Abstract
The development of underground space is a very complicated process, and the traditional 2D-based approach in engineering is not enough to solve the problems encountered. The 3D visualization brought by BIM technology greatly improves the accuracy of design and construction. This paper’s case is the underground parking lot development project of Shanghai International Shipping Service Center. The underground parking lot design and optimization is based on the Building Information Modeling (BIM)+ traffic simulation technology. And according to the actual condition of the parking lot, we established a safety evaluation index system, and constructed a micro-simulation road network through VISSIM, so that we can determine potential safety conflict points on each floor and make recommendations. Finally, based on fuzzy evaluation theory and analytic hierarchy process, we evaluated the safety level of the underground parking lot. The safety evaluation result shows that the junction of the passageway from the B2 to B1 is the main point of security conflict, and it is necessary to set up corresponding warning signs and guidance measures at these locations. The BIM + traffic simulation technology adopted in this paper is a new model, and this research has reference value for the development of urban underground parking systems.
Keywords: SISSC, Underground parking lot, Development, BIM, Traffic simulation technology, Analytic hierarchy process, Case study.
Received: 25 March 2020 / Revised: 27 April 2020 / Accepted: 19 May 2020/ Published: 8 June 2020
Contribution/ Originality
The paper provide a new mode of BIM technology used: BIM + traffic simulation technology, and this research has reference value for the development of urban underground parking systems.
1. INTRODUCTION
The world is in the process of rapid urbanization. The rapidly expanding cities have higher demand for infrastructure. Effective and integrated use of underground space is of great significance for improving the living standards of cities, especially for densely populated cities [1]. Underground parking lot can effectively use land without reducing the area of green space. It is a very effective method to alleviate urban traffic congestion and solve the problem of difficult parking. In the design and development of underground parking lots, developers focus on the issues of construction area and cost control. A high-economic design scheme of underground parking garage is very essential to control the construction cost of underground parking garages.
The case in this paper is selected from the development project of Shanghai International Shipping Service Center (SISSC). The design and optimization of the underground parking lot is based on BIM + traffic simulation technology. And the final scheme was evaluated for security level, by establishing a fuzzy evaluation model.
The research can provide a reference for the planning and design of urban underground parking systems.
2. LITERATURE REVIEW
The development of underground space is a large-scale and time-consuming project, which requires complicated technology. At the same time, there are a lot of random factors at each stage. These characteristics make it difficult to achieve project goals. The traditional methods mainly based on 2D in engineering are insufficient to solve the problems encountered. The 3D visualization brought by BIM technology has greatly improved the accuracy of design and construction [2]. Not only that, BIM technology can help identify and evaluate risk factors in the project and provide effective support for the entire life cycle of the project. The BIM industry working group [3] said that the British government believes that the use of BIM technology throughout the project life cycle can bring high efficiency and high returns. Through investigation and analysis of 204 construction projects, Hwang, et al. [4] found that projects implementing BIM often have lower rework rates. Ustinovičius, et al. [5] concluded in 《Challenges of BIM technology application in project planning 》that the proper use of BIM technology design can help users avoid mistakes and reduce the loss of financial resources.
The implementation of BIM technology may affect all processes of the project, Howard and Björk [6] emphasized that it should be comprehensively managed rather than treated in isolation as a software tool. The proposal of BIM + theory extends BIM from the technical level to the fields of production organization and operation management. In the article 《From BIM to Geo-analysis: View Coverage and Shadow Analysis by BIM / GIS Integration》, Rafiee, et al. [7] stated that the combination of BIM and GIS can form a more comprehensive system to help urban planners, architects and others carry out analysis for different purposes. The project in this paper used BIM + traffic simulation technology.
Computer simulation technology has been widely used in the field of traffic engineering since the 1970s. In the 1990s, most traffic system simulation applications are based on vehicle-to-vehicle interaction patterns and are microscopic in nature [8]. VISSIM, officially released by PTV Transworld AG in 1993, is a micro-simulation model based on time intervals and driving behavior. It is usually used for traffic modeling of urban transportation and public transportation operations. VISSIM can reproduce the traffic flow under different traffic conditions in the real world [9]. At the same time, it allows users to adjust the model parameters to reflect the traffic conditions under specific actual conditions [10].
