GPS navigators are now present in most vehicles and smartphones. The usual goal of these navigators is to take the user in less time or distance to a destination. However, the global use of navigators in a given city could lead to traffic jams as they have a highly biased preference for some streets. From a general point of view, spreading the traffic throughout the city could be a way of preventing jams and making a better use of public resources. We propose a way of calculating alternative routes to be assigned by these devices in order to foster a better use of the streets. Our experimentation involves maps from OpenStreetMap, real road traffic, and the microsimulator SUMO. We contribute to reducing travel times, greenhouse gas emissions, and fuel consumption. To analyze the sociological aspect of any innovation, we analyze the penetration (acceptance) rate which shows that our proposal is competitive even when just 10% of the drivers are using it.
http://doi.acm.org/10.1145/3071178.3071193
Fine Tuning of Traffic in Our Cities with Smart Panels: The Quito City Case S...Daniel H. Stolfi
In this article we work towards the desired future smart city in which IT and knowledge will hopefully provide a highly livable environment for citizens. To this end, we test a new concept based on intelligent LED panels (the Yellow Swarm) to guide drivers when moving through urban streets so as to finally get rid of traffic jams and protect the environment. This is a minimally invasive, low cost idea for the city that needs advanced simulations with real data coupled with new algorithms which perform well. Our proposal is to use evolutionary computation in the Yellow Swarm, which will finally help alleviate the traffic congestion, improve travel times, and decrease gas emissions, all at the same time and for a real case like the city of Quito (Ecuador).
http://doi.acm.org/10.1145/2908812.2908868
This PhD thesis presents a summary of the research work done with the aim of addressing and solving Smart Mobility problems in a smart city context. Several big cities are modeled to be optimized using new evolutionary techniques and the traffic simulator SUMO. Three new architectures, Red Swarm, Green Swarm and Yellow Swarm are proposed, analyzed and used to reduce travel times, greenhouse gas emissions, and fuel consumption of vehicles. A new method for calculating alternative routes for GPS navigators and the prediction of car park occupancy rates are also included in this PhD thesis. Moreover, a novel algorithm for generating realistic traffic flows is developed and tested in different scenarios: working
days, Saturdays, and Sundays. Finally, a new family of bio-inspired algorithms based on epigenesis was designed and tested on the Multidimensional Knapsack Problem and used in the Yellow Swarm architecture.
https://hdl.handle.net/10630/17299
Two models are present, the first is point to point model and demonstrated the minimizing cost issue, while the other model is Multi-stops operating model, and it is addressing profit maximization.
Vehicle routing and scheduling Models:
Travelling salesman problem
vehicle routing problem with time window
Pick up and delivery problem with time window
Route optimization algorithm are the mathematical formula that solve routing problems..
Some types of routing:
1) Vehicle Routing Problem (VRP)
2) Traveling Salesman Problem (TSP)
3) Ant Colony Optimization (ACO)
Fine Tuning of Traffic in Our Cities with Smart Panels: The Quito City Case S...Daniel H. Stolfi
In this article we work towards the desired future smart city in which IT and knowledge will hopefully provide a highly livable environment for citizens. To this end, we test a new concept based on intelligent LED panels (the Yellow Swarm) to guide drivers when moving through urban streets so as to finally get rid of traffic jams and protect the environment. This is a minimally invasive, low cost idea for the city that needs advanced simulations with real data coupled with new algorithms which perform well. Our proposal is to use evolutionary computation in the Yellow Swarm, which will finally help alleviate the traffic congestion, improve travel times, and decrease gas emissions, all at the same time and for a real case like the city of Quito (Ecuador).
http://doi.acm.org/10.1145/2908812.2908868
This PhD thesis presents a summary of the research work done with the aim of addressing and solving Smart Mobility problems in a smart city context. Several big cities are modeled to be optimized using new evolutionary techniques and the traffic simulator SUMO. Three new architectures, Red Swarm, Green Swarm and Yellow Swarm are proposed, analyzed and used to reduce travel times, greenhouse gas emissions, and fuel consumption of vehicles. A new method for calculating alternative routes for GPS navigators and the prediction of car park occupancy rates are also included in this PhD thesis. Moreover, a novel algorithm for generating realistic traffic flows is developed and tested in different scenarios: working
days, Saturdays, and Sundays. Finally, a new family of bio-inspired algorithms based on epigenesis was designed and tested on the Multidimensional Knapsack Problem and used in the Yellow Swarm architecture.
https://hdl.handle.net/10630/17299
Two models are present, the first is point to point model and demonstrated the minimizing cost issue, while the other model is Multi-stops operating model, and it is addressing profit maximization.
Vehicle routing and scheduling Models:
Travelling salesman problem
vehicle routing problem with time window
Pick up and delivery problem with time window
Route optimization algorithm are the mathematical formula that solve routing problems..
Some types of routing:
1) Vehicle Routing Problem (VRP)
2) Traveling Salesman Problem (TSP)
3) Ant Colony Optimization (ACO)
An Evolutionary Algorithm to Generate Real Urban Traffic FlowsDaniel H. Stolfi
In this article we present a strategy based on an evolutionary algorithm to calculate the real vehicle flows in cities according to data from sensors placed in the streets. We have worked with a map imported from OpenStreetMap into the SUMO traffic simulator so that the resulting scenarios can be used to perform different optimizations with the confidence of being working with a traffic distribution close to reality. We have compared the result of our algorithm to other competitors and achieved results that replicate the real traffic distribution with a precision higher than 90%.
http://dx.doi.org/10.1007/978-3-319-24598-0_30
Reducing Gas Emissions in Smart Cities by Using the Red Swarm Architecture (C...Daniel H. Stolfi
The aim of the work presented here is to reduce gas emissions in modern cities by creating a light infrastructure of WiFi intelligent spots informing drivers of customized, real-time routes to their destinations. The reduction of gas emissions is an important aspect of smart cities, since it directly affects the health of citizens as well as the environmental impact of road traffic. We have built a real scenario of the city of Malaga (Spain) by using OpenStreetMap (OSM) and the SUMO road traffic microsimulator, and solved it by using an efficient new Evolutionary Algorithm (EA). Thus, we are dealing with a real city (not just a roundabout, as found in the literature) and we can therefore measure the emissions of cars in movement according to traffic regulations (real human scenarios). Our results suggest an important reduction in gas emissions (10%) and travel times (9%) is possible when vehicles are rerouted by using the Red Swarm architecture. Our approach is even competitive with human expert’s solutions to the same problem.
