Sakarya şehri için dış ve iç yönlendirmeli rezervasyon tabanlı otopark yönetim sistemi tasarımı ve sistem başarımı
Öz
Günümüz şehirlerinin her geçen gün artan nüfus yoğunlukları şehrin çoklu kullanım alanlarının verimli, sağlıklı ve güvenli olarak paylaşılması çalışmalarını zorlaştırmaktadır. Bunun üstesinden gelmek için şehir altyapı planlamalarının geleceğe yönelik revize edilmesi başta olmak üzere şehrin ortak kullanım alanlarının optimize kullanılmasıyla ilgili birçok çözüm stratejisi geliştirilmiştir. Bu altyapı optimizasyonunda en önemli bileşenlerden biri hiç şüphesiz trafik koordinasyonudur. Sağlıklı bir şehiriçi araç parklanma yönetiminin sağlanması günümüz şehirlerinde trafik altyapı koordinasyonunda oldukça önemli bir yere sahiptir. Bu çalışmada çeşitli endüktif sensörler, kameralar ve trafik yönlendirme ve bilgilendirme panoları kullanılarak parklanma sahası içinde veya trafikte hareket halinde olup park yeri bulmaya çalışan araçların en kolay ve en kısa sürede park edebilmesini sağlayacak bir parklanma rezervasyon sistemi geliştirilmiştir. Şehir içerisinde bulunan otoparkların şehir parklanma sorununa katkıda bulunacak koordineli bir yönetim sistemi ile atıl vaziyetten kurtulması ve daha işlevsel hale getirilmesi çalışmanın hedefidir. Kurgulanan akıllı park yönetim sistemi pilot park kapasitesi dikkate alınarak başta sürücülerin güniçi yoğun saatlerde park yeri bulmada yaşadığı ortalama 7.3 dakikayı bulan parklanma süresinin 1.6 dakikaya kadar düşürülebilmesi bununla beraber kazanılan parklanma süresi kısaltımı ile hem trafik akışının sürekliliğine katkıda bulunulacak sadece parklanma yapacak aracın değil trafikte olan diğer araçların CO2 emisyonunun ve yakıt tüketiminin pilot park kapasitesi üzerinden oransal olarak en az %74.5 daha düşük seviyelere çekilmesi ve işgücü zamanının aynı oran üzerinden % 10 arttırılması hedeflenmektedir. Bununla beraber şehir altyapıların daha akıllıca kullanılması ve basitleştirilmiş parklanma verilerinin toplanması ile güniçi atıl durumdan kurtulacak olan park yerlerinin işletme kârlılığının oransal olarak en az %20 arttırılarak park ücretlerinin de %15 minimize edilebilmesi hedeflenmiştir.
Anahtar Kelimeler
Bildirim Panelleri Şehir Içi Akıllı Parklanma Çözümü Trafik Koordinasyonu Ulaşım Sistemi Entegrasyonu
Kaynakça
- [1] Chen, Z., Xia, J.C., Irawan, B., Caulfied, C., 2014, “Development of Location-Based Services For Recommending Departure Stations to Park and Ride Users”, Elsevier, Transportation Research Part C 48, 256–268. [2] Chou, S. Y., Lin, S. W., Li, C. C., 2008, “Dynamic parking negotiation and guidance using an agent-based platform”, Elsevier, Expert Systems with Applications 35, 805–817. [3] Dobre, C., Xhafa, F., 2014, “Intelligent services for Big Data science”, Elsevier, Future Generation Computer Systems 37,267–281. [4] Du, L., Han, L., Li, X. Y., 2014, “Distributed coordinated in-vehicle online routing using mixed-strategy congestion game”, Elsevier, Transportation Research Part B 67, 1–17. [5] Haque, M. M., Chin, H. C., Debnath, A. K., 2013, “Sustainable, safe, smart three key elements of Singapore’s evolving transport policies” , Elsevier, Transport Policy 27, 20–31. [6] Harrison C., 2010, “Foundations for Smarter Cities”, IBM J. Res. & Dev. Vol. 54 No. 4 Paper 1 July/August. [7] Qingquan L., 2011, “Dynamic accessibility mapping using floating car data: a network-constrained density estimation approach”, Elsevier, Journal of Transport Geography 19, 379–393. [8] Mahmud, S. A., Khan, G. M., Rahman, M., Zafar, H., 2013, “A Survey of Intelligent Car Parking System”, Journal of Applied Research and Technology, Faheem et al. / 714‐726. [9] Yamagata, Y., Seya, H., 2013, “Simulating a future smart city: An integrated land use-energy model”, Elsevier, Applied Energy 112 (2013) 1466–1474. [10] Zhong, S., Zhou, L., Ma, S., Jia, N., Wang, X., 2014, “Guidance compliance behaviors of drivers under different information release modes on VMS”, Elsevier, Information Sciences 289, 117–132. [11] Teng, H., Qi, Y., Martinelli D. R.,2008, Parking Difficulty And Parking İnformation System Technologies And Costs, Journal of Advanced Transportation, Vol:42/2, pp.151-178. [12] Shibui, M., Naganawa, T., Ogiwara, M., Yoshikai, N.,2001 , Intelligent parking reservation service on the Internet, Workshops, San Diego, CA, USA, pp.159-164. [13] Caicedo, F., Blazquez, C., Miranda, P.A., 2012, Prediction of parking space availability in real time, Expert Systems with Applications Vol.39(8), pp.7281–7290. [14] Litman, T., 2007, Parking Management Strategies, Evaluation and Planning. Victoria Transport Policy Institute. [15] An S., Lee B., Shin D.,2011, A Survey of Intelligent Transportation Systems, Third International Conference on Computational Intelligence, Communication Systems and Networks. [16] Chen, Z., Sun, R.; Yang, B., 2014, Reservation Based Optimal Parking Lot Recommendation Model in Internet of Vehicle Environment;; CHINA COMMUNICATIONS; Volume: 11 Issue: 10 Pages: 38-48; October. [17] Thompson R G, Richardson A J., 1998, "A parking search model [J].", Transportation Research Part A: Policy and Practice, 32(3): 159–170. [18] Thompson R.G, Takada K., Kobayakawa S.,2001, "Optimization of parking guidance and information systems display configurations [J].", Transportation Research Part C: Emerging Technologies, 9(1): 69–85. [19] Bonsall P, Palmer I.,2014, "Modelling drivers’ car parking behavior using data from a travel choice simulator [J]", Transportation Research Part C: Emerging Technologies,12(5):321–347. [20] Chen M, Hu C, Chang T.,2011, "The research on optimal parking space choice model in parking lots [M]", Computer Research and Development (ICCRD), 2011 3rd International Conference on. IEEE, 93–97. [21] Khandker N H, Mahmoud M S, Coleman J.,2013, "The Effect of Parking Charges at Transit Stations on ‘Park and Ride’ Mode Choice: Lessons Learned from a Stated Preference Survey in Greater Vancouver [M]", Transportation Research Board 92nd Annual Meeting. [22] Gallo M, D'acierno L, Montella B.,2011, "A multilayer model to simulate cruising for parking in urban areas [J]", Transport policy , 18(5): 735–744. [23] Giuffrè T., Siniscalchi S. M., Giovanni T., 2012, “A novel architecture of Parking management for Smart Cities”, Procedia - Social and Behavioral Sciences 53, 16 – 28. [24] Jun C, Zhi-Yong Z, Wei W.,2006, Choice model of parking behaviors in urban [J]. Journal of Traffic and Transportation Engineering, 2006, 2: 27-30.
Öz
Constantly growing population of modern cities makes it difficult to share the public areas efficiently, healty and securely. Especially revising the infrastructures of urban regions according to future, there are a lot of strategies including optimum operating of public areas to overcome this problem. Undoubtedly, one of the most important components of optimization facilities is the traffic coordination. Studies on building the multi-lane roads, subways, undergrounds and pedestrian bridges, positioning the pedestrian and vehicle lanes for these roads, designing the traffic lights according to traffic jam are the most important backbones of the traffic management. Intelligent signalization applications integrated with this backbone, traffic routing and pinboards are some main components of the coordination for this traffic infrastructure. For this reason, the management of city car parking is crucial for this coordination works. In this study, it has been intended to design a system enables cars, in motion at traffic or parking area, to park in a easiest way as soon as possible via various inductive sensors, cameras, traffic routing and pinboards. Intelligent car parking solutions integrated with city traffic management systems have been formed by providing data coordination via cellular and fiber communication infrastructures in accordance to the proposed structure of the system. The parking time with an average of about 7.3 minutes during the day can be reduced by up to 5.3 minutes through considered parking system. Thus, time saving and labor force efficiency will be achieved about 74,5% which means CO2 emissions, are not only for cars in traffic but also for other vehicles, will be reduced at least about 15% in accordance with total pilot parking time. At the same time, more effective utilization of city infrastructure and data collection of simplified parking system will provide us to gain at least 20% operating profit and minimize proportionally parking fees about 15%.