3. DESIGN AND OPTIMIZATION OF PARKING GARAGE
3.1. Design Ideas
The design plan of the parking garage should comprehensively consider the specific building space of the parking garage and the actual needs, and scientifically optimize the layout of the parking spaces and parking passages.
(1) Establish the base map according to the initial construction plan of the parking garage.
Mark the relevant information in the base map, including the entrance and exit positions of the parking garage, the available parking space, the location, shape and size of obstacles. Obstacles include building pillars, equipment land, and house land where all parking spaces cannot be constructed.
(2) According to the obstacles and the location of the garage entrance and exit, design the main road distribution plan inside the garage to get the road network distribution map.
(3) Mark the boundary of the main road in the CAD base map according to the distribution of the road network, and import it into the BIM system, and get the design plan automatically.
(4) Use traffic simulation software to conduct safety assessment of internal channels and nodes, readjust and design the parking garage plan, and finally obtain a scientific and reasonable parking garage floor plan.
3.2. Design Scheme
The two initial design schemes are shown in Table 1.
Table-1. Initial design scheme.
Import the base map into the BIM system to get the number of parking spaces for the two options.
Table-2. Number of parking spaces.
Basement 1 |
Basement 2 |
Basement 3 |
|
Scheme 1 |
115 |
480 |
660 |
Scheme 2 |
130 |
515 |
680 |
In the Table 2, it can be seen that the scheme 2 has more parking spaces and higher space utilization, and the location of parking spaces and the direction of parking passages are more reasonable.
Mark the entrance and exit positions of the parking garage, available parking space, obstacles and other related information in the selected design diagram.
The design and optimization plan of the three floors of the parking garage are shown in Table 3. Red is the garage boundary, purple is the parking space, green is the road boundary, black is the obstacle boundary, and pink is the barrier-free parking space boundary.
Table-3. The design and optimization plan.
Basement 1 |
|
Basement 2 |
|
Basement 3 |
4. SAFETY EVALUATION ANALYSIS OF PARKING LOT
4.1. Safety Evaluation Index
Research on safety evaluation indicators can be roughly divided into three categories: risk indicators, accident indicators, and hidden danger indicators. Ex-ante risk assessment mainly uses hidden danger indicators for evaluation.
The study of parking lot traffic safety is a special systematic project. In the process of parking, the probability of a traffic safety accident is low, and the damage and impact of the accident are not very serious. However, from the perspective of system engineering, there are still many conflict points， and these hidden danger indicators for parking safety.
Divide the parking lot into exit and entrance sections and internal sections for safety evaluation.
The evaluation of the entrance and exit sections is mainly based on road network conditions and interference conditions, including the service level of adjacent road sections, obstacle rate of traffic interference, lane length, line-of-sight safety, and service level.
The evaluation of internal sections is mainly based on the situation of conflict points and key passages, including the type of intersection, traffic flow, turning radius, the slope and width of the passage, the number of conflict points, and the flat curve rate of the lane.
4.2. Microscopic Simulation Model of Parking Lot
Use VISSIM micro-simulation software to build a simulation road network and determine potential security conflict points (red circled in Table 4) at each layer. The conflict point has the following characteristics: near the entrance and exit, the traffic volume is relatively large, and the intersection has multidirectional traffic flow. It is recommended to set up safety warning signs and arrange facilitators for control and mediation in the actual operation process.
Table-4. Simulation road network of underground parking lot.
4.3. Fuzzy Comprehensive Evaluation Model
In complex large systems, factors at different levels and different aspects often need to be considered. For such cases, it is usually necessary to classify the set of judgment factors according to attributes, then make a comprehensive evaluation according to the category classification, and finally perform a high-level comprehensive evaluation between the categories on the results of various types of assessment. Fuzzy comprehensive evaluation can be divided into first-level fuzzy evaluation model and multi-level fuzzy evaluation model.
