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138

11 - Reduce car rides at traffic peak hours

How to cope with traffic on the Nidfeld 2000-Watt Site in Kriens (LU)

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Topic:

On the Nidfeld site in Kriens, a new neighborhood with apartments and commercial space is currently under construction. To avoid overloading the traffic situation in the area during peak hours, there is a given requirement (by the authorities) on how many cars are allowed to enter and leave the site between 17:00 CEST / 5 PM and 18:00 CEST / 6 PM.

The "Fahrtenmodell" available to the site developer Losinger Marazzi AG estimates that the maximum of 200 entrances and exits will be exceeded once the new site is in use.

Challenge:

Use the "Fahrtenmodell" to gain ideas about reducing the number of car rides during the peak hour. Review / test your solutions based on the "Fahrtenmodell".

Possible Solutions:

Losinger Marazzi's current plan is to slow down the exit barrier to limit the number of exits temporarily. However, there must be a better solution than this. For example, there might be ways to create incentives for residents, workers, and customers to bypass the peak hour or use public transport, bicycles, or car sharing. You are free to think out of the box and come up with solutions that reduce the number of car rides to the allowed maximum.

Data & Tools:

First update:

Initially, we have evaluated different possible solutions to reduce traffic during rush hours caused by residents. Still, on the other hand, we are also questioning the Mobilitätsbüro's calculation, i.e., Google shows that Prodega customers peak around midday-2pm, which would imply that the 10% share of DWV in the peak hours 5pm-6pm seems overly optimistic. We identified two possible stakeholder groups where significant improvements can be made: 1. Residents 2. Prodega customers

Result:

We evaluated possible solutions to reduce traffic during rush hours caused by the key stakeholders: residents and Prodega customers. Although a third group - employees of companies located in the area - contributes to the traffic situation, we focused on the first two groups. Measures for residents and Prodega customers seem to be more feasible than for employees. Before coming up with ideas and evaluating them, we questioned the data that was provided to us. When comparing the numbers of Prodega visitors with the "Popular Times" section for Prodega Kriens on Google, we detected that the number of customers peaked around midday-2pm. This implies that the Mobilitätsbüro assumption that 10% of DWV is from 5pm to 6pm seems overly optimistic.

Key Stakeholders:

  • Residents
  • Prodega customers

 Process:

In the beginning, we sat together to brainstorm. The goal was to get a wide set of ideas prioritized and evaluated in detail. This resulted in the following mindmap containing ideas for residents and Prodega customers: Brainstorming

 Residents:

We believe that financial benefits or other incentives can influence human behavior. Therefore we came up with ideas for residents to not use their cars during rush hour. The following options are among them:

  • Carpooling service via App
  • Partially subsidized car-sharing services
  • Signaling: Control of traffic flow (i.e., sending outgoing traffic in one direction only)
  • Reduced or even free public transport tickets
  • Mobility Car Sharing promotion, i.e., free annual subscription
  • Variable monthly parking fee. I.e., discounts if no exits in peak hours are registered. This may follow a staggered approach, e.g., no departures will give the highest discount, whereas up to 10 exits per month will yield a slightly reduced discount.
  • Free delivery services for residents: We believe a certain share of exits may be attributed to grocery shopping.
  • commercial stores on the ground floor: evaluate supermarket
  • Make the way between the living area and nearest train station more attractive by offering e-mobility solutions like e-scooters or enuu vehicles, attractive pricing necessary.

Prodega:

  • Partially subsidized delivery service for Restaurants
  • Time-dependent discounts. I.e., time the discounts to only be valid during non-peak hours. Prodega's cooperation may be awarded a rent deduction.
  • Promote online shopping services.
  • Promote combined pickup for multiple customers
  • Time-dependent parking fee:
    • Free of charge from 10am-3pm
    • From 4-7pm pm e.g. 5 francs/15minutes.

Screenshot of Simulation Environment

Evaluation of Main Ideas

Variable monthly parking fee for residents and employees

Implement a bonus system for individuals that rent a private parking spot. The default rent is set to above average in the beginning of the month. Residents can reduce their rent by not exiting the area during the peak time slot 5-6 pm. If a certain number of exits or entries during the peak time is not surpassed, the rental price will drop significantly. The App designed for the area could display the savings for each resident.

