Apps - TEAM - IP project

TEAM applications

Following the vision of TEAM the following collaborative TEAM applications show how we fulfill our respective TEAM objectives. The selection of these applications followed our TEAM research and methodology approach. The final 11 TEAM applications are part of our overall TEAM results and highlight the collaboration between travellers and drivers and the road infrastructure operators.

For each application a short overview is provided first, and then the use cases are highlighted, showing the most relevant features of the application.

  1. FLEX infrastructure applications

    • Collaborative pro-active urban/inter-urban monitoring and ad-hoc control (CMC)

      Challenge: Coordination of traffic control to reduce fuel consumption and emission levels.

      Solution: Instruments to build a comprehensive picture of the traffic situation from various sources: vehicle sensors, traffic management centres, crowd sourcing, mobile devices, data providers, public authorities.

      Benefits: City authorities can identify and solve traffic problems in an adaptive and anticipatory way.

      TEAM equipped vehicles monitor urban roads and recognize incidents or special events (i.e. road closures, work zones, public large-scale events) while driving. Furthermore, they provide real-time information to the Traffic Management Centre, which validates the reliability of this information and optimizes the traffic efficiency. Such innovative paradigm is based both on the information that comes from the vehicle side (as a monitoring sensor) and from a proactive traffic management centre.

      A comprehensive picture of the traffic situation can be build through a vehicle-to-infrastructure communication, information from other data sources (e.g. crowd sourcing, mobile devices tracking etc.) and the existing legacy monitoring system. All the collected data are processed in order to obtain reliable traffic forecasts regarding the status of the network in the short and mid-term to define estimated levels of service, travel time, saturation ratio and forecasted utilisation of the arcs of the road network. This application will also support other TEAM applications providing dynamic real-time information to coordinate collaborative traffic control, in order to reduce congestion, fuel consumption and consequently emission levels.

    • Collaborative co-modal route planning (COPLAN)

      Challenge: Rapid interaction with the map database and display of complex data at Traffic Management Centres (TMCs)

      Solution: Tools for visualization, monitoring and traffic interaction with a graphical interface

      Benefits: Traffic managers get simplified options for route-planning and can react better to user needs and constraints

      This application provides collaborative co-modal route planning services considering:

      • statistical information for specific geo-locations,
      • real-time evaluation and computation of predicted / forecasted traffic development,
      • evaluation of location-specific and distributed routing data from all vehicles involved in the system in order to enable truly collaborative route planning by involving user decisions through a feedback information facility.

      To this end, COPLAN is enabled through a global system view by aggregating and fusing information of TEAM infrastructure (FLEX) applications, such as CMC and CPTO.

      COPLAN has a high environmental impact, thanks to the inclusion of environmentally friendly transportation modes such as public transportation, bikes, car-sharing services, walk, etc. It also involves user preferences in its optimization engine allowing prioritized transportation modes, differentiated vehicle priorities, desired time of arrival, and maximal overall travel cost, among others.

      In order to enable its real-time predictive and interpolative traffic evolution engine, COPLAN has built-in routed and existing traffic tracking features. In this way, traffic behaviour is available on a real-time basis with much greater accuracy than on today's TMC enabled navigation systems. Furthermore, this application is available to all TEAM and non-TEAM applications that might require global routing services beyond the capabilities offered by user-level navigation devices.

    • Co-modal coaching with support from virtual/avatar users (CCA)

      Challenge: Reliable and exact information about true travel costs, travel times, trip alternatives and CO2 emissions

      Solution: Virtual travels with an avatar by using the most efficient of all transport modes

      Benefits: Travellers get a virtual coach to support their travel plans and even experienced users such as commuters can benefit from real-time knowledge

      This is a co-modal application with post trip cost/benefit analysis functionalities, made through a comparison of the behaviors of the real user and the "virtual" avatar user. The proposed idea does not aim on vague pre-trip forecasts but reliable and exact post-trip information about a user's realized trip alternatives. These concern the same pair of origin-destination including monitoring and displaying their true costs, travel times and CO2 emissions based on real-time knowledge about occurred traffic jams or delays in public and private transport. The idea in here is to understand the users' mobility patterns and provide co-modal real-time route recommendations that integrate environmental footprint costs on post planned journey, offering travellers the opportunity to choose the most environmentally friendly alternative of mode for their journey. A comparison will be made through real time monitoring the individual route of a user and the encountered trip alternatives of an avatar travelling by optimal transport modes from the same origin to the same destination at mostly the same time. Such cost-benefit analysis can create good understanding on a user in taking decisions about a real mobility options on his next trips. The integration of this application with collaborative and social aspects of TEAM will further increase its end-user impact.

