Accessibility-driven Planning for First- and Last-Mile Micromobility Services

Shared micromobility can bridge the first and last mile of public transport (PT) journeys, but commercial operating areas often concentrate near city centres, leaving some residential districts outside their coverage. This study develops and applies an accessibility-driven, step-by-step planning method to identify urban areas where extending shared e-scooter services could improve connections to PT. Its case study covers 290 traffic analysis zones (TAZs) and 932,856 residents in metropolitan Thessaloniki, Greece. 

The method combines origin-destination travel demand for work and education trips, walking access to bus stops, existing e-scooter service boundaries, road gradients, bus frequency, reliability and comparative journey times. Ten-minute walking isochrones, assuming a walking speed of 5 km/h, assess bus-stop coverage. Non-central TAZs are ranked by daily trips to and from the city centre per square kilometre. For promising zones outside the existing e-scooter operating area, the study assesses bus level of service (LoS) using peak-period frequency adjusted by service reliability. Travel times from selected zones to three points of interest are compared for bus-only and e-scooter-supported travel. The calculations assume e-scooter trips of up to 2.5 km at an average speed of 13.75 km/h. 

Although all analysed areas meet the selected ten-minute bus-stop accessibility threshold, the analysis identifies inequalities in service quality and gaps in shared micromobility coverage. Three high-demand zones (TAZs 513, 516 and 615) fall outside the existing e-scooter service area. E-scooter-supported journeys have lower estimated travel times in eight of nine assessed origin-destination combinations, with reductions ranging from 3.0% to 59.2%. Two service-area expansion scenarios are proposed: a targeted extension to TAZ 615 and a wider extension covering all three zones. They would increase the population within the e-scooter service area by 2.5% and 9.2%, respectively. 

The research offers authorities and operators a transferable, evidence-based framework for prioritising first/last-mile service expansion while considering the trade-off between broader accessibility and operational demands. The estimates describe potential outcomes; they are not measured effects of an implemented expansion.

Supporting evidence

The analysis uses 290 TAZs (932,856 residents), trip matrices assembled for Thessaloniki’s Sustainable Urban Mobility Plan and bus-stop, timetable and 2023 telematics information supplied by the local transport authority. It focuses on journeys between the city centre and other TAZs for work and education. Walking isochrones indicate that all zones are within ten minutes of a bus stop under the study assumptions; this does not mean bus service quality is uniform. 

Of the 17 highest-demand TAZs examined, three (513, 516 and 615) lie outside the current shared e-scooter operating area. Their mean road slopes are 2.3%, 3.3% and 0.45%, respectively. TAZ 615 has the weakest assessed bus connection (LoS D). For journeys to three central destinations, adding e-scooters decreases estimated travel time in eight of nine cases. The largest reduction is from 24.3 to 9.9 minutes (59.2%) for TAZ 615 to POI 1, using an e-scooter alone; one TAZ 516 journey increases from 20.2 to 22.2 minutes (9.9%). 

The current operating area covers 15.932 km² and 364,640 residents. Scenario A expands it to 16.229 km² and 373,870 residents (+2.5% population); Scenario B reaches 16.905 km² and 398,140 residents (+9.2%). These are modelled comparisons, not observed changes following implementation (Tables 1–2).

Key findings

1. Access to a bus stop is not the same as access to an effective public transport service. Although the ten-minute walking analysis identifies no spatial gaps in bus-stop coverage, some districts have less attractive bus frequencies or reliability. First/last-mile micromobility planning should therefore combine spatial accessibility with service quality and demand, rather than rely on stop proximity alone. 
2. An integrated, zone-based screening method can identify potential expansion locations. Ranking work- and education-related demand per square kilometre, checking the existing micromobility boundary, examining terrain and comparing bus LoS directs attention to three high-demand areas outside the current service zone: TAZs 513, 516 and 615. The process can be adapted to other urban areas where suitable transport and spatial data exist. 
3. Integration with micromobility can offer meaningful time savings, particularly where bus LoS is weak. Across the nine assessed connections to three central destinations, estimated travel time improves in eight. TAZ 615, served by a LoS D bus line, shows reductions of 25.4%–59.2%. However, not every combined journey is advantageous: the TAZ 516–POI 2 comparison shows a 9.9% increase, demonstrating the need to test specific routes. 
4. The two proposed expansion options involve different coverage and operational trade-offs. Scenario A prioritises TAZ 615 and increases the population within the operating area by 2.5%, with a 1.9% geographic expansion. Scenario B includes all three TAZs, increasing the served population by 9.2% and the geographic area by 6.1%. The broader option may create greater management, supply and cost challenges. 
5. Planners should use these results as decision support, not as proof of realised impacts. The study estimates potential accessibility and time benefits but does not evaluate an actual deployment, induced public transport ridership, modal shift or emissions reductions. Future work should embed equity and differing residents’ mobility needs in a broader planning tool, alongside infrastructure readiness, budgets and operational feasibility.