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TIMON - Enhanced real time services for an optimized multimodal mobility relying on cooperative networks and open data

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EGVIA - ERTRAC 1st European Conference Results from Road Transport Research in H2020 projects
29 November 2017 to 30 November 2017
Brussels

Published in: Automotive
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TIMON - Enhanced real time services for an optimized multimodal mobility relying on cooperative networks and open data

  1. 1. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON Enhanced real time services for optimized multimodal mobility relying on cooperative networks and open data Enrique Onieva
  2. 2. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. FACTS AND FIGURES § TIMON § Work programme: Smart, green and integrated transport § Call: Mobility for Growth 2014. MG.3.5-2014. Cooperative - ITS for safe, congestion-free and sustainable mobility § Type of action: Research and Innovation Actions § Grant Agreement: 636220 § CONSORTIUM § 11 partners at EU level § Coordinated by the University of Deusto (Spain) § Overall budget: 5.605.213 € § Duration: 42 months (June 2015 - November 2018)
  3. 3. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. GENERAL OBJECTIVES § To increase road safety § To achieve more flexible transport § By taking advantage of the different data available related to transport and mobility, from different sources: § infrastructure, open data, vehicles and VRU § To reduce pollution emissions by 6-10% § To relieve traffic congestion by 12-20%
  4. 4. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. OVERALL CONCEPT § Development of a web platform and mobile applications for the delivery of information services to road agents, drivers and vulnerable road users. § Driving hazard alerts § Traffic congestion § Route optimization Infrastructure sensors Open data Vehicles&VRU Multi-modal dynamic commuter Enhanced RT Traffic Information API Getting involved users Emergency vehicle approaching Road Hazard warning Dynamic Route re-planning for drivers Services for Drivers Vehicle density awareness Collision alert Dynamic route re-planning Services for VRUs TIMON Server Open platform and APP development SERVICES FOR CITIZENS SERVICE FOR BUSINESS TIMON COLLABORATIVE ECOSYSTEM DATA SOURCES Vehicular hybrid networks LTE ITS-G5 Artificial Intelligence Route planning Congestion prediction Cooperative positioning TECHNOLOGIES
  5. 5. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. SPECIFIC OBJECTIVES § Identify transport open data sources of information and its harmonization. § Increase accuracy on the position of vehicles and VRUs by means of the cooperative positioning techniques enhancing GNSS positioning § Develop hybrid networks for assuring communication between vehicles and VRU, supporting ETSI-G5 and mobile cellular LTE § Leverage the information gathered from different sources, by applying artificial intelligence techniques: traffic behaviour patterns detection, optimized routing § Implement ITS real time services enhancing dynamic maps and cloud computing, in the areas of: driver assistance, vulnerable users and multimodal dynamic commuter or enhanced real time traffic information API
  6. 6. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. TECHNOLOGICAL CHALLENGES § Cooperative positioning § Positioning under GNSS signal blocking § High precision § Hybrid communication networks § Short-long range synergy (ITS-G5+LTE) § Reducing investment in infrastructure § Artificial Intelligence (Led by Deusto) § Congestion prediction § Optimization of intermodal routes
  7. 7. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. INNOVATIVE ASPECTS § Current mobility services only collect data from infrastructure and/or open data sources. § TIMON § Collects and processes data from a variety of sources § Vehicles as sensors: providing position, time stamp, speed… § Vehicles/motorcycles are prosumers: they provide data to the system and consume information from it. § Open data and infrastructure. § Collects data in Real-time à real-time services.
  8. 8. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. DATA SOURCES § More tan 20 data sources integrated and harmonized § All of them standardized under the DATEX-II Bike Rental Parking Availability Car Sharing Real-time Weather Taxi Contact Details Electric Vehicle Charging Stations Traffic Light Locations Traffic Bluetooth Sensors Traffic Light Inductive Loop Sensors Traffic Roadworks & Accidents Traffic Delays & Congestion Train GTFS Pollution guidance Pedestrian Zones GPS Data from Vehicles Bus RT-GTFS Train RT-GTFS (…)
  9. 9. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. PILOT OF SOLUTIONS § Testing in Helmond, the Netherlands § Real data used § Phase 1: Subsystem testing (September 2016; June 2017) § Phase 2: Global system validation (February 2018) § Piloting in real environment in Ljubljana (Slovenia), May 2018. § Participation of citizens as users of the TIMON system. § 50-80 participants: drivers, motorcyclists and public transport users.
  10. 10. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. ADVANCED ARTIFICIAL INTELLIGENCE § Motivation § Interpretability § Overcome classic artificial intelligence techniques § Focused on system accuracy but Not in its interpretability § Imbalance § Traffic data is usually highly imbalanced: § Abnormal situations are very rare § Some predictions have a high degree of accuracy, but they are not useful § There won't be a traffic jam at 4:30 am § Methods § Fuzzy Logic à “Low”, “medium”, “high”, “about 50”, “slow”, “fast” § Evolutionary Algorithms à Flexibility to optimize any model’s structure § Multi-Objective Optimization à {Price vs Quality} {Accuracy vs Complexity}