    • Collaborative smart intersection for intelligent priorities (CSI)

      Challenge: Traffic flow optimization at intersections (especially for public transport)

      Solution: Priority for certain vehicles (i.e. buses), synchronization of traffic lights and speed recommendations through exchange of information between smartphones, vehicles and road side units.

      Benefits: Drivers, travellers and the environment benefit from a better traffic flow in the city.

      This is an integrated application for intersections. One of the main objectives is to optimize public transport, giving priority to buses. Priority techniques can generate improvements in service regularity, which usually means alignment with nominal time-tables and headways. The priorities can also be considered based on the vehicle type (e.g. truck, bus, tram, car, motorcycle, pedestrians, cyclists etc.) and on other factors (truck with dangerous goods, ambulance, disabled person wanting to cross the street, etc.).

      This application also includes communication and synchronization of multiple traffic lights in a region to optimize traffic flow. The vehicles will send their intended destination to the current intersection and that one will communicate with the next ones to help regulate the traffic flow, based on the number of vehicles that will follow in each direction. The vehicles will receive a speed recommendation in order to get to the next traffic light in green.

      Additionally, the application includes start and stop functionality based on information that comes from smart and pro-active RSUs (i.e. how long do they have to turn off the engine, when to turn on the engine, duration of the red light phase, when the lights will be green, position in a queue etc.)

    • Collaborative public transport optimization (CPTO)

      Challenge: Passengers and cities need an efficient public transport network, with reduced emissions and minimal operating costs.

      Solution: Optimal bus routes and timetables computation according to predefined criteria.

      Benefits: More flexible and better organized networks serving both travellers' and cities' requirements.

      The goal of this application is to highlight the flexibility of the transport infrastructure serving dynamically the needs and demand of the cities and the citizens. It mainly focuses on buses but it can be extended to other means of transport, as well.

      By exploiting information from the TEAM users, such as their position, destination and preferences, together with information about the road traffic and bus line characteristics, the public transport operator dynamically adapts the timetables and the routes in order to achieve specific targets. These include optimisation of the overall network efficiency, reduced CO2 emissions, minimisation of operator cost from low demand lines and in general increase of the network efficiency.

    • Collaborative dynamic corridors (DC)

      Challenge: Bus lanes are needed only during peak traffic periods while distribution vehicles cannot deliver goods efficiently due to heavy traffic.

      Solution: Corridors for heavy vehicles (trucks or buses) which are established in a dynamic way.

      Benefits: Through dedicated lanes the whole city transport can be optimized.

      The main objective of this application is to establish corridors for heavy vehicles, being trucks or buses, in a dynamic way. Certain lanes could be reserved for certain vehicles during a certain period.

      For example, a bus lane could be assigned in the city centre only for buses during the period of peak in traffic, in order to prioritize public transportation schedule. Another example is to have lanes dedicated to distribution vehicles during the early morning to deliver goods in an efficient way. As a last example, inter-urban roads could have dynamic dedicated lanes only for heavy trucks.

  3. DIALOGUE traveller&driver applications

    • Collaborative adaptive cruise control (C-ACC)

      Challenge: Using communication to improve existing Adaptive Cruise Control (ACC) systems that adjust a car's speed to maintain a safe following distance

      Solution: Combination of sensor and traffic data information with information from the users are exchanged between vehicles and infrastructure

      Benefits: Drivers benefit from an ACC system with an extended foresight range that can better predict traffic density to improve traffic flow

      The Concept of Cooperative Adaptive Cruise Control (C-ACC) leverages wireless communication between vehicles and Infrastructure in order to harmonize cruising speed and thereby achieving a positive impact on road safety and traffic efficiency.

      Current research on C-ACC focuses mostly on achieving string stability in vehicle platoons, which helps to avoid shockwave traffic jams and to enhance driving comfort. In TEAM we are going one step further, by taking traffic information and road user centric information into account. In this way, the cruising speed of the vehicles is adapted regarding e.g. upcoming traffic incidents, traffic light phases, and infrastructure related incidents like construction sites or dynamic speed limits.

