Lisbon
• 10 mobility services datasets published
• 2 solutions available
• 3% reduction of CO2e/vkm on intervened bus routes
Lisbon aims to facilitate data sharing for actionable intelligence, enhancing route planning for people with reduced mobility and making public transportation more competitive and aligned with urban environmental and sustainability goals.
Enhancing seamless route planning
Cluster: Speciality Travel Information
This use case aims to utilise existing as well as newly generated data to improve door-to-door navigation for People with Reduced Mobility (PRM) and provide detailed information for decision-makers.
This includes:
- Subject services to examination: Utilising data from various sources to identify barriers in accessing EMEL’s services and accessibility.
- Increasing information coverage: Identifying and verifying accessibility levels of infrastructure and providing real-time information on temporary accessibility barriers.
- Easy oversight: Creating a comprehensive and interactive heat map for decision-makers.
This use case project will streamline the access to meaningful information for the city’s decision-makers (e.g., Lisbon City Council, city parishes, and EMEL) and foster innovation by making machine-readable and interoperable data discoverable and usable for third parties, enabling them to enhance and develop applications and solutions tailored to PRM needs.
Background:
Lisbon is currently defining a strategy to engage key stakeholders by identifying mobility challenges for individuals with reduced mobility. Limited and fragmented accessibility data for PRM impacts their navigation and access to essential services.
Increasing the attractiveness of alternative mobility solutions – Corporate MaaS
Cluster: Multimodality
This use case aims to reduce car dependency in work commuting and business travel. Alternative mobility solutions are become more attractive by making transport service and infrastructure data interoperable and usable for multimodal digital mobility service providers and corporate mobility management providers.
This includes:
- Harmonising transport data: Utilising data space components and EMDS deployment to improve the technical availability and quality of transport service data.
- Creation of a digital infrastructure: Developing a public digital infrastructure to support the creation of multimodal mobility solutions.
- Collaborating with providers: Working with transport service providers and organisations to create meaningful mobility bundles for employees.
This use case leverages data space components and EMDS deployment to enhance the availability and quality of transport data, establishing a digital infrastructure for multimodal mobility solutions targeted at corporate users. EMEL will collaborate with transport providers to create and manage mobility bundles for organisations, promoting sustainable commuting and reducing car dependency.
Background:
Currently, there is a significant reliance on private cars in Lisbon: 45% of trips in the city and 58.9% in the metropolitan area made by car, leading to congestion and pollution. Despite improvements in public transport and cycling infrastructure, complementary measures to promote sustainable urban mobility are still needed. EMEL’s focus on integrating high-quality services and promoting an inclusive, sustainable transport system aligns with the city’s MOVE Lisbon 2030 vision.
Increasing schedule reliability and/or commercial speed of buses
Cluster: Public transport operations
This use case aims to increase the schedule reliability and commercial speed of buses by identifying and resolving transportation conflicts that slow down bus travel.
This includes:
- Identifying conflict points: Mapping locations where different transport modes conflict, resulting in low bus speeds.
- Harvesting and processing data: Utilising existing data and deploying necessary APIs to facilitate data access and sharing for analysis.
- Implementing solutions: Proposing interventions like dedicated bus lanes, traffic light programming changes, or controlling abusive parking to improve bus flow.
The use case focuses on enhancing bus service efficiency in Lisbon by pinpointing and addressing areas where bus speeds are hindered, using data analysis to propose and implement effective solutions, and improving communication of bus schedules and estimated times of arrival (ETA) to passengers.
Background:
TML, the transport authority, oversees bus services across 18 municipalities, with over 1,700 buses and 630,000 daily commuters. Buses frequently face delays due to traffic, traffic lights, and illegal parking, without schedules fully accounting for these issues. Existing data systems collect vast amounts of data, but this data is not yet structured for efficient use, making it hard to prioritise and justify interventions based on objective analysis rather than personal perception.