Area Assessment
Effect Lowers traffic during peak time.
Feasibility Altering the rental price does not require any costly steps. Registration of exit and entrance can be measured either by sensors on the parking spot or by registration of the license plate number at the exit/entrance location.
Financing Above average rental compensates the bonus.
Acceptance As the measure is designed as a bonus and not as a malus system, we assume wide acceptance.
Risk Above average (upfront) prices for parking spots may have a negative impact on attractivity of living area

Time-dependent discounts for Prodega customers

Identify customers that regularly shop during peak times at Prodega. Analyze their shopping behavior and offer time-dependent personal discounts (i.e., use Supercard data). For example: "10% on mayonnaise before 5pm or after 6 pm."

Area Assessment
Effect Altering preferred shopping time for customers
Feasibility Identification of products and customers with the biggest impact is feasible under the condition that the data collection occurs through loyalty cards. Difficult to convince Prodega to participate.
Financing Prodega discount could be financed through a reduction of rent.
Acceptance As the measure is designed as a bonus and not as a malus system we assume wide acceptance. Acceptance of Prodega is questionable.
Risk Prodega is not willing to participate. Cost of discount financing may be too high.

Reduced or free public transport tickets & Subsidized Mobility Car Sharing for residents

Reduced public transport cost for residents may lower car usage. Subsidizing the annual subscription of Mobility Car Sharing for the residents and providing on-premise Mobility Cars might get people not to want to own a car.

Area Assessment
Effect Shift from car to public transport or car sharing results in less traffic.
Feasibility Measure is easily implementable under the condition that financing is solved.
Financing Finance through higher parking spot price or include the discount in the rent.
Acceptance Depends on financing. Public transport discount needs to be conveyed as an extra service.
Risk Strong dependence on the quality of public transport. Public transport discount may not lead to usage.

E-Mobility solutions between living area and nearest/most important train stations

In order to increase usage of public transport the transfer time from the living area to the nearest train station is crucial. To shorten the transfer time, the availability of e-mobility vehicles like e-scooters, e-bikes or e-cars (for example, Enuu) could be ensured. The provider may implement a specific subscription model for residents.

Area Assessment
Effect Attractivity of public transport increases. Shift from car to public transport results in less traffic.
Feasibility Feasible if e-mobility providers are willing to collaborate. 
Financing Fixed cost of loading stations may be financed by the e-mobility providers.
Acceptance Additional mobility offer does not have any negative impact on residents and should be widely accepted.
Risk Usage of e-mobility depends on the weather situation. Constant availability of e-vehicles is difficult to guarantee.

Next Steps:

Before proceeding with further analysis, we strongly recommend to the challenge owner to verify the data provided by the "Mobilitätsbüro" as we can not assure its validity. LUSTAT and Astra may be the right institutions to get in touch with. Unfortunately, we could not communicate with them as we did not get any responses either by phone or by email.

We spent a fair amount of time trying to model the traffic flow using the open-source and state-of-the-art urban mobility modeling software "SUMO". We deem the software's capability as quite significant and thus recommend investing more time in modeling the traffic flow surrounding the area to trial various ideas. We are attaching the developed modeling environment in the following ZIP file: Link

28.11.2020 18:00

Hackathon finished

28.11.2020 15:01

Progress made

noice

-- maurice

28.11.2020 14:59

Documentation

Worked on by niclas

28.11.2020 13:14

Team forming

niclas has joined

28.11.2020 13:14

Team forming

nico has joined

28.11.2020 11:15

Progress made

  • Prototype under development
  • documentation started

-- maurice

27.11.2020 19:45

Progress made

First update posted on project site. Status report sent to challenge owner.

-- maurice

27.11.2020 19:37

Documentation

Worked on by maurice

27.11.2020 16:34

Progress made

Researching

-- maurice

27.11.2020 16:33

Team forming

kosta has joined

27.11.2020 16:33

Team forming

maurice has joined

27.11.2020 09:00

Hackathon started

25.11.2020 16:43

Documentation

Worked on by waarbenz

11.11.2020 19:28

Documentation

Worked on by Marlen

05.11.2020 15:18

Team forming

wdkoelli has joined

30.10.2020 10:35

Team forming

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30.10.2020 09:50

Documentation

Worked on by waarbenz

29.10.2020 15:15

Team forming

waarbenz has joined

29.10.2020 15:15

Project started

Initialized by waarbenz

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