http://dx.doi.org/10.1007/978-3-642-40643-0_30
Predicting Car Park Occupancy Rates in Smart CitiesDaniel H. Stolfi
In this article we address the study of parking occupancy data published by the Birmingham city council with the aim of testing several prediction strategies (polynomial fitting, Fourier series, k-means clustering, and time series) and analyzing their results. We have used cross validation to train the predictors and then tested them on unseen occupancy data. Additionally, we present a web page prototype to visualize the current and historical parking data on a map, allowing users to consult the occupancy rate forecast to satisfy their parking needs up to one day in advance. We think that the combination of accurate intelligent techniques plus final user services for citizens is the direction to follow for knowledge-based real smart cities.
http://dx.doi.org/10.1007/978-3-319-59513-9_11
Un Algoritmo Evolutivo para la Reducción de Tiempos de Viaje y Emisiones Util...Daniel H. Stolfi
En este trabajo proponemos la arquitectura Yellow Swarm dedicada a la reducción de los tiempos de viaje del tráfico rodado mediante la utilización de una serie de paneles LED con el fin de sugerir diferentes cambios de dirección durante determinadas ventanas de tiempo. Estos tiempos son calculados por un algoritmo evolutivo diseñado expresamente para este trabajo, el cual evalúa los escenarios compuestos de mapas reales importados desde OpenStreetMap, mediante la utilización del simulador SUMO. Los resultados de nuestra experimentación, sobre una zona de la ciudad de Málaga propensa a sufrir atascos, muestran acortamientos de los tiempos medios de viaje de hasta 24,6 %, una reducción en las emisiones de gases de efecto invernadero de hasta 24,1 %, y una disminución máxima del consumo de combustible del 12,6 %.
Red Swarm: Smart Mobility in Cities with EAs (GECCO'13)Daniel H. Stolfi
This work presents an original approach to regulate traffic by using an on-line system controlled by an EA. Our proposal uses computational spots with WiFi connectivity located at traffic lights (the Red Swarm), which are used to suggest alternative individual routes to vehicles. An evolutionary algorithm is also proposed in order to find a configuration for the Red Swarm spots which reduces the travel time of the vehicles and also prevents traffic jams. We solve real scenarios in the city of Malaga (Spain), thus enriching the OpenStreetMap info by adding traffic lights, sensors, routes and vehicle flows. The result is then imported into the SUMO traffic simulator to be used as a method for calculating the fitness of solutions. Our results are competitive compared to the common solutions from experts in terms of travel and stop time, and also with respect to other similar proposals but with the added value of solving a real, big instance.
http://dx.doi.org/10.1145/2463372.2463540
Eco-friendly Reduction of Travel Times in European Smart Cities (GECCO'14)Daniel H. Stolfi
This article proposes an innovative solution for reducing polluting gas emissions from road traffic in modern cities. It is based on our new Red Swarm architecture which is composed of a series of intelligent spots with WiFi connections that can suggest a customized route to drivers. We have tested our proposal in four different case studies corresponding to actual European smart cities. To this end, we first import the city information from OpenStreetMap into the SUMO road traffic micro-simulator, propose a Red Swarm architecture based on intelligent spots located at traffic lights, and then optimize the resulting system in terms of travel times and gas emissions by using an evolutionary algorithm. Our results show that an important quantitative reduction in gas emissions as well as in travel times can be achieved when vehicles are rerouted according to our Red Swarm indications. This represents a promising result for the low cost implementation of an idea that could engage the interest of both citizens and municipal authorities.
http://dx.doi.org/10.1145/2576768.2598317
Smart Mobility Policies with Evolutionary Algorithms: The Adapting Info Panel...Daniel H. Stolfi
In this article we propose the Yellow Swarm architecture for reducing travel times, greenhouse gas emissions and fuel consumption of road traffic by using several LED panels to suggest changes in the direction of vehicles (detours) for different time slots. These time intervals are calculated using an evolutionary algorithm, specifically designed for our proposal, which evaluates many working scenarios based on real cities, imported from OpenStreetMap into the SUMO traffic simulator. Our results show an improvement in average travel times, emissions, and fuel consumption even when only a small percentage of drivers follow the indications provided by our panels.
http://doi.acm.org/10.1145/2739480.2754742
CycleStreets: Our Story - presentation to Net2Camb eventCycleStreets
Here is our presentation at the Net2Camb event.
See:
http://www.cyclestreets.net/blog/2010/12/29/net2camb-meetup-building-cyclestreets/
http://net2camb.org/2011/01/january-net2camb-meetup-building-cyclestreets/
Walkalytics - Reachability Analysis for your businessStephan Heuel
Walking is the most natural mode of transportation. It is available everywhere and is usually the first and last part of a journey, whether long or short. We have developed an area-based approach for computing the paths and reachability for pedestrians, calculated to an accuracy of just a few meters.
We use heterogeneous data sources and can even model desire paths which are not explicitly mapped in the base data. In particular, we do not rely on a consistent routing network.
Building smart green mobility in South Tyrol through an open data hubSpeck&Tech
ABSTRACT: For decades the traditional approach for solving mobility and transportation challenges has been based on the idea of creating new road or rail infrastructures. Thanks to the impressive enhancement of intelligent transportation systems (ITS) technologies, in the last years this approach is going into the direction of rather improving the efficiency of how available transportation infrastructure is used. New digital infrastructures allow all mobility actors (vehicles, pedestrians, sensors, traffic management centers) to cooperate together to achieve the ambitious goal of improving mobility, enhancing safety, reducing congestion and environmental impacts. But how can we achieve this and ensure that public and private actors efficiently work together? In South Tyrol we have tried to give an answer to these challenges through the implementation of an open data hub, which enables the real-time data / information exchange among all interested parties and fosters the multiplication of development of research & innovation projects between local companies, research centers and public organizations. After years of implementation, the Open Data Hub South Tyrol is now creating the premises for a new historical phase for mobility in the region, with concepts like Mobility-as-a-Service or environmental traffic management that are finally moving from research to deployment.
