Mercedes-Benz Düsseldorf: Sustainability Focused Planning with Employee Mobility Analysis
Aim:
Mercedes-Benz Werk Düsseldorf launched a comprehensive mobility study to understand its employees' commuting habits and develop more sustainable transportation solutions. The main objectives of this study are:
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Analyzing current transportation preferences
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Identifying factors that hinder the adoption of sustainable transportation modes
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Developing internal transportation strategies by actively involving employees
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Developing solutions to reduce carbon emissions
Methodology:
A digital survey was conducted via Mapalyse in February 2023 with the participation of 830 employees. The survey addressed the following topics:
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Demographic information
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Commuting habits
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Transportation preferences
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Route safety perceptions
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Openness to alternative mobility options
The survey included map-based location selection, route drawing, a matrix rating scale, single or multiple choice, and open-ended questions, ensuring anonymity.
Sample question: Are there any dangerous spots (risky areas) along your route?
Example: No lighting, no bike path, very heavy traffic, etc.
Please mark a dangerous spot with the (+) symbol and enter a description.
Sample question: How do you usually get to work?
If you use more than one mode of transportation for this route, please specify.
Participants marked their routes, identified the modes of transportation they used, and shared their openness to alternative modes of transportation. All responses were collected anonymously.
Analysis:
As data was collected, analyses were automatically generated through Mapalyse, enabling the following:
We provide multimodal mobility insights in operational, tactical and strategic levels (travel demand analysis, origin-destination analysis, congestion index, queue dynamics, traffic flow, etc.) for future plans by using different mobility data input sources like vehicle, public transportation and location based services.
Transportation mode use was analyzed in different formats such as pie charts and bar charts in order to identify common trends in frequency and demographic distribution.
Quantitative Data
By turning accident related data like accident type, location, road users, infrastructure, weather, etc. into actionable insights (road safety ranking, hotspot analysis, relations with traffic data, etc.) more accurate data-based decisions are enabled.
In particular, the inputs from open-ended responses and security flags were evaluated using thematic analysis, revealing recurring concerns or innovative employee suggestions.
Qualitative Data
By using different data inputs like road side sensors, traveler data, road closures, etc. the more effective, real-time traffic management is provided with comprehensive solutions like dynamic junction management,
integrated corridor management, real-time traffic density and traffic estimation, etc.
Inputs from map-based questions were used to identify the most frequently used corridors and safety risk points.
Spatial Data
Key Findings
Thanks to Mapalyse, Mercedes-Benz management gained in-depth insights into employee mobility:
The most preferred type of transportation: Private vehicle
The main reasons behind vehicle use
The most preferred vehicle and bicycle parking areas
The most effective incentive to increase bicycle use
Openness and expectations regarding the transition to public transport
Prominent action suggestions for sustainable transportation