smart parking reservation systems - github pages · single criteria smart parking system system...

Smart Parking Reservation Systems

Charles Menne

Division of Science and MathematicsUniversity of Minnesota, Morris

Morris, Minnesota, USA

November 17, 2018

Menne (U of Minn, Morris) Smart Parking Reservation Systems November 17, 2018 1 / 27

Introduction Parking issues

Issues with current parking strategies

Finding an open parking space can be:DifficultTime consumingA result of luck

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Introduction Smart parking

How can smart parking help?

Assist drivers in locating and navigating to an open parking spaceDriver can reserve a parking space through their smartphoneReceive directions to the parking area that you’ve reserved aspace in


Introduction Smart parking

Outline

1 Single criteria smart parking system

2 Multi criteria smart parking system

3 Conclusion


Single criteria smart parking system

Outline

1 Single criteria smart parking systemSystem architectureCost functionSimulation results


3 Conclusion


Single criteria smart parking system

Single criteria smart parking system overview

Pham et al. [1]Goal of reducing time to provide driver with parking spaceFind a parking area at the least cost

Cost based on distance to a parking area and the likelihood of thatarea having an open space

Forward drivers to a new parking area if current one is full


Single criteria smart parking system System architecture

Outline



3 Conclusion



Overview of system architecture



Local unit

Control unitInternet connected controllerAuthenticates driversOpen parking area gateUpdate cloud-based server

ScreenTotal capacityPercentage of free spacesStatus of driver authenticationMini map of parking area


Single criteria smart parking system Cost function

Outline



3 Conclusion



Use of cost function

When a driver first requests a parking spaceIn the event that a driver arrives at a full parking areaLower cost is better



Cost function

Fij(α, β) = α ·dij

Dup+ β ·

tjTup

(1)

ij represent parking areasα and β are coefficients in the range from 0 to 1 inclusive

Sum of both is 1Researchers used simulations to discover good values



Cost function


Dup+ β ·

tjTup

(1)

dij , distance between parking areas i and jDup, greatest maximum distance between any two parking areasα determines importance of this side of equation



Cost function


Dup+ β ·

tjTup

(1)

tj , number of full spaces in parking area jTup, greatest maximum capacity of any parking areaβ determines importance of this side of equation


Single criteria smart parking system Simulation results

Outline



3 Conclusion



Why use simulations?

Implementation is impractical due to costs or timeApproval for implementation can be difficult



Network models

Forwarding modelGreedy model

Figures: Network models taken from [1]



Simulation setup

Parameter Value UnitNumber of vehicles 50, 60, 70, 80, 90, 100 Vehiclesarriving at each car parkInter-arrival rate POIS(15) MinutesService rate EXPO(60) MinutesCoefficient α 0, 0.2, 0.5, 0.8, 1Coefficient β 0, 0.2, 0.5, 0.8, 1

Figure: Simulation parameters modified from [1]



Simulation results

Figure: Average wait time results from [1]


Multi criteria smart parking system

Outline


2 Multi criteria smart parking systemUtility functionSimulation results

3 Conclusion


Multi criteria smart parking system

Multi criteria smart parking system overview

Rehena et al. [2]Goal of taking user preferences into accountFind a parking area with highest utility value

Utility value based on the importance of user preferences andavailable spaces in parking areas


Multi criteria smart parking system Utility function

Outline



3 Conclusion



Use of utility function

Similar to cost function in single criteria systemGives a utility value for each parking areaHigher utility value is better



Utility function

U(Oi) =m∑

k=1

Zk (Oi) · Wk , i = 1,2, ...,n (2)

U utility valueOi is parking area i

n number of parking areas



Utility function

U(Oi) =m∑

k=1

Zk (Oi) · Wk , i = 1,2, ...,n (2)

k represents the criterion being consideredm number of criteria



Utility function

U(Oi) =m∑

k=1

Zk (Oi) · Wk , i = 1,2, ...,n (2)

Zk (Oi), normalized score of criterion k in parking area iWk , weight of importance for criterion k



Utility function

Zk (Oi) =

∣∣∣∣ Oik − Okmin

Okmax − Okmin

∣∣∣∣ (2)

Oik , value of criterion k for parking area iOkmin, minimum value criterion k can beOkmax , maximum value criterion k can beNormalized score in the range from 0 to 1 inclusive


Multi criteria smart parking system Simulation results

Outline



3 Conclusion



Simulation preferences

Criteria being consideredC1 = Distance between parking area and drivers destinationC2 = Price per hour for reserving a spaceC3 = Number of open spaces in parking area

Preference sets

W1 W2 W3Equal priority 0.33 0.33 0.33

Distance priority 0.60 0.20 0.20Price priority 0.20 0.60 0.20



Simulation setup

P1 P2 P3 P4C1 (meter) 500 1900 700 1000C2 (rupee) 50 30 50 40C3 (space) 50 90 20 80




Simulation setup




Simulation results

Figure: Average walking distance for preferences taken from [2]



Simulation results

Figure: Parking occupancy for preference II taken from [2]


Conclusion

Outline



3 Conclusion


Conclusion

Conclusion

Both systems reduce time spent looking for a parking spaceUsing preferences helps a driver obtain a parking space theypreferBoth smart parking systems provide a parking area, not a space


Conclusion

Acknowledgements

Thank you to Nic McPhee and Elena Machkasova for their helpfulfeedback. As well as my friends and family.


Conclusion

Acknowledgements

Thank you to Nic McPhee and Elena Machkasova for their helpfulfeedback. As well as my friends and family.

Questions?


References

References

T. N. Pham, M.-F. Tsai, D. B. Nguyen, C.-R. Dow,and D.-J. Deng.A Cloud-Based Smart-Parking System Based onInternet-of-Things TechnologiesIn IEEE Access, Volume 3, pages 1581-1591, Sep 2015.

Z. Rehena, M. A. Mondal, and M. JanssenA Multiple-Criteria Algorithm for Smart Parking: Making fair andpreferred parking reservations in Smart CitiesIn Proceedings of the 19th Annual International Conference onDigital Government Research: Governance in the Data Age,Article No. 40, May 2018


smart parking reservation systems - github pages · single criteria smart parking system system...

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