BIO: Roberto Cavaliere is an ITS Project Manager at NOI Techpark Südtirol / Alto Adige, a public-owned organization in the Italian alpine region of South Tyrol coordinating the NOI Tech Park and with the mission to drive and foster research & innovation in the region. Roberto is the reference person in NOI for all initiatives in the field of ITS and smart mobility and in the last 10 years has coordinated a relevant number of EU-funded projects in this field. His main interests cover cooperative systems, autonomous driving, ITS for the environment, mobility-as-a-service and sharing mobility, road weather information systems (RWIS).
Routing, scheduling, and dispatching are critical in keeping operations running smoothly and at lowest cost. Providing optimal drive routes between a set of locations is a key factor in reducing operating costs for numerous industries (fleet vehicles, transportation, currier services, home delivery). In this session, we’ll discuss routing technology, demonstrate routing applications, and discuss how advances in mobile technology have enabled a cost effective routing and real-time asset tracking solution.
On/Off Road Cycle Infrastructure Review - Urban
Venue: Glasgow - Cycling Scotland Office
Site Visit: Glasgow Connect 2 Cycle Infrastructure
Date: Wednesday 31st August 2011
Start Time 9.30am
Brief Description: Review of Connect 2 infrastructure installed within Glasgow. This will be completed by a series of workshops on designing for cyclists looking in depth at current design manuals and providing a more technical review of current standards. Site visits will be used to review the infrastructure completing the day with a feedback session on the installed infrastructure.
Innovatie estafette DEMO Consultants - TNO- Gemeente Rotterdam - 2013DEMOConsultants
Presentation Innovation Estafette 2013 about Urban Infra Strategy, Smart Cities, BIM and GIS for low-disturbance urban infrastructure projects and the research results of EU project PANTURA.
By DEMO Consultants, TNO and City of Rotterdam
The presentation was illustrated at the CEEM CoP Webinar: “Achieving Low Carbon Mobility: Urban Transportation Modelling, Public Awareness and Behavioural Change" on tge 10th of October 2013
CEEM CoP stands for Community Energy and Emissions Modelling (CEEM) Community of Practice (CoP).
CEEM CoP is an informal group supporting CEEM practitioners and local governments in furthering greenhouse gas modelling, target-setting and action in communities across BC – www.toolkit.bc.ca/ceem
Mobility is an important part of daily life. Progressive community planning and transportation design can greatly reduce the need for automobile travel, instead providing a diverse range of active transportation alternatives.
This presentation on the CATCH project looks at how transportation-related data can be used to understand a city’s travel footprint and help to inform city planning and programs to promote individual behaviour change.
It reviews the findings and lessons learned from the ‘CATCH Project’ (Carbon Aware Travel Choice): a 2 million euro-funded project, involving 11 partners across 6 European Union countries, aimed to develop a knowledge platform to help urban communities move to less carbon-intensive transportation systems. This presentation touches on the important role of developing a system to compare and contrast best practices, identify the many motivators for change to low carbon mobility, and use tools for engaging the public and decision makers to support innovation and change.
An Evolutionary Algorithm to Generate Real Urban Traffic FlowsDaniel H. Stolfi
In this article we present a strategy based on an evolutionary algorithm to calculate the real vehicle flows in cities according to data from sensors placed in the streets. We have worked with a map imported from OpenStreetMap into the SUMO traffic simulator so that the resulting scenarios can be used to perform different optimizations with the confidence of being working with a traffic distribution close to reality. We have compared the result of our algorithm to other competitors and achieved results that replicate the real traffic distribution with a precision higher than 90%.
http://dx.doi.org/10.1007/978-3-319-24598-0_30
Reducing Gas Emissions in Smart Cities by Using the Red Swarm Architecture (C...Daniel H. Stolfi
The aim of the work presented here is to reduce gas emissions in modern cities by creating a light infrastructure of WiFi intelligent spots informing drivers of customized, real-time routes to their destinations. The reduction of gas emissions is an important aspect of smart cities, since it directly affects the health of citizens as well as the environmental impact of road traffic. We have built a real scenario of the city of Malaga (Spain) by using OpenStreetMap (OSM) and the SUMO road traffic microsimulator, and solved it by using an efficient new Evolutionary Algorithm (EA). Thus, we are dealing with a real city (not just a roundabout, as found in the literature) and we can therefore measure the emissions of cars in movement according to traffic regulations (real human scenarios). Our results suggest an important reduction in gas emissions (10%) and travel times (9%) is possible when vehicles are rerouted by using the Red Swarm architecture. Our approach is even competitive with human expert’s solutions to the same problem.
http://dx.doi.org/10.1007/978-3-642-40643-0_30
Predicting Car Park Occupancy Rates in Smart CitiesDaniel H. Stolfi
In this article we address the study of parking occupancy data published by the Birmingham city council with the aim of testing several prediction strategies (polynomial fitting, Fourier series, k-means clustering, and time series) and analyzing their results. We have used cross validation to train the predictors and then tested them on unseen occupancy data. Additionally, we present a web page prototype to visualize the current and historical parking data on a map, allowing users to consult the occupancy rate forecast to satisfy their parking needs up to one day in advance. We think that the combination of accurate intelligent techniques plus final user services for citizens is the direction to follow for knowledge-based real smart cities.
http://dx.doi.org/10.1007/978-3-319-59513-9_11
Un Algoritmo Evolutivo para la Reducción de Tiempos de Viaje y Emisiones Util...Daniel H. Stolfi
En este trabajo proponemos la arquitectura Yellow Swarm dedicada a la reducción de los tiempos de viaje del tráfico rodado mediante la utilización de una serie de paneles LED con el fin de sugerir diferentes cambios de dirección durante determinadas ventanas de tiempo. Estos tiempos son calculados por un algoritmo evolutivo diseñado expresamente para este trabajo, el cual evalúa los escenarios compuestos de mapas reales importados desde OpenStreetMap, mediante la utilización del simulador SUMO. Los resultados de nuestra experimentación, sobre una zona de la ciudad de Málaga propensa a sufrir atascos, muestran acortamientos de los tiempos medios de viaje de hasta 24,6 %, una reducción en las emisiones de gases de efecto invernadero de hasta 24,1 %, y una disminución máxima del consumo de combustible del 12,6 %.
