rooney.design
Optimizing Urban Mobility
Leveraging Lacuna's City Conductor for Data-Driven Transportation Policy and Micromobility Management
How Los Angeles Department of Transportation (LADOT) employees utilized Lacuna’s City Conductor map tools to analyze and improve the state of micromobility in their city through data-driven, geographically-based transportation policies
INTRODUCTION
A Los Angeles Department of Transportation (LADOT) Analyst is tasked with identifying ways of improving urban mobility and transportation efficiency within the city. To achieve this goal, the analyst seeks to utilize Conductor's GIS capabilities to identify trends through micro-mobility operator data (e.g., Bird scooters, Lyft bikes, etc.) and visualization tools like heatmaps & charting. (Note: GIS stands for Geographic Information System and is a system that analyzes and displays geographically referenced information.)
This case study highlights how Conductor's GIS drawing tools enabled LADOT employees to analyze vehicles in the public right of way (PRoW), identify trends over time, create a GeoJSON shape to filter map data results with an (AoI) area of interest, and draft a policy governing the deployment of micro-mobility vehicles in the AoI.
CHALLENGES
- Vehicles in the Public Right of Way (PRoW): The analyst needed to gain a comprehensive understanding of the types and quantities of vehicles occupying the public right of way, including cars (both ride-hailing services like Uber and autonomous vehicles like Waymo), bicycles, electric scooters, and other micromobility devices. Additionally, they sought to identify potential issues such as traffic congestion, PRoW blockages caused by improper parking or over-deployment of micromobility vehicles, and reported accidents.
- Identifying Trends Over Time: The City desired insights into how transportation patterns and the presence of micromobility vehicles change over time. This analysis aimed to identify peak hours of micromobility usage, popular transportation routes, and potential areas with high demand for micromobility services.
- Creating GeoJSON Shape for Data Filtering: The Analyst needed to focus the analysis on a specific area of interest within the city. A GeoJSON shape was to be created to filter and extract relevant data for the designated region.
- Drafting Micromobility Policy: The Analyst needed to draft a comprehensive policy governing the number of micromobility vehicles that a provider could deploy within the city. This policy sought to maintain transportation equity, prevent clutter, and ensure safe and sustainable micromobility operations.
Identifying Key Workflows & User Roles
User Journey: Drawing on the map
SOLUTION
The Analyst leveraged Conductor's map drawing functionality to address each of the following challenges:
- Vehicles in the Public Right of Way (PRoW) Analysis: Conductor integrates various data sources, including GPS data from vehicles, micromobility providers, and traffic sensors, to generate a detailed map of vehicles in the public right of way. Using the map's drawing tools, an analyst could highlight an AoI to see the distribution of different vehicle types and identify problematic hotspots around the city.
- Trends Over Time Analysis: By using historical data and machine learning algorithms, Conductor provided the analyst with insights into micromobility patterns over time within the selected map area. Trends such as peak micromobility usage hours, popular travel routes, and areas with high demand for micromobility services were identified, allowing the analyst to determine where new or adapted policies were needed.
- Creating GeoJSON Shape for Data Filtering: Once the analyst determined a new policy was needed to improve the micromobility behaviors within the selected map region, the analyst used Conductor's Geography creation feature to save a GeoJSON shape of the AoI. This shape allowed for the filtering and processing of data specifically relevant to the designated region, enabling targeted analysis and policy formulation.
- Drafting Micromobility Policy: Using the insights gained from the map visualization, the analyst drafted a comprehensive micromobility policy. This policy specified the maximum number of micromobility vehicles allowed in the area of interest, taking into account factors like population density, transportation demand, and available infrastructure (e.g., bike lanes, scooter parking corrals, etc.). The policy aimed to strike a balance between convenient, equitable access to micromobility services and preventing oversaturation that could lead to clutter and safety hazards.
RESULTS
City Conductor's drawing for policy authoring workflow proved to be highly beneficial for LADOT for the following reasons:
- A detailed analysis of vehicles in the PRoW provided crucial insights into transportation diversity and potential congestion points, supporting better urban mobility planning.
- Trends over time analysis allowed the city to optimize transportation resources, improve public transit, and ensure that micromobility services were available when and where needed most.
- The GeoJSON shape facilitated precise data filtering, streamlining the analysis and policy development process.
- The drafted micromobility policy provided clear guidelines to providers for ensuring sustainable, safe, and equitable transportation solutions for the city.
CONCLUSION
By leveraging Lacuna's City Conductor tool, LADOT employees successfully conducted a comprehensive analysis of vehicles in the public right of way, identified trends over time, created a GeoJSON shape for data filtering, and drafted a well-informed policy for micromobility providers. The tool's advanced capabilities enabled data-driven decision-making, leading to a more efficient, sustainable, and equitable urban transportation system, benefiting both residents and visitors alike. The city's partnership with micromobility providers flourished under the guidance of this dynamic policy framework. LADOT set an example for other urban centers seeking to optimize their transportation networks and improve overall urban mobility.