    • Collaborative eco-friendly parking (EFP)

      Challenge: Exploding parking demand and no access to real time information about parking availability

      Solution: Involvement of motion detectors and sensors to identify parking space in a simple press-a-button-way

      Benefits: Drivers can quickly detect optimal parking conditions while cities can allocate parking space more efficiently

      This application offers real time information about free parking spaces either in the surrounding of the navigator destination or in the most feasible destination. Via manual trigger or autonomous parking/leaving detection the vehicle sends relevant data when entering /leaving a parking slot so that the cloud-based application can constantly monitor the availability of free parking slots. This application's objective will enable connected vehicles to access real time information about parking availabilities along the destination. The vehicles are connected to a cloud service that informs individual road users (vehicle drivers and other device equipped read users) with data about available parking spots.

      The application includes the following features:

      • Detection of the parking searching context,
      • Open slot sensing,
      • Free parking market.

      The application will include a system which manages the knowledge about the free parking spaces and the allocation of parking spaces to users in search for such places. Relevant statistics will also be possible, to guarantee an acceptable quality of service, e.g. filtering information about free slots (or in general individually preferred environments, such as safe routes where few accidents happen, non-complex crossings etc.).

    • Collaborative driving and merging (CDM)

      Challenge: More safety in situations where vehicles interact: lane change or lane merging, roundabout driving, emergency braking, speed limit adaptation etc.

      Solution: Tools that inform drivers about potential risks through other vehicles and support the right decision making

      Benefits: Drivers can improve safety and energy efficiency through collaboration

      The application addresses the challenges in the collaboration among the vehicles to increase safety and improve energy efficiency. It refers to situations where two or more vehicles need to interact among themselves and/or with the road infrastructure to solve specific driving situations.

      The most representative use case is lane change or lane merging; other relevant situations include roundabout driving, emergency braking or hazardous situation in front, intersection start and stop including vehicle-infrastructure collaboration, highway entrance or exit and speed limit adaptation.

      The application is implemented by the vehicle/driver and the TEAM backend. This application provides advice for the driver or vehicle and support to the driver/vehicle for decision making.

    • Green, safe and collaborative driving serious game and community building (SG-CB)

      Challenge: A serious game to support better driving through connecting collaborative TEAM applications and third parties

      Solution: A gamified environment to exchange simple feedback between all participants about their current level of performance

      Benefits: Drivers and travellers build a community and together reach higher levels of green driving and lower traffic

      This application intends to promote and favour an appropriate driver behaviour, with a particular attention to collaborative applications that are being developed in TEAM. The SG-CB application consists of a gamified social network environment where drivers and passengers can share their information and improve their use of collaborative TEAM applications (and also 3rd parties, in an open and scalable perspective), in a pleasant and compelling way and featuring a map-based user interface.

      Given this support to a good use of the other TEAM applications, SG-CB may be thought of as a "meta-application", a user-centred user-interaction based layer aimed at incentivising the use of every connected TEAM application.

      The application includes also a serious game (SG) that exploits vehicle data in order to create a challenge so that drivers are motivated to collaboratively reach high levels of green driving and low levels of traffic in their zones (typically a city or a city area).

    • Collaborative eco-friendly navigation (CONAV)

      Challenge : Solve traffic jams while respecting individual citizens' mobility and community needs

      Solution: Balance traffic load and relax traffic hotspots (schools, leisure areas) by calculating aligned, personalized routing

      Benefits: Vehicle drivers and mobile citizens benefit from a better traffic flow while the community benefits from less pollution – especially at sensible locations

      This application is a turn-by-turn navigation application running on smartphones and on a vehicle-integrated platform. It does routing and navigation for vehicles considering individual user's needs and community (system-centric) needs.

      CONAV provides the interface to the user while he/she is driving and it makes turn-by-turn instructions. It monitors the user behaviour especially looking at his preferences and triggers new route calculations (either in case he/she behaves differently from the instructions or if traffic conditions have changed).

      Different to today's navigation systems, this application provides route recommendations, which are optimized based on multiple needs (environment, traffic load balancing, robustness, queuing at gas stations, balanced pollution levels, safety). CONAV will also consider real-time traffic information provided by the infrastructure.

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