Red Swarm: Smart Mobility in Cities with EAs (GECCO'13)Daniel H. Stolfi
This work presents an original approach to regulate traffic by using an on-line system controlled by an EA. Our proposal uses computational spots with WiFi connectivity located at traffic lights (the Red Swarm), which are used to suggest alternative individual routes to vehicles. An evolutionary algorithm is also proposed in order to find a configuration for the Red Swarm spots which reduces the travel time of the vehicles and also prevents traffic jams. We solve real scenarios in the city of Malaga (Spain), thus enriching the OpenStreetMap info by adding traffic lights, sensors, routes and vehicle flows. The result is then imported into the SUMO traffic simulator to be used as a method for calculating the fitness of solutions. Our results are competitive compared to the common solutions from experts in terms of travel and stop time, and also with respect to other similar proposals but with the added value of solving a real, big instance.
http://dx.doi.org/10.1145/2463372.2463540
Eco-friendly Reduction of Travel Times in European Smart Cities (GECCO'14)Daniel H. Stolfi
This article proposes an innovative solution for reducing polluting gas emissions from road traffic in modern cities. It is based on our new Red Swarm architecture which is composed of a series of intelligent spots with WiFi connections that can suggest a customized route to drivers. We have tested our proposal in four different case studies corresponding to actual European smart cities. To this end, we first import the city information from OpenStreetMap into the SUMO road traffic micro-simulator, propose a Red Swarm architecture based on intelligent spots located at traffic lights, and then optimize the resulting system in terms of travel times and gas emissions by using an evolutionary algorithm. Our results show that an important quantitative reduction in gas emissions as well as in travel times can be achieved when vehicles are rerouted according to our Red Swarm indications. This represents a promising result for the low cost implementation of an idea that could engage the interest of both citizens and municipal authorities.
http://dx.doi.org/10.1145/2576768.2598317
Smart Mobility Policies with Evolutionary Algorithms: The Adapting Info Panel...Daniel H. Stolfi
In this article we propose the Yellow Swarm architecture for reducing travel times, greenhouse gas emissions and fuel consumption of road traffic by using several LED panels to suggest changes in the direction of vehicles (detours) for different time slots. These time intervals are calculated using an evolutionary algorithm, specifically designed for our proposal, which evaluates many working scenarios based on real cities, imported from OpenStreetMap into the SUMO traffic simulator. Our results show an improvement in average travel times, emissions, and fuel consumption even when only a small percentage of drivers follow the indications provided by our panels.
http://doi.acm.org/10.1145/2739480.2754742
CycleStreets: Our Story - presentation to Net2Camb eventCycleStreets
Here is our presentation at the Net2Camb event.
See:
http://www.cyclestreets.net/blog/2010/12/29/net2camb-meetup-building-cyclestreets/
http://net2camb.org/2011/01/january-net2camb-meetup-building-cyclestreets/
Walkalytics - Reachability Analysis for your businessStephan Heuel
Walking is the most natural mode of transportation. It is available everywhere and is usually the first and last part of a journey, whether long or short. We have developed an area-based approach for computing the paths and reachability for pedestrians, calculated to an accuracy of just a few meters.
We use heterogeneous data sources and can even model desire paths which are not explicitly mapped in the base data. In particular, we do not rely on a consistent routing network.
Building smart green mobility in South Tyrol through an open data hubSpeck&Tech
ABSTRACT: For decades the traditional approach for solving mobility and transportation challenges has been based on the idea of creating new road or rail infrastructures. Thanks to the impressive enhancement of intelligent transportation systems (ITS) technologies, in the last years this approach is going into the direction of rather improving the efficiency of how available transportation infrastructure is used. New digital infrastructures allow all mobility actors (vehicles, pedestrians, sensors, traffic management centers) to cooperate together to achieve the ambitious goal of improving mobility, enhancing safety, reducing congestion and environmental impacts. But how can we achieve this and ensure that public and private actors efficiently work together? In South Tyrol we have tried to give an answer to these challenges through the implementation of an open data hub, which enables the real-time data / information exchange among all interested parties and fosters the multiplication of development of research & innovation projects between local companies, research centers and public organizations. After years of implementation, the Open Data Hub South Tyrol is now creating the premises for a new historical phase for mobility in the region, with concepts like Mobility-as-a-Service or environmental traffic management that are finally moving from research to deployment.
BIO: Roberto Cavaliere is an ITS Project Manager at NOI Techpark Südtirol / Alto Adige, a public-owned organization in the Italian alpine region of South Tyrol coordinating the NOI Tech Park and with the mission to drive and foster research & innovation in the region. Roberto is the reference person in NOI for all initiatives in the field of ITS and smart mobility and in the last 10 years has coordinated a relevant number of EU-funded projects in this field. His main interests cover cooperative systems, autonomous driving, ITS for the environment, mobility-as-a-service and sharing mobility, road weather information systems (RWIS).
Routing, scheduling, and dispatching are critical in keeping operations running smoothly and at lowest cost. Providing optimal drive routes between a set of locations is a key factor in reducing operating costs for numerous industries (fleet vehicles, transportation, currier services, home delivery). In this session, we’ll discuss routing technology, demonstrate routing applications, and discuss how advances in mobile technology have enabled a cost effective routing and real-time asset tracking solution.
On/Off Road Cycle Infrastructure Review - Urban
Venue: Glasgow - Cycling Scotland Office
Site Visit: Glasgow Connect 2 Cycle Infrastructure
Date: Wednesday 31st August 2011
Start Time 9.30am
Brief Description: Review of Connect 2 infrastructure installed within Glasgow. This will be completed by a series of workshops on designing for cyclists looking in depth at current design manuals and providing a more technical review of current standards. Site visits will be used to review the infrastructure completing the day with a feedback session on the installed infrastructure.
Innovatie estafette DEMO Consultants - TNO- Gemeente Rotterdam - 2013DEMOConsultants
Presentation Innovation Estafette 2013 about Urban Infra Strategy, Smart Cities, BIM and GIS for low-disturbance urban infrastructure projects and the research results of EU project PANTURA.
By DEMO Consultants, TNO and City of Rotterdam
The presentation was illustrated at the CEEM CoP Webinar: “Achieving Low Carbon Mobility: Urban Transportation Modelling, Public Awareness and Behavioural Change" on tge 10th of October 2013
CEEM CoP stands for Community Energy and Emissions Modelling (CEEM) Community of Practice (CoP).