The fuzzy comprehensive evaluation of this paper is multi-level.
Follow the steps below to build a multi-level fuzzy comprehensive evaluation model.
(1) According to an attribute, the evaluation factor set U is divided into m subsets, then make it satisfied ：
then get the second-level evaluation factor set:
U=｛U1，U2，…，Um｝
Ui=｛Uik｝( i =1,2,…, m; k=1,2,…, nk) means that subset Ui contains nk evaluation factors.
(2) For the nk factors in each subset of Ui, assess them according to the single-level fuzzy comprehensive evaluation model. If all factors weight distribution in Ui is Ai, and the evaluation decision matrix is Ri, then get the comprehensive evaluation results of the i subset Ui:
(4) Assess the m subset Ui (i=1,2, …, m) in U comprehensively and get the decision matrix:
If the weight distribution of each factor subset in U is A, then get the comprehensive evaluation results:
In the formula (5), B* is the comprehensive evaluation result of U, and also the comprehensive evaluation result of all evaluation factors in U.
If there are still many factors in U, divide it again then can get multi-level evaluation model. The multi-level fuzzy comprehensive evaluation model can not only show the factors’ different levels, but also avoid the difficulty of weight distribution due to too many factors.
4.4. Safety Evaluation of Basement 1
The B1 area was divided and screened, and 7 intersections and 3 main passages were selected for safety assessment.
4.4.1. Calculation of Weights
According to the analytic hierarchy process (AHP), and the expert's scoring method, compare the importance of the same-layer factor index to the upper-layer factor, then can get pairwise comparison n × n order judgment matrix A. Let.The matrix has the unique nonzero maximum eigenvalue
The five indicators of the intersection evaluation were marked as N11, N12, N13, N14, N15, respectively.
Compare them to each other, then can get the membership degree as shown in Table 5 :
(The membership degree is the qualitative evaluation index to each previous layer, which is the relative weights of each layer of factors.)
Table-5. Weight calculation of various factors at the intersection.
N |
N1 |
N2 |
N3 |
N4 |
N5 |
|
N1 |
1 |
0.5 |
0.5 |
0.33 |
1 |
0.11 |
N2 |
2 |
1 |
0.67 |
0.5 |
1 |
0.17 |
N3 |
2 |
1.5 |
1 |
1 |
2 |
0.27 |
N4 |
3 |
2 |
1 |
1 |
2 |
0.31 |
N5 |
1 |
1 |
0.5 |
0.5 |
1 |
0.14 |
alculate the maximum eigenvalue of each comparison matrix and the corresponding normalized eigenvector, getconsistency ratio
CR<0.1, so this weight matrix is acceptable.
Similarly, the five indicators of passageway evaluation were marked as L11, L12, L13, L14, L15, respectively. The relative weights are shown in Table 6:
Table-6. Weight calculation of each factor in the passageway.
L |
L1 |
L2 |
L3 |
L4 |
L5 |
|
L1 |
1.00 |
1.50 |
0.67 |
0.50 |
1.00 |
0.16 |
L2 |
0.67 |
1.00 |
0.50 |
0.50 |
1.00 |
0.13 |
L3 |
1.50 |
2.00 |
1.00 |
1.50 |
2.00 |
0.29 |
L4 |
2.00 |
2.00 |
0.67 |
1.00 |
1.50 |
0.25 |
L5 |
1.00 |
1.00 |
0.50 |
0.67 |
1.00 |
0.15 |
Consistency ratio CR<0.1, so this weight matrix is acceptable.
4.4.2. Calculation of System Evaluation Values
The following data Table 8 was obtained through VISSIM simulation, including intersection traffic, left-turn vehicle proportion, related car seats, and intersection service level.
Table-8. VISSIM simulation data.
