prometteuse pour le transport des ressources et la régulation du trafic. Dans cet article, nous examinons la possibilité de faire croiser des flux de véhicules autonomes sans les arrêter afin d'éviter les congestions (retards) et la perte d'énergie. Nous proposons un contrôle aux intersections basé sur la synchronisation temporelle des véhicules. Nous décentralisons le problème en gérant indépendamment chaque intersection. Nous définissons un agent de contrôle qui est capable de synchroniser les véhicules arrivant sur une intersection, en assurant l'alternance entre les flux. Nous présentons un simulateur qui permet d'évaluer l'approche et de la comparer avec la stratégie standard des feux de circulation. Les résultats expérimentaux montrent un gain important en termes de temps et d'énergie pour les véhicules à une intersection et dans un réseau

Optimization Model of Transit Signal Priority Control for Intersection and Downstream Bus Stop

Transit signal priority has a positive effect on improving traffic condition and level of transit service in the urban area. In this paper, a passenger-based transit signal priority (TSP) optimization model is formulated to optimize intersection signal phasing based on minimizing accessibility-based passenger delay at the intersection and increased waiting-delay at the downstream bus stop simultaneously. Genetic Algorithm is utilized to calculate passenger-based optimization model that is calibrated by evening rush hour actual traffic data (17:30–18:30, October 13th–October 15th, 2015) along Shuiximen Boulevard in Nanjing, China. The performance of the proposed optimization model in decreasing delay and improving system reliability is simulated and evaluated by VISSIM-based simulation platform, and the results illustrate that the proposed optimization model presents promising outcomes in decreasing accessibility-based passenger delay at intersection (average reduction of 12%) and passenger waiting-delay at downstream bus service stop (average reduction of 18%) compared with traditional vehicle-based TSP optimization method in rush hour

The State of the Art in Smart City Research – A Literature Analysis on Green IS Solutions to Foster Environmental Sustainability

Environmental sustainability is one of the most critical issues worldwide, concerning every individual. The main objective in this area is to preserve scarce resources and reduce CO2 emissions in order to prevent environmental degradation. In recent years the potential of information systems (IS) as a driver for environmental sustainability has emerged under the term “Green IS”. Given that cities represent a huge share of environmental degradation due to factors such as mobility, energy and water consumption, and waste production, the municipal domain offers huge potentials in terms of sustainability. The advent of smart cites is an attempt to address this concern. In this paper we aim to provide an overview of current publications on environmental sustainability in smart cities, as research in this field is still unstructured. This paper focuses on structuring the research field by providing a research framework to achieve a more holistic view on the application of Green IS. We distinguish between research performed by the IS community and that of related fields, such as urban development, and perform a cross-sectional, exhaustive literature analysis with almost 1,500 articles to uncover the differences and commonalities between the domains

Decentralized Traffic Management: A Synchronization-Based Intersection Control --- Extended Version

Controlling the vehicle traffic in large networks remains an important challenge in urban environments and transportation systems. Autonomous vehicles are today considered as a promising approach to deal with traffic control. In this paper, we propose a synchronization-based intersection control mechanism to allow the autonomous vehicle-agents to cross without stopping, i.e., in order to avoid congestions (delays) and energy loss. We decentralize the problem by managing the traffic of each intersection independently from others. We define control agents which are able to synchronize the multiple flows of vehicles in each intersection, by alternating vehicles from both directions. We present experimental results in simulation, which allow to evaluate the approach and to compare it with a traffic light strategy. These results show the important gain in terms of time and energy at an intersection and in a network.Contrôler le trafic dans les grands réseaux reste un défi important dans les milieux urbains et les systèmes de transport. Les véhicules autonomes sont aujourd'hui considérés comme une approche prometteuse pour fluidifier le trafic. Dans cet article, nous proposons un mécanisme de contrôle d'intersection fondé sur la synchronisation pour permettre aux véhicules-agents autonomes de traverser sans s'arrêter afin d'éviter les congestions (retards) et la perte d'énergie. Nous décentralisons le problème en gérant le trafic de chaque intersection indépendamment des autres. Nous définissons des agents de contrôle qui sont capables de synchroniser les multiples flux de véhicules à chaque intersection, en alternant les véhicules des deux routes. Nous présentons des résultats expérimentaux mesurés en simulation, lesquels permettent d'évaluer l'approche et de la comparer à une stratégie plus classique basée sur les feux de circulation. Ces résultats montrent le gain important en termes de temps et d'énergie à une intersection et dans un réseau

A new approach for co-operative bus priority at traffic signals

Bus priority at traffic signals is a growing area of co-operative transport system applications. Interest in bus priority continues to grow as the Cities pay more attention to the needs of buses to provide fast, frequent and reliable services thus contributing to a sustainable transport system. Bus priority at traffic signals is particularly favoured at places where road space is limited and traffic signal density is high. With increasing use of Automatic Vehicle Location (AVL) systems, it is now possible to provide ‘differential’ priority, where different levels of priority can be awarded to buses at traffic signals according to chosen criteria (e.g. to improve regularity). At present, common strategies are based on the comparison of the time headway of a bus with the scheduled headway. However, this paper shows that greater regularity benefits could be achieved through a strategy where priority for a bus is based not only on its own headway, but also the headway of the bus behind. This paper demonstrates the benefits of this on a theoretical basis and quantifies the benefits from simulation modeling of a high frequency bus route. Such a strategy provides an opportunity to exploit the more detailed location information available from the growing number of AVL-based systems for buses being implemented around the world