CEEM CoP is an informal group supporting CEEM practitioners and local governments in furthering greenhouse gas modelling, target-setting and action in communities across BC – www.toolkit.bc.ca/ceem
Mobility is an important part of daily life. Progressive community planning and transportation design can greatly reduce the need for automobile travel, instead providing a diverse range of active transportation alternatives.
This presentation on the CATCH project looks at how transportation-related data can be used to understand a city’s travel footprint and help to inform city planning and programs to promote individual behaviour change.
It reviews the findings and lessons learned from the ‘CATCH Project’ (Carbon Aware Travel Choice): a 2 million euro-funded project, involving 11 partners across 6 European Union countries, aimed to develop a knowledge platform to help urban communities move to less carbon-intensive transportation systems. This presentation touches on the important role of developing a system to compare and contrast best practices, identify the many motivators for change to low carbon mobility, and use tools for engaging the public and decision makers to support innovation and change.
Slides of the article "CTPATH: A Real World System to Enable Green Transportation by Optimizing Environmentally Friendly Routing Paths" for the congress Smart-CT, Málaga (Spain), June 2016
Improving Pheromone Communication for UAV Swarm Mobility ManagementDaniel H. Stolfi
In this article we address the optimisation of pheromone communication used for the mobility management of a swarm of Unmanned Aerial Vehicles (UAVs) for surveillance applications. A genetic algorithm is proposed to optimise the exchange of pheromone maps used in the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model which improves the vehicles' routes in order to achieve unpredictable trajectories as well as maximise area coverage. Experiments are conducted using realistic simulations, which additionally permit to assess the impact of packet loss ratios on the performance of the surveillance system, in terms of reliability and area coverage.
https://doi.org/10.1007/978-3-030-88081-1_17
Optimising Autonomous Robot Swarm Parameters for Stable Formation DesignDaniel H. Stolfi
Autonomous robot swarm systems allow to address many inherent limitations of single robot systems, such as scalability and reliability. As a consequence, these have found their way into numerous applications including in the space and aerospace domains like swarm-based asteroid observation or counter-drone systems. However, achieving stable formations around a point of interest using different number of robots and diverse initial conditions can be challenging. In this article we propose a novel method for autonomous robots swarms self-organisation solely relying on their relative position (angle and distance). This work focuses on an evolutionary optimisation approach to calculate the parameters of the swarm, e.g. inter-robot distance, to achieve a reliable formation under different initial conditions. Experiments are conducted using realistic simulations and considering four case studies. The results observed after testing the optimal configurations on 72 unseen scenarios per case study showed the high robustness of our proposal since the desired formation was always achieved. The ability of self-organise around a point of interest maintaining a predefined fixed distance was also validated using real robots.
https://doi.org/10.1145/3512290.3528709
Evaluating Surrogate Models for Robot Swarm SimulationsDaniel H. Stolfi
Realistic robotic simulations are computationally demanding, especially when considering large swarms of autonomous robots. This makes the optimisation of such systems intractable, thus limiting the instances' and swarms' size. In this article we study the viability of using surrogate models based on Gaussian processes, Artificial Neural Networks, and simplified simulations, as predictors of the robots' behaviour, when performing formations around a central point of interest. We have trained the predictors and tested them in terms of accuracy and execution time. Our findings show that they can be used as an alternative way of calculating fitness values for swarm configurations which can be used in optimisation processes, increasing the number evaluations and reducing execution times and computing cluster budget.
https://doi.org/10.1007/978-3-031-34020-8_17
Competitive Evolution of a UAV Swarm for Improving Intruder Detection RatesDaniel H. Stolfi
In this paper we present a Predator-Prey approach to enhance the protection of a restricted area using a swarm of Unmanned Aerial Vehicles (UAV). We have chosen the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model for the UAVs and a new model for intruders based on attractive and repulsive forces. After proposing a number of parameters for each mobility model, we have conducted a competitive optimisation of them (Predators and Preys), to achieve a more robust configuration improving the success rate of UAVs when detecting intruders. We have optimised three case studies by performing 30 independent runs of our competitive coevolutionary genetic algorithm and conducted a number of master tournaments using the best specimens obtained for each case study.
https://doi.org/10.1109/IPDPSW50202.2020.00094
A Cooperative Coevolutionary Approach to Maximise Surveillance Coverage of UA...Daniel H. Stolfi
This paper presents the parameterisation and optimisation of the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model used by an Unmanned Aerial Vehicle (UAV) swarm to perform surveillance tasks. CACOC uses chaotic solutions of a dynamical system and pheromones for optimising area coverage. Consequently, several parameters of CACOC are to be optimised with the aim of improving its coverage performance. We propose a Genetic Algorithm (GA) and two Cooperative Coevolutionary Genetic Algorithms (CCGA) to tackle this problem. After testing our proposals on four case studies we performed a comparative analysis to conclude that the cooperative approaches allow a better exploration of the search space by optimising each UAV parameters independently.
https://doi.org/10.1109/CCNC46108.2020.9045643
Optimizing the Performance of an Unpredictable UAV Swarm for Intruder DetectionDaniel H. Stolfi
In this paper we present the parameterisation and optimisation of the CACOC (Chaotic Ant Colony Optimisation for Coverage) mobility model applied to Unmanned Aerial Vehicles (UAV) in order to perform surveillance tasks. The use of unpredictable routes based on the chaotic solutions of a dynamic system as well as pheromone trails improves the area coverage performed by a swarm of UAVs. We propose this new application of CACOC to detect intruders entering an area under surveillance. Having identified several parameters to be optimised with the aim of increasing intruder detection rate, we address the optimisation of this model using a Cooperative Coevolutionary Genetic Algorithm (CCGA). Twelve case studies (120 scenarios in total) have been optimised by performing 30 independent runs (360 in total) of our algorithm. Finally, we tested our proposal in 100 unseen scenarios of each case study (1200 in total) to find out how robust is our proposal against unexpected intruders.
https://doi.org/10.1007/978-3-030-41913-4_4
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
This presentation explores a brief idea about the structural and functional attributes of nucleotides, the structure and function of genetic materials along with the impact of UV rays and pH upon them.