  11. 11. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. ADVANCED ARTIFICIAL INTELLIGENCE § Objectives § Short-term congestion prediction § Through the use of bio-inspired metaheuristics to optimize fuzzy logic based systems § Optimization of point-to-point routes § Implementing bioinspired optimizers in a multi-modal way to respond to user requirements § Results § Evaluation of "classical" data mining techniques and comparison of 384 models § Data reduction by Instances selection and Attributes selection § Enhanced algorithms § Adjusting the importance of each rule to prediction § Rule generation based on evolutionary algorithms § Fitness function adjustment to consider imbalances § Improved crossover and mutation operators
  12. 12. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. ADVANCED ARTIFICIAL INTELLIGENCE § Real Time Traffic + Traffic Prediction System Services § TIMON Cloud data collection and preparation § Traffic information engine calculation of future traffic status § Geographic information system module locates information in the road network § Geo-referenced information is sent to the TIMON Cloud
  13. 13. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. ADVANCED ARTIFICIAL INTELLIGENCE § Multimodal Route Planning Service § Based on OpenTripPlanner § Open, robust and flexible § Data Integration § GTFS à public transport à intermodal routes § Slopes à emissions calculation à green routes § Slopes à bike friendly routes § Traffic predictions à optimal routes § Multi-objective optimization through differential evolution
  14. 14. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. ADVANCED ARTIFICIAL INTELLIGENCE § RESULTS § Reduction of data needed to predict >70% § Accuracy (prediction hit) >90% § Sensitivity (hit in anomalous states) >80% § Time to of training (24 cameras) <10 min. § Time to predict (24 points) <0.1 sec. § Complexity of models <10 rules
  15. 15. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. EXPECTED POTENTIAL IMPACT § Increase of road safety § Drivers and VRU will be alerted of potentially hazardous events § Predictions and routes provided users to choose safer routes § Hybrid vehicular communications and enhanced positioning will help to distribute real time accurate information § Reduction of traffic congestion § The system will suggest the most optimized multimodal transport route according to user`s profile § Since the traveling duration can be predicted more accurately, it will be possible to boost and improve car sharing initiatives § Flexibility of transport § Users will be provided with accurate multimodal travel-services, indicating the best route and mean of transport § Reduction in pollution emissions § Routes produced take into account data related to vehicles’ consumption, the steepness of the routes and all the available public transports in the city for the multimodal routing.
  16. 16. This project has received funding from the [European Union’s Horizon 2020 research and innovation programme under grant agreement No 723970 TIMON project has received funding from the European Union’s Horizon 2020 research and innovation programme under Grant Agreement no 636220. THANK YOU Enrique Onieva enrique.onieva@deusto.es www.timon-project.eu Indicator Units used Reference Objective Current Vehicles Data sources ingested Number of data sources Open and closed data sources 20 25 Car, bus, train, bike Traffic flow improvement % reduction of traffic congestion Route planning which considers RT traffic information and predictions 12 TBD Car, bus, motorcycle Traffic predictions % accuracy in traffic predictions Traffic predictions for 15, 30, 45 and 60 mins to avoid traffic congestion >80% Interurban: 90% Highway: 98% Car, bus Route calculations % duration error Routes that consider Duration, Length, Safety, Inclination <35% 30% Car, bike, motorcycle, public transport, walk Real time information to road users % accuracy of RT information The system updates the information every 15 minutes: with sensors or with floating data Sensors: 90% Floating data: 70% Sensors: 95% FD: TBD Car, bus, motorcycle Improvement of transport flexibility Types of routes or parameters Route planner that considers flexible parameters to be adjusted to the users’ needs 1 alternative route improves 100% of routes improve Car, bike, motorcycle, public Improvement or positioning technologies % enhancement in accuracy of positioning Positioning in low GNSS coverage areas 50% >50% Car Sensors and in-vehicle computers development Type and number of sensors Equipment installed in Ljubljana 3 OBUs and several RSUs 37 BT sensors, 3 OBUs and 10 RSUs Car, motorcycle, bus CO2 or fuel consumption reduction % reduction of emissions Routes consider fuel consumption 6 TBD Car Standardisation of on-/ or offboard software Programming Languages, Middleware types Work under DATEX II standardization All information in DATEX II All information in DATEX II Car, bike, motorcycle, bus Development of new urban mobility systems Number of different transport modes Multimodal route planning system Route planner Flexible route calculator Car, bike, motorcycle

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