Sistemi di priorità semaforica per il trasporto pubblico nelle reti stradali

La continua crescita dei centri urbani, l’aumento della popolazione e la tendenza a preferire gli spostamenti con mezzi privati rendono la congestione stradale un fenomeno sempre più frequente e problematico. Una tipologia di interventi utile per contrastare tale fenomeno consiste nel migliorare le performance dei sistemi di trasporto pubblico per renderli più attrattivi, spesso però con limitati budget a disposizione. Di particolare interesse in questo ambito sono i sistemi di priorità semaforica per il trasporto pubblico (bus e tram), che vengono descritti nel presente lavoro. Tali sistemi, diminuendo o annullando i ritardi dovuti alla presenza di intersezioni semaforizzate, consentono di ridurre i tempi totali di percorrenza dei mezzi pubblici, aumentando quindi l’affidabilità e l’attrattività del servizio. Dopo una descrizione delle diverse strategie di preferenziamento e dei criteri di modifica dei piani semaforici, vengono evidenziati gli elementi organizzativi e tecnologici necessari per la loro attuazione. Sulla base di alcuni studi disponibili in letteratura, vengono analizzati i benefici e gli impatti negativi che queste strategie generano per i mezzi pubblici e per le altre componenti del traffico veicolare, evidenziando i principali fattori che ne influenzano l’efficacia. Vengono infine presentati alcuni casi di applicazione riferiti a città italiane e internazionali nelle quali sono stati implementati interventi finalizzati all’assegnazione della priorità semaforica per i mezzi pubblici

MAVEN Deliverable 7.2: Impact Assessment - Technical Report

This deliverable focuses on an important topic within the MAVEN project - evaluation of the project impact. This is an important step that will allow us to say what the results and impact of the different technologies, functionalities as well as assumptions are. It covers different dimensions of the impact assessment as stated in the Deliverable D7.1 - Impact assessment plan [10]. The field tests proved that the technology in the vehicle works together with the infrastructure and the solution is technically feasible. This was demonstrated also during particular events and is reported in the attached test protocols. At the same time, the emulation and simulation in Dominion software proved the functionality, for example with respect to the cooperative perception or safety indicators. The tests also proved that the key performance indicator "minimum time to the collision" decreases when applying the cooperative sensing. Also, the number of human interventions needed was zero in all the tests. This deliverable also discussed selected results of a detailed user survey aiming at understanding the expected impacts and transition of automated vehicles. The overall number of respondents reached 209. The responses have revealed some interesting facts. For example, over 80% of the respondents believe that CAVs will decrease the number of traffic accidents. Similarly, about 70% of the respondents expect improvements in traffic congestions. Over 82% of respondents declared that they would accept some detour when driving if it helps the overall traffic situation. The literature review, however, indicated that autonomous vehicles will have either a positive or a negative effect on the environment, depending on the policies. For example, opening cars as a mode of transport to new user groups (seniors, children etc.) together with improvements of the traffic, flow parameters can increase the traffic volume on roads. Policy makers shall focus on the integration of the CAVs into a broader policy concept including car or ride-sharing, electromobility and others. In order to evaluate the transition, for example, the influence of different penetration rates of CAVs on the performance, a microscopic traffic simulation was performed. Here the particular MAVEN use cases, as well as their combination, was addressed. The results of the simulation are rather promising. The potential for improvements in traffic performance is clearly there. It was demonstrated that a proper integration of CAVs into city traffic management can, for example, help with respect to the environmental goals (Climate Action of the European Commission) and reduce CO2 emissions by up to 12 % (a combination of GLOSA and signal optimization). On corridors with a green wave, a capacity increase of up to 34% was achieved. The conclusions from this project can be used not only by other researchers but mainly by traffic managers and decision-makers in cities. The findings can get a better idea about the real impacts of particular use cases (such as green wave, GLOSA and others) in the cities. An important added value is also the focus on the transition phase. It was demonstrated that already for lower penetration rates (even 20% penetration of automated vehicles), there are significant improvements in traffic performance. For example, the platooning leads to a decrease of CO2 emissions of 2,6% or the impact indicator by 17,7%

Development and Evaluation of An Adaptive Transit Signal Priority System Using Connected Vehicle Technology

Transit signal priority (TSP) can be a very effective preferential treatment for transit vehicles in congested urban networks. There are two problems with the current practice of the transit signal priority. First, random bus arrival time is not sufficiently accounted for, which’ve become the major hindrance in practice for implementing active or adaptive TSP strategies when a near-side bus stop is present. Secondly, most research focuses on providing bus priority at local intersection level, but bus schedule reliability should be achieved at route level and relevant studies have been lacking. In the first part of this research, a stochastic mixed-integer nonlinear programming (SMINP) model is developed to explicitly to account for uncertain bus arrival time. A queue delay algorithm is developed as the supporting algorithm for SMINP to capture the delays caused by the interactions between vehicle queues and buses entering and exiting near-side bus stops. A concept of using signal timing deviations to approximate the impacts of TSP operations on other traffic is proposed for the first time in this research. In the second part of the research, the deterministic version of the SMINP model is extended to the arterial setting, where a route-based TSP (R-TSP) model is develop to optimize for schedule-related bus performances on the corridor level. The R-TSP model uses the real-time data available only from the connected vehicle communications technology. Based on the connected vehicle technology, a real-time signal control system that implements the proposed TSP models is prototyped in the simulation environment. The connected vehicle technology is also used as the main detection and monitoring mechanism for the real-time control of the adaptive TSP signal system. The adaptive TSP control module is designed as a plug-in module that is envisioned to work with a modern fixed-time or adaptive signal controller with connected vehicle communications capabilities. Using this TSP-enabled signal control system, simulation studies were carried out in both a single intersection setting and a five-intersection arterial setting. The effectiveness of the SMINP model to handle uncertain bus arrival time and the R-TSP model to achieve corridor-level bus schedule reliability were studied. Discussions, conclusions and future research on the topic of adaptive TSP models were made