Study on regional road network planning based on time and noise integrated resistance function Haibo Wang 1 School of Civil and Transportation Engineering, Guangdong University of Technology No.100 Waihuan West Road, Higher Education Mega Center, Guangzhou 510006, China Zhipeng Wu 2

School of Civil and Transportation Engineering, Guangdong University of Technology No.100 Waihuan West Road, Higher Education Mega Center, Guangzhou 510006, China Manyi Huang 3

School of Civil and Transportation Engineering, Guangdong University of Technology No.100 Waihuan West Road, Higher Education Mega Center, Guangzhou 510006, China Liang Chen 4

School of Civil and Transportation, Hebei University of Technology

No. 5340 Xiping Road, Beichen District, Tianjin 300401, China Jincai Chen 5,  School of Civil and Transportation Engineering, Guangdong University of Technology No.100 Waihuan West Road, Higher Education Mega Center, Guangzhou 510006, China

ABSTRACT To rationally reduce traffic noise emission from road network from the perspective of planning, a regional traffic flow distribution method combining time and noise integrated resistance function is proposed, and the method is applied in a typical region to verify its reasonability and practicability. Firstly, according to Greenshields model, the relationship among three traffic parameters (velocity, density and flow) is described, and combined with a line-source emission model of traffic noise, a univariate noise prediction model based on flow is established. Then, with the establishing of the traffic noise resistance function, an integrated resistance model considering traffic noise impact and travel time impact is proposed, which is used for traffic flow distribution while in the road network planning process. Finally, the network planning is realized utilizing the proposed method considering traffic noise. A network planning case in a typical region shows that the method can effectively reduce the noise emission of the regional network, which has practical value in traffic environment control. Keywords : Traffic noise, Emission prediction, Integrated resistance, Flow distribution, Network planning

1. INTRODUCTION The acceleration of urbanization is accompanied by the increase of road density and the prosperity of social economy, but also brings about many environmental pollution problems including road traffic

 Correspondence: chenjc@gdut.edu.cn

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noise. Therefore, it is necessary to predict and evaluate the network noise scientifically, and complete the road network planning on this basis, which would be carrying out the goal of reasonable noise control [1-2].

Traffic noise prediction is the basis of traffic noise control, and the most common models are statistical ones based on vehicle noise source emission. Among them, the American FHWA model has been widely applied and improved [3-5]. These models are mainly targeted at sections or specific regions, and have high accuracy when the sections are dominated by steady traffic flow [6]. Based on such models, noise control measures for road networks are mostly focused on the built areas, mainly including emission control [7-9] and propagation attenuation control [10-11]. These noise protection methods have generated additional economic costs, but still cannot fundamentally solve the problem of traffic noise in the urban road network. Therefore, it is a feasible idea to constrain traffic noise emission to achieve source control from the perspective of road network planning: to establish a prediction model with road noise emission as the objective function and traffic flow parameters as the dependent variable, and the relationship between traffic flow parameters constitutes the constraint conditions of the function. When the planning area is extended to the road network, the constraint conditions of the objective function will become relatively complex [12-13], and scholars have carried out abundant studies on this issue. For example, Afandizadeh et al.[14] took environment- related functions (such as vehicle emissions) as the objective function of urban network design, and built a two-level planning model considering travel time, investment cost and other factors. Huang et al.[15] established a two-level programming model considering environmental capacity constraints to maximize road network traffic flow by controlling road network noise emission at the noise capacity threshold. Wang et al.[16] presented a two-layer traffic network design model considering environmental factors, and minimized the total emission cost, total excess noise cost and total system running time by using the Pareto optimization method. Coloma et al.[17] solved the problem of sitting noise-sensitive facilities in the road network by minimizing the total noise threshold and the total system travel time on the underlying road network. These research methods play good roles in dealing with the relationship between traffic emissions and road network design, but they lack flexibility in applying the same traffic noise constraint to the whole region, resulting in the accumulation of traffic costs or noise costs in some regions, which does not meet the actual needs of road network planning.

Therefore, A road resistance function compounding the cost of traffic noise and travel time is established, and a regional traffic flow distribution method based on integrating time and noise resistance is proposed aimed at the road network traffic planning considering noise impact.

2. METHODOLOGY The road network traffic planning considering noise factors is realized through three steps: univariate traffic noise prediction, time and noise integrated road resistance function construction and traffic flow distribution under user equilibrium.

2.1. Univariate traffic noise prediction The road is used as a linear sound source to predict traffic noise based on the traffic flow model. The equivalent sound level L Aeq at the noise receiving point is defined as shown in Equation (1) according to the Chinese standard JTG B03-2006 [18].

  = + −    

Q L L lg TV

(1)

10 16 Aeq o

where, o L is the average noise level of vehicles at the reference point (dB), which can be described

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as Equation (2) according to JTG B03-2006; Q is the traffic flow of the road (veh/h); T is the calculation time (h); v is the road traffic flow speed (km/h).

12.6 34.73lg o L v = + (2) According to Equation (1), the prediction of road traffic noise emission requires certain traffic flow and speed. Considering the limitation of parameters acquisition of planning network, the functional relationship between flow Q and speed v of the planning road are described based on Greenshields model (refer to Equation (3)-(5)), and a univariate traffic noise prediction based on flow Q is built.

  = −      

v K K v

(3)

• 1 j

f

  = −      

2 • j

v Q K v v

(4)

f

2

V v V v K

Q = + + (5)

f f f

2 4

j

where, f v is free-flow speed (km/h); j K is jam density (veh/km).