Seminar of U.V. Spectroscopy by SAMIR PANDASAMIR PANDA
Spectroscopy is a branch of science dealing the study of interaction of electromagnetic radiation with matter.
Ultraviolet-visible spectroscopy refers to absorption spectroscopy or reflect spectroscopy in the UV-VIS spectral region.
Ultraviolet-visible spectroscopy is an analytical method that can measure the amount of light received by the analyte.
Richard's entangled aventures in wonderlandRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
Cancer cell metabolism: special Reference to Lactate PathwayAADYARAJPANDEY1
Normal Cell Metabolism:
Cellular respiration describes the series of steps that cells use to break down sugar and other chemicals to get the energy we need to function.
Energy is stored in the bonds of glucose and when glucose is broken down, much of that energy is released.
Cell utilize energy in the form of ATP.
The first step of respiration is called glycolysis. In a series of steps, glycolysis breaks glucose into two smaller molecules - a chemical called pyruvate. A small amount of ATP is formed during this process.
Most healthy cells continue the breakdown in a second process, called the Kreb's cycle. The Kreb's cycle allows cells to “burn” the pyruvates made in glycolysis to get more ATP.
The last step in the breakdown of glucose is called oxidative phosphorylation (Ox-Phos).
It takes place in specialized cell structures called mitochondria. This process produces a large amount of ATP. Importantly, cells need oxygen to complete oxidative phosphorylation.
If a cell completes only glycolysis, only 2 molecules of ATP are made per glucose. However, if the cell completes the entire respiration process (glycolysis - Kreb's - oxidative phosphorylation), about 36 molecules of ATP are created, giving it much more energy to use.
IN CANCER CELL:
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
Unlike healthy cells that "burn" the entire molecule of sugar to capture a large amount of energy as ATP, cancer cells are wasteful.
Cancer cells only partially break down sugar molecules. They overuse the first step of respiration, glycolysis. They frequently do not complete the second step, oxidative phosphorylation.
This results in only 2 molecules of ATP per each glucose molecule instead of the 36 or so ATPs healthy cells gain. As a result, cancer cells need to use a lot more sugar molecules to get enough energy to survive.
introduction to WARBERG PHENOMENA:
WARBURG EFFECT Usually, cancer cells are highly glycolytic (glucose addiction) and take up more glucose than do normal cells from outside.
Otto Heinrich Warburg (; 8 October 1883 – 1 August 1970) In 1931 was awarded the Nobel Prize in Physiology for his "discovery of the nature and mode of action of the respiratory enzyme.
WARNBURG EFFECT : cancer cells under aerobic (well-oxygenated) conditions to metabolize glucose to lactate (aerobic glycolysis) is known as the Warburg effect. Warburg made the observation that tumor slices consume glucose and secrete lactate at a higher rate than normal tissues.
(May 29th, 2024) Advancements in Intravital Microscopy- Insights for Preclini...Scintica Instrumentation
Intravital microscopy (IVM) is a powerful tool utilized to study cellular behavior over time and space in vivo. Much of our understanding of cell biology has been accomplished using various in vitro and ex vivo methods; however, these studies do not necessarily reflect the natural dynamics of biological processes. Unlike traditional cell culture or fixed tissue imaging, IVM allows for the ultra-fast high-resolution imaging of cellular processes over time and space and were studied in its natural environment. Real-time visualization of biological processes in the context of an intact organism helps maintain physiological relevance and provide insights into the progression of disease, response to treatments or developmental processes.
In this webinar we give an overview of advanced applications of the IVM system in preclinical research. IVIM technology is a provider of all-in-one intravital microscopy systems and solutions optimized for in vivo imaging of live animal models at sub-micron resolution. The system’s unique features and user-friendly software enables researchers to probe fast dynamic biological processes such as immune cell tracking, cell-cell interaction as well as vascularization and tumor metastasis with exceptional detail. This webinar will also give an overview of IVM being utilized in drug development, offering a view into the intricate interaction between drugs/nanoparticles and tissues in vivo and allows for the evaluation of therapeutic intervention in a variety of tissues and organs. This interdisciplinary collaboration continues to drive the advancements of novel therapeutic strategies.
Computing New Optimized Routes for GPS Navigators Using Evolutionary Algorithms
1. COMPUTING NEW OPTIMIZED ROUTES
FOR GPS NAVIGATORS
USING EVOLUTIONARY ALGORITHMS
Daniel H. Stolfi
dhstolfi@lcc.uma.es
Enrique Alba
eat@lcc.uma.es
Departamento de Lenguajes y Ciencias de la Computación
University of Malaga
Genetic and Evolutionary Computation Conference
GECCO 2017
Berlin, Germany
July 2017
2. CONTENTS
1 INTRODUCTION
2 OUR PROPOSAL
3 RESULTS
4 CONCLUSIONS & FUTURE WORK
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 1 / 17
3. CONTENTS
1 INTRODUCTION
2 OUR PROPOSAL
3 RESULTS
4 CONCLUSIONS & FUTURE WORK
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 1 / 17
4. CONTENTS
1 INTRODUCTION
2 OUR PROPOSAL
3 RESULTS
4 CONCLUSIONS & FUTURE WORK
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 1 / 17
5. CONTENTS
1 INTRODUCTION
2 OUR PROPOSAL
3 RESULTS
4 CONCLUSIONS & FUTURE WORK
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 1 / 17
7. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
INTRODUCTION
Nowadays in our cities. . .
There is a larger number of vehicles in the streets
The number of traffic jams is rising
Tons of greenhouse gases are emitted to the
atmosphere
The citizens’ quality of life is decreasing
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 2 / 17
8. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
INTRODUCTION
Nowadays in our cities. . .
There is a larger number of vehicles in the streets
The number of traffic jams is rising
Tons of greenhouse gases are emitted to the
atmosphere
The citizens’ quality of life is decreasing
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 2 / 17
9. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
INTRODUCTION
Nowadays in our cities. . .
There is a larger number of vehicles in the streets
The number of traffic jams is rising
Tons of greenhouse gases are emitted to the
atmosphere
The citizens’ quality of life is decreasing
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 2 / 17
10. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
INTRODUCTION
Nowadays in our cities. . .
There is a larger number of vehicles in the streets
The number of traffic jams is rising
Tons of greenhouse gases are emitted to the
atmosphere
The citizens’ quality of life is decreasing
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 2 / 17
11. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
INTRODUCTION
Nowadays in our cities. . .