Intersection |
Total flow (veh) |
Left turn |
Straight on |
Right turn |
Ratio of Left turn(%) |
Delay time(s) |
HN1 |
25 |
10 |
15 |
0 |
40% |
0.3 |
HN2 |
30 |
0 |
5 |
25 |
0% |
0.4 |
HN3 |
44 |
0 |
30 |
14 |
0% |
1.1 |
JN1 |
14 |
0 |
14 |
0 |
0% |
0.9 |
JN2 |
34 |
12 |
8 |
14 |
35% |
1.6 |
JN3 |
306 |
272 |
34 |
0 |
89% |
11.1 |
JN4 |
315 |
9 |
306 |
0 |
3% |
5.4 |
JN5 |
374 |
313 |
0 |
61 |
84% |
4.4 |
Entry&Exit |
373 |
-- |
-- |
-- |
-- |
1.7 |
Then normalize the raw data and use it for data analysis. The min-max normalization method used in this project is linear transformation of raw data. Set minA as the minimum values of intersection flow and maxA as maximum values. Map an original value x of A to the value x' in the interval [45,95] through min-max normalization, the formula is:
Score the Intersection turning radius according to the degree of minimum turning radius. If the two values are equal, scores 75. If turning radius is larger, scores 85.
For the different intersection road type, the T-shaped intersection score is 50, and the cruciform intersection score is 30.
The value range of the safety indicators is from 0 to 100, a larger value means a higher safety degree. As shown in Table 9 to Table 11.
Table-9. Intersection evaluation value.
Intersection |
Type |
Flow |
Turning radius (Score) |
Left-turn vehicle ratio |
Delay |
HN1 |
50 |
93.5 |
72.5 |
72.5 |
95.0 |
HN2 |
50 |
92.8 |
95.0 |
95.0 |
94.5 |
HN3 |
50 |
90.8 |
95.0 |
95.0 |
91.3 |
JN1 |
50 |
95.0 |
95.0 |
95.0 |
92.2 |
JN2 |
30 |
92.2 |
75.1 |
75.1 |
89.0 |
JN3 |
50 |
54.4 |
45.0 |
45.0 |
45.0 |
JN4 |
50 |
53.2 |
93.4 |
93.4 |
71.4 |
JN5 |
50 |
45.0 |
47.9 |
47.9 |
76.0 |
Table-10. Passageway evaluation value.
Channel |
Slope |
Width |
Intersection |
Channel traffic flow |
Curvature |
L1 |
100 |
95.0 |
60 |
45.0 |
100 |
L2 |
100 |
57.5 |
80 |
95.0 |
100 |
L3 |
100 |
45.0 |
70 |
92.7 |
100 |
Table-11. Evaluation value of entrance and exit.
Passageway |
E1 |
Service level of adjacent roads |
62 |
Obstacle rate of traffic interference |
100 |
Lane length |
50 |
Exit services level |
80 |
Horizon security |
60 |
.4.3. Analysis of Evaluation Results
According to model , the total safety evaluation score of the system is calculated in Table 12:
Table-12. Evaluation result score.
Intersection |
R |
Color |
HN1 |
80.07 |
|
HN2 |
88.11 |
|
HN3 |
87.32 |
|
JN1 |
85.50 |
|
JN2 |
74.88 |
|
JN3 |
56.53 |
|
JN4 |
74.88 |
|
JN5 |
60.19 |
|
Passageway |
||
L1 |
71.61 |
|
L2 |
85.82 |
|
L3 |
80.31 |
|
Entry & Exit |
||
E1 |
70.57 |
This project uses 4 levels to evaluate the security status of the system, as shown in Table 13.
Table-13. Security scale of evaluation results.
Composite score |
<60 |
60-75 |
75-85 |
85-100 |
Evaluation results |
Bad |
Not bad |
Good |
Great |
Color |
Red |
Orange |
Yellow |
Green |
Identify on the map and shown in Figure 1.
5. CONCLUSION
This case is selected from the development project of Shanghai International Shipping Service Center (SISSC) underground parking lot. The project uses BIM and traffic simulation technology to design and optimize the parking space setting and parking aisle. The final design plan is Table 3. The safety level of the parking lot was evaluated by constructing a micro-simulation road network of the parking lot and establishing a fuzzy comprehensive evaluation model.