The influence of road structure and traffic flow is considered in the traffic noise prediction with the help of the traffic flow model. And combined with the parameters form of the planned road network, the establishing process of the modified road traffic noise emission prediction model can be described as follows:

( ) ( ) ( ) ( ) , , eq L f v Q f Q Q v F Q = = = (6)

2.2. Construction of time and noise integrated road resistance function In this study, the road resistance function issued by the Federal Highway Administration of the United States is adopted to describe the travel time cost of traffic participants, as shown in Equation (7).

      = +          

L Q t v C

1 1

(7)

lim

where, 1 t is the time resistance of road section; L is the length (m), lim v is the speed limit (km/h), C is the practical capacity (veh/h).  and  are control parameters ， where 0.15 4   = = ， in this study.

Further, the influence of noise emission is studied and analyzed. According to the limit value of the equivalent sound level of environmental noise stipulated in 4a Class acoustic environmental functional area and the acoustic environmental quality standard [19], this paper intends to set the limit value

min Aeq L as 55dB for subsequent calculation. There is a functional relationship between noise

impedance and traffic impedance as shown in Equation 8:

 −  = 

( )

t L L L t L

＞55

min 1

eq eq eq

＞55 (8)

2

0



eq

where, t 2 is noise resistance;  is control parameter which is set as 0.05.

The time and noise integrated road resistance function can be described as: A=t 1 +t 2 (9)

2.3. Traffic flow distribution under user equilibrium In this study, the mathematical programming model proposed by Beckmann is used to allocate the

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traffic volume of the road network under user equilibrium mode [20]. This method reflects the behavior of the user's choice of path. Since the behavioral choice in any system is based on the maximization of individual interests, this principle accurately reflects the actual situation of users choosing travel routes in the transportation network.

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3. CASE STUDY

3.1. Basic descriptions The area around the Qifeng Park in Dongcheng District, Dongguan, is chosen as the study area in this paper. The scope of the area and road network are shown in Figure1. The size of the area is 12.63km 2 , in which 7 traffic zones and 19 road sections are taken into consideration. And the occurrence and attraction flows of peak hours of each traffic zones are acquired employing a traffic survey.

Dongguan

(a) The scope of the study area

(b) Network of the study area Figure 1: The scope and road network of the study area Based on the design specification of the capacity of one lane in each grade of the road section, the capacity of each section is calculated according to the road grade and the number of lanes between each traffic node, and the capacity of each traffic node is calculated, as shown in Table 1.

Table 1:Section length and capacity between traffic nodes

Road section

Length

Capacity

Road section

Length

Capacity

(km)

(veh/h)

(km)

(veh/h) 1-2 1.6 4200 7-8 0.97 4200 1-4 1 4200 7-11 1.5 4200 2-3 0.9 4200 8-12 1.7 3800 2-9 2 3800 9-10 0.8 4050 3-13 1.2 7500 10-11 0.74 4050 4-5 0.65 4200 10-13 1.25 7500 4-9 1.2 4050 11-12 1.6 4200 5-6 1.6 4200 12-14 2.1 4200 6-7 0.69 4200 13-14 1.5 7500 6-9 0.91 3800

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3.2. Traffic flow distribution of study network The UE equalization mode is adopted to distribute the traffic flow in this region, and the results of road section traffic distribution are shown in Figure 2. Figure 2 (a) are the road resistances of road sections with noise considered, and Figure 2 (b) is the traffic flow distribution result under the comprehensive road resistance function.

(a) Resistances of road sections (b) Flow distribution result

Figre 2: Traffic flow distribution of study network

3.3 ． Traffic noise evaluation analysis of road network The traffic noise and travel time in the initial road network and the optimized road network are calculated respectively. p is defined as travel delay ratio (improved model /UE original model), and q as noise emission ratio (improved model /UE original model). The calculation results of each road section are shown in Figure 3. The results show that:

A. At the view of the whole road network, traffic flow distribution according to the integrated resistance can reduce the road network traffic noise by about 12% ( q =0.88) with a lesser time cost ( p =1.03, a 3% increase in time delay). For a single road section, there is a significant negative correlation between traffic noise and travel time, and reducing traffic noise pollution and road travel delay cannot be achieved at the same time.

B. In this case, 7 of the 19 roads with more travel delays (less flow is distributed) and less serious traffic noise emission, with an integrated resistance consideration in the process of traffic flow distribution, which indicates that these roads have a greater impact on traffic noise, and the

optimization of road structure of these roads can significantly reduce road traffic noise pollution.

C. It should be emphasized that the purpose of this model is to minimize the cost of traffic noise under normal road network travel, which does not necessarily minimize the pollution of traffic noise. However, according to the above research, coordinated control of traffic noise and travel time can achieve the purpose of reducing traffic noise.

Figure 3: Travel delay ratio noise emission ratio of the study area

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4. CONCLUSIONS In this paper, a traffic flow distribution method based on time and noise integrated resistance is proposed and applied to regional road network traffic planning. The road traffic resistance model combining time and noise resistance functions is established. Noise impact can be added to the constraint of the objective function at the beginning of planning to achieve comprehensive traffic noise planning.

The typical case shows that there is a significant negative correlation between traffic noise and travel time for specific sections. But for the whole road network, the road network planning method considering noise impedance can effectively reduce the noise emission of the regional road network. This method can provide a new idea for solving traffic environment pollution.

5. ACKNOWLEDGEMENTS This work was supported by the Basic and Applied Basic Research Project of Guangzhou, China (202102020670), and the Natural Science Foundation of Guangdong Province, China (2018A030310334).

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