There is a larger number of vehicles in the streets
The number of traffic jams is rising
Tons of greenhouse gases are emitted to the
atmosphere
The citizens’ quality of life is decreasing
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 2 / 17
12. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
13. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Shortest vs. fastest routes
Avenues, main streets, . . .
Everyone is taking the same (fast?) route
Some of them use traffic data
Internet? Expensive? Developing world?
Traffic jams
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
14. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Shortest vs. fastest routes
Avenues, main streets, . . .
Everyone is taking the same (fast?) route
Some of them use traffic data
Internet? Expensive? Developing world?
Traffic jams
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
15. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Shortest vs. fastest routes
Avenues, main streets, . . .
Everyone is taking the same (fast?) route
Some of them use traffic data
Internet? Expensive? Developing world?
Traffic jams
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
16. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Shortest vs. fastest routes
Avenues, main streets, . . .
Everyone is taking the same (fast?) route
Some of them use traffic data
Internet? Expensive? Developing world?
Traffic jams
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
17. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Shortest vs. fastest routes
Avenues, main streets, . . .
Everyone is taking the same (fast?) route
Some of them use traffic data
Internet? Expensive? Developing world?
Traffic jams
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
18. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Shortest vs. fastest routes
Avenues, main streets, . . .
Everyone is taking the same (fast?) route
Some of them use traffic data
Internet? Expensive? Developing world?
Traffic jams
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
19. Introduction
Our Proposal
Results
Conclusions & Future Work
Road Traffic
GPS Navigators
GPS NAVIGATORS
Fixed routes
Shortest vs. fastest routes
Avenues, main streets, . . .
Everyone is taking the same (fast?) route
Some of them use traffic data
Internet? Expensive? Developing world?
Traffic jams
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 3 / 17
20. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
ALTERNATIVE ROUTES FOR GPS NAVIGATORS
Alternative routes to prevent traffic jams
For vehicles driving throughout the city
Reduce travel times
Reduce greenhouse gas emissions
Reduce fuel consumption
Save money
Improve health and
quality of life
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 4 / 17
21. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
ALTERNATIVE ROUTES FOR GPS NAVIGATORS
Alternative routes to prevent traffic jams
For vehicles driving throughout the city
Reduce travel times
Reduce greenhouse gas emissions
Reduce fuel consumption
Save money
Improve health and
quality of life
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 4 / 17
22. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
ALTERNATIVE ROUTES FOR GPS NAVIGATORS
Alternative routes to prevent traffic jams
For vehicles driving throughout the city
Reduce travel times
Reduce greenhouse gas emissions
Reduce fuel consumption
Save money
Improve health and
quality of life
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 4 / 17
23. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
ALTERNATIVE ROUTES FOR GPS NAVIGATORS
Alternative routes to prevent traffic jams
For vehicles driving throughout the city
Reduce travel times
Reduce greenhouse gas emissions
Reduce fuel consumption
Save money
Improve health and
quality of life
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 4 / 17
24. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CALCULATING ALTERNATIVE ROUTES
Based on the Dynamic User Equilibrium (DUE)
Different probabilities for each route
Strategies:
Dijkstra
DUE.r
DUE.rp
DUE.ea
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 5 / 17
25. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CALCULATING ALTERNATIVE ROUTES
Based on the Dynamic User Equilibrium (DUE)
Different probabilities for each route
Strategies:
Dijkstra
DUE.r
DUE.rp
DUE.ea
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 5 / 17
26. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CALCULATING ALTERNATIVE ROUTES
Based on the Dynamic User Equilibrium (DUE)
Different probabilities for each route
Strategies:
Dijkstra
DUE.r
DUE.rp
DUE.ea
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 5 / 17
27. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CALCULATING ALTERNATIVE ROUTES
Based on the Dynamic User Equilibrium (DUE)
Different probabilities for each route
Strategies:
Dijkstra
DUE.r
DUE.rp
DUE.ea
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 5 / 17
28. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CALCULATING ALTERNATIVE ROUTES
Based on the Dynamic User Equilibrium (DUE)
Different probabilities for each route
Strategies:
Dijkstra
DUE.r
DUE.rp
DUE.ea
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 5 / 17
29. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CALCULATING ALTERNATIVE ROUTES
Based on the Dynamic User Equilibrium (DUE)
Different probabilities for each route
Strategies:
Dijkstra
DUE.r
DUE.rp
DUE.ea
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 5 / 17
30. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
MALAGA CITY CENTER
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 6 / 17
31. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
MALAGA CITY CENTER
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 6 / 17
32. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
MALAGA CITY CENTER
OpenStreetMap
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 6 / 17
33. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
MALAGA CITY CENTER
OpenStreetMap SUMO
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 6 / 17
34. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
BUILDING MALAGA
1 Download the map from OpenStreetMap
2 Clean the irrelevant elements using JOSM
3 Import the city model using NETCONVERT
4 Define its routes using DUAROUTER and the Flow
Generator Algorithm (FGA)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 7 / 17
35. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
BUILDING MALAGA
1 Download the map from OpenStreetMap
2 Clean the irrelevant elements using JOSM
3 Import the city model using NETCONVERT
4 Define its routes using DUAROUTER and the Flow
Generator Algorithm (FGA)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 7 / 17
36. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
BUILDING MALAGA
1 Download the map from OpenStreetMap
2 Clean the irrelevant elements using JOSM
3 Import the city model using NETCONVERT
4 Define its routes using DUAROUTER and the Flow
Generator Algorithm (FGA)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 7 / 17
37. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
BUILDING MALAGA
1 Download the map from OpenStreetMap
2 Clean the irrelevant elements using JOSM
3 Import the city model using NETCONVERT
4 Define its routes using DUAROUTER and the Flow
Generator Algorithm (FGA)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 7 / 17
38. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
BUILDING MALAGA
1 Download the map from OpenStreetMap
2 Clean the irrelevant elements using JOSM
3 Import the city model using NETCONVERT
4 Define its routes using DUAROUTER and the Flow
Generator Algorithm (FGA)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 7 / 17
39. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CHARACTERISTICS OF THE CASE STUDY
3 km2
58 traffic lights
107 routes
More than 4800 vehicles per hour
Flows calculated using the Flow Generator Algorithm1
12 traffic measurement points
Working days, Saturdays, and Sundays
1
Daniel H Stolfi and Enrique Alba. “An Evolutionary Algorithm to Generate Real Urban Traffic Flows”. In:
Advances in Artificial Intelligence. Vol. 9422. Lecture Notes in Computer Science. Springer International Publishing,
2015, pp. 332–343.
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 8 / 17
40. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CHARACTERISTICS OF THE CASE STUDY
3 km2
58 traffic lights
107 routes
More than 4800 vehicles per hour
Flows calculated using the Flow Generator Algorithm1
12 traffic measurement points
Working days, Saturdays, and Sundays
1
Daniel H Stolfi and Enrique Alba. “An Evolutionary Algorithm to Generate Real Urban Traffic Flows”. In:
Advances in Artificial Intelligence. Vol. 9422. Lecture Notes in Computer Science. Springer International Publishing,
2015, pp. 332–343.
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 8 / 17
41. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
CHARACTERISTICS OF THE CASE STUDY
3 km2
58 traffic lights
107 routes
More than 4800 vehicles per hour
Flows calculated using the Flow Generator Algorithm1
12 traffic measurement points
Working days, Saturdays, and Sundays
1
Daniel H Stolfi and Enrique Alba. “An Evolutionary Algorithm to Generate Real Urban Traffic Flows”. In:
Advances in Artificial Intelligence. Vol. 9422. Lecture Notes in Computer Science. Springer International Publishing,
2015, pp. 332–343.
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 8 / 17
42. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
EVOLUTIONARY ALGORITHM
(10+2)-EA
Individuals are evaluated using SUMO
Detours are implemented by using TraCI
Calculates the probability of each route (DUE.ea)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 9 / 17
43. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
EVOLUTIONARY ALGORITHM
(10+2)-EA
Individuals are evaluated using SUMO
Detours are implemented by using TraCI
Calculates the probability of each route (DUE.ea)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 9 / 17
44. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
REPRESENTATION
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 10 / 17
45. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
REPRESENTATION
121 probability values
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 10 / 17
46. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
REPRESENTATION
121 probability values
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 10 / 17
47. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
REPRESENTATION
121 probability values
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 10 / 17
48. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
EVALUATION
Fitness Function
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 11 / 17
49. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
EVALUATION
Fitness Function
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 11 / 17
50. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
EVALUATION
Fitness Function
F =
α
N
N
i=1
travel timei
We are minimizing travel times, so the lower the better
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 11 / 17
51. Introduction
Our Proposal
Results
Conclusions & Future Work
Alternative Routes
Case Study: Malaga
Evolutionary Algorithm
EVALUATION
Fitness Function
F =
α
N
N
i=1
travel timei
We are minimizing travel times, so the lower the better
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 11 / 17
58. Introduction
Our Proposal
Results
Conclusions & Future Work
Improvements
Examples
Penetration Rate
PREVENTING TRAFFIC JAMS
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 13 / 17
59. Introduction
Our Proposal
Results
Conclusions & Future Work
Improvements
Examples
Penetration Rate
BETTER ROUTES
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 14 / 17
60. Introduction
Our Proposal
Results
Conclusions & Future Work
Improvements
Examples
Penetration Rate
PENETRATION RATE
What if not all drivers are
using our proposal?
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 15 / 17
61. Introduction
Our Proposal
Results
Conclusions & Future Work
Improvements
Examples
Penetration Rate
PENETRATION RATE
What if not all drivers are using our proposal?
Penetration Rate Study
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 15 / 17
62. Introduction
Our Proposal
Results
Conclusions & Future Work
Improvements
Examples
Penetration Rate
PENETRATION RATE
What if not all drivers are using our proposal?
Penetration Rate Study
Working Days
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 15 / 17
63. Introduction
Our Proposal
Results
Conclusions & Future Work
Improvements
Examples
Penetration Rate
PENETRATION RATE
What if not all drivers are using our proposal?
Penetration Rate Study
Working Days Saturdays
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 15 / 17
64. Introduction
Our Proposal
Results
Conclusions & Future Work
Improvements
Examples
Penetration Rate
PENETRATION RATE
What if not all drivers are using our proposal?
Penetration Rate Study
Working Days Saturdays Sundays
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 15 / 17
65. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
66. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
67. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
68. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
69. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
70. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
71. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
72. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
73. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
CONCLUSIONS
Alternative routes for GPS navigators
Based on the Dynamic User Equilibrium
Suggested according to probabilities (DUE.ea)
Scenarios based on real road traffic data (FGA)
DUE.ea achieved:
Shorter travel times (up to 18%)
Less greenhouse gas emissions (up to 14%)
Fuel saving (up to 7.5%)
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 16 / 17
74. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
FUTURE WORK
Extend our analysis to other/bigger areas
Optimization of the entire city by districts/neighborhoods
Address the simulation of thousands of vehicles
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 17 / 17
75. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
FUTURE WORK
Extend our analysis to other/bigger areas
Optimization of the entire city by districts/neighborhoods
Address the simulation of thousands of vehicles
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 17 / 17
76. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
FUTURE WORK
Extend our analysis to other/bigger areas
Optimization of the entire city by districts/neighborhoods
Address the simulation of thousands of vehicles
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 17 / 17
77. Introduction
Our Proposal
Results
Conclusions & Future Work
Conclusions
Future Work
FUTURE WORK
Extend our analysis to other/bigger areas
Optimization of the entire city by districts/neighborhoods
Address the simulation of thousands of vehicles
Daniel H. Stolfi & Enrique Alba Computing New Optimized Routes for GPS. . . 17 / 17
78. QUESTIONS
Computing New Optimized Routes for GPS Navigators
Using Evolutionary Algorithms
Questions?
Daniel H. Stolfi Enrique Alba
dhstolfi@lcc.uma.es eat@lcc.uma.es
http://danielstolfi.com http://neo.lcc.uma.es
Acknowledgements: This research has been partially funded by Spanish MINECO project TIN2014-57341-R (moveON). Daniel H. Stolfi is
supported by a FPU grant (FPU13/00954) from the Spanish Ministry of Education, Culture and Sports. University of Malaga. International
Campus of Excellence Andalucia TECH.