Anahtar Kelimeler
Variable Message Systems(VMS) Smart Parking Traffic Coordination Transportation Integration Systems
Kaynakça
- [1] Chen, Z., Xia, J.C., Irawan, B., Caulfied, C., 2014, “Development of Location-Based Services For Recommending Departure Stations to Park and Ride Users”, Elsevier, Transportation Research Part C 48, 256–268. [2] Chou, S. Y., Lin, S. W., Li, C. C., 2008, “Dynamic parking negotiation and guidance using an agent-based platform”, Elsevier, Expert Systems with Applications 35, 805–817. [3] Dobre, C., Xhafa, F., 2014, “Intelligent services for Big Data science”, Elsevier, Future Generation Computer Systems 37,267–281. [4] Du, L., Han, L., Li, X. Y., 2014, “Distributed coordinated in-vehicle online routing using mixed-strategy congestion game”, Elsevier, Transportation Research Part B 67, 1–17. [5] Haque, M. M., Chin, H. C., Debnath, A. K., 2013, “Sustainable, safe, smart three key elements of Singapore’s evolving transport policies” , Elsevier, Transport Policy 27, 20–31. [6] Harrison C., 2010, “Foundations for Smarter Cities”, IBM J. Res. & Dev. Vol. 54 No. 4 Paper 1 July/August. [7] Qingquan L., 2011, “Dynamic accessibility mapping using floating car data: a network-constrained density estimation approach”, Elsevier, Journal of Transport Geography 19, 379–393. [8] Mahmud, S. A., Khan, G. M., Rahman, M., Zafar, H., 2013, “A Survey of Intelligent Car Parking System”, Journal of Applied Research and Technology, Faheem et al. / 714‐726. [9] Yamagata, Y., Seya, H., 2013, “Simulating a future smart city: An integrated land use-energy model”, Elsevier, Applied Energy 112 (2013) 1466–1474. [10] Zhong, S., Zhou, L., Ma, S., Jia, N., Wang, X., 2014, “Guidance compliance behaviors of drivers under different information release modes on VMS”, Elsevier, Information Sciences 289, 117–132. [11] Teng, H., Qi, Y., Martinelli D. R.,2008, Parking Difficulty And Parking İnformation System Technologies And Costs, Journal of Advanced Transportation, Vol:42/2, pp.151-178. [12] Shibui, M., Naganawa, T., Ogiwara, M., Yoshikai, N.,2001 , Intelligent parking reservation service on the Internet, Workshops, San Diego, CA, USA, pp.159-164. [13] Caicedo, F., Blazquez, C., Miranda, P.A., 2012, Prediction of parking space availability in real time, Expert Systems with Applications Vol.39(8), pp.7281–7290. [14] Litman, T., 2007, Parking Management Strategies, Evaluation and Planning. Victoria Transport Policy Institute. [15] An S., Lee B., Shin D.,2011, A Survey of Intelligent Transportation Systems, Third International Conference on Computational Intelligence, Communication Systems and Networks. [16] Chen, Z., Sun, R.; Yang, B., 2014, Reservation Based Optimal Parking Lot Recommendation Model in Internet of Vehicle Environment;; CHINA COMMUNICATIONS; Volume: 11 Issue: 10 Pages: 38-48; October. [17] Thompson R G, Richardson A J., 1998, "A parking search model [J].", Transportation Research Part A: Policy and Practice, 32(3): 159–170. [18] Thompson R.G, Takada K., Kobayakawa S.,2001, "Optimization of parking guidance and information systems display configurations [J].", Transportation Research Part C: Emerging Technologies, 9(1): 69–85. [19] Bonsall P, Palmer I.,2014, "Modelling drivers’ car parking behavior using data from a travel choice simulator [J]", Transportation Research Part C: Emerging Technologies,12(5):321–347. [20] Chen M, Hu C, Chang T.,2011, "The research on optimal parking space choice model in parking lots [M]", Computer Research and Development (ICCRD), 2011 3rd International Conference on. IEEE, 93–97. [21] Khandker N H, Mahmoud M S, Coleman J.,2013, "The Effect of Parking Charges at Transit Stations on ‘Park and Ride’ Mode Choice: Lessons Learned from a Stated Preference Survey in Greater Vancouver [M]", Transportation Research Board 92nd Annual Meeting. [22] Gallo M, D'acierno L, Montella B.,2011, "A multilayer model to simulate cruising for parking in urban areas [J]", Transport policy , 18(5): 735–744. [23] Giuffrè T., Siniscalchi S. M., Giovanni T., 2012, “A novel architecture of Parking management for Smart Cities”, Procedia - Social and Behavioral Sciences 53, 16 – 28. [24] Jun C, Zhi-Yong Z, Wei W.,2006, Choice model of parking behaviors in urban [J]. Journal of Traffic and Transportation Engineering, 2006, 2: 27-30.
Ayrıntılar
| Birincil Dil | Türkçe |
|---|---|
| Konular | Elektrik Mühendisliği |
| Bölüm | Araştırma Makalesi |
| Yazarlar | |
| Yayımlanma Tarihi | 1 Şubat 2018 |
| Gönderilme Tarihi | 26 Nisan 2016 |
| Kabul Tarihi | 25 Eylül 2017 |
| Yayımlandığı Sayı | Yıl 2018 Cilt: 22 Sayı: 1 |
Kaynak Göster
Cited By
Coğrafi Bilgi Sistemleri Ağ Analizinde Anlık Dinamik Sorgulama Simülasyonu
Afyon Kocatepe University Journal of Sciences and Engineering
Ahmet USLU
https://doi.org/10.35414/akufemubid.598535
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.