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（2） Design traffic composition and proportion

Figure 5.3 Traffic composition and vehicle velocity distribution

（3） Other important description

We totally did two simulations, and you can find details in the table below:

Table 5.1 Simulation content

Simulation times Tollbooth pattern Main street Toll lane ETC ETC lane position The first simulation Traditional Honeycomb Tollbooth Tollbooths 3 3 8 8 2 2 Bottom Road The center two lanes The second Simulation Traditional Honeycomb Tollbooth Tollbooths 3 3 8 8 0 0 0 0

Q: Why only consider ETC and artificial charges in the simulation, but do not consider the

exact-change toll pattern？

A: According to the literature [17], the capacity of tollbooths in the United States, MTC (Only pre-sale tickets) 500veh/h, exact-change toll(Collect some coins) 500veh/h. This time only to simulate the above situation, if we consider all the charge pattern, our model will be too complicated. You can find section 5.2 for details.

Q: Why not consider autonomous vehicles?

A: Because autonomous vehicles don’t need driver. The main solution is to install an ETC device on an automatic car. Ignoring the difference in this simulation, the specific impact of autonomous vehicles on the tollbooth is described in section 4.5.

Q: How to explain the great difference between the result of the queueing model and the result of the VISSIM simulation?

A: VISSIM software has taken a lot of factors into consideration. Therefore, compared with the pure theoretical derivation, VISSIM is more practical.

Q: How to explain the great change at the traffic flow 2000veh/h.

A: Both two kinds of toll station have their maximum capacity. Therefore, there will be a great change for the total time cost and the time delayed. We can't eliminate the error between VISSUM and the reality, however, this won't affect our analysis.

5.1.2 Simulation Conclusion

(1) Sensitivity Analysis of Traffic Flow in Honeycomb Tollbooths

According to Fig. 1, Compared with the traditional tollbooth, honeycomb tollbooth is not sensitive to the traffic flow and has strong robustness. It is suitable for practical construction.

Simulation results show that the average transit time remains at about 11 seconds under different throughputs from 0 to 2000 (Unit: veh / h). We can infer that this model is not sensitive to traffic flow variations and has strong robustness which is suitable for practical construction.

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（2）设计交通组成和比例

（3）其他重要说明

我们完全做了两个模拟，您可以在下表中找到详细信息： 表5.1模拟内容

问：为什么在模拟中只考虑ETC和人工费用，而没有考虑精确的费率模式？ 答：根据文献[17]，美国收费站的容量MTC

（只有预售票）500元/小时，精确更换收费（收取一些硬币）500元/小时。这次只是为了模拟上述情况，如果我们考虑所有的收费模式，我们的模式将会太复杂。详情请参阅第5.2节。 问：为什么不考虑自动驾驶汽车？

答：因为自主车辆不需要司机。主要的解决方案是在自动汽车上安装ETC设备。忽略这个模拟的不同之处，第4.5节描述了自动驾驶汽车对收费站的具体影响。

问：如何解释排队模型结果与VISSIM模拟结果之