The simulation focuses on the peak hours of off-hours. It examines the parking lot operation in the case of concentrated high-density traffic in one direction, and quantitatively evaluates the safety evaluation levels at the entrances and intersections of each floor.
The safety evaluation result shows that the junction of the passageway from the B2 to B1 is the main point of security conflict. The reason is that the passage on the ground floor not only serves the parking spaces on this floor, but also bears the ingress and egress of vehicles on the rest of the floors. In addition, there is a certain security risk at the intersection of each floor near the entrance and exit. Corresponding warning signs and guidance measures should be set at these locations.
This paper provide a new mode of BIM technology used: BIM + traffic simulation technology, and this research has reference value for the development of urban underground parking systems.
Funding: This study received no specific financial support. |
Competing Interests: The authors declare that they have no competing interests. |
Acknowledgement: All authors contributed equally to the conception and design of the study. |
REFERENCES
[1] X. Y. Wang, C. X. Liu, and D. Xu, "Analysis on parking problem for residential area," Applied Mechanics and Materials, vol. 193–194, pp. 1075–1078, 2012. Available at: https://doi.org/10.4028/www.scientific.net/amm.193-194.1075 .
[2] R. Eadie, M. Browne, H. Odeyinka, C. McKeown, and S. McNiff, "BIM implementation throughout the UK construction project lifecycle: An analysis," Automation in Construction, vol. 36, pp. 145–151, 2013. Available at: 10.1016/j.autcon.2013.09.001.
[3] BIM, "BIM Industry working group, A report for the government construction client group building information modelling (BIM) working party strategy paper. Retrieved from http://www.bimtaskgroup.org/wp-content/uploads/2012/03/BISBIM-strategy-Report.pdf . [Accessed January 2013] " 2011
[4] B. G. Hwang, X. Zhao, and K. W. Yang, "Effect of BIM on rework in construction projects in Singapore: Status Quo, magnitude, impact, and strategies," Journal of Construction Engineering and Management, vol. 145, p. 04018125, 2019. Available at: https://doi.org/10.1061/(asce)co.1943-7862.0001600.
[5] L. Ustinovičius, A. Puzinas, J. Starynina, M. Vaišnoras, O. Černiavskaja, and R. Kontrimovičius, "Challenges of BIM technology application in project planning," Engineering Management in Production and Services, vol. 10, pp. 15-28, 2018. Available at: https://doi.org/10.2478/emj-2018-0008.
[6] R. Howard and B.-C. Björk, "Building information modelling–experts’ views on standardisation and industry deployment," Advanced Engineering Informatics, vol. 22, pp. 271-280, 2008. Available at: https://doi.org/10.1016/j.aei.2007.03.001.
[7] A. Rafiee, E. Dias, S. Fruijtier, and H. Scholten, "From BIM to geo-analysis: View coverage and shadow analysis by BIM/GIS integration," Procedia Environmental Sciences, vol. 22, pp. 397-402, 2014. Available at: https://doi.org/10.1016/j.proenv.2014.11.037.
[8] P. Matti, "Simulation of traffic systems-an overview," Journal of Geographic Information and Decision Analysis, vol. 3, pp. 1-8, 1999.
[9] R. Hoyer and M. Fellendorf, "Parametrization of microscopic traffic flow models through image," in Processing. 8h IFAC Symposium on Transportation Systems. Chania, Greece, 1997.
[10] M. Fellendorf and P. Vortisch, "Validation of the microscopic traffic flow model VISSIM in different real-world situations.," in Proceedings of the 80th Annual Meeting of the Transportation Research Board, Washington,DC, USA, 7–11 January 2001, 2001.
Views and opinions expressed in this article are the views and opinions of the author(s), Review of Industrial Engineering Letters shall not be responsible or answerable for any loss, damage or liability etc. caused in relation to/arising out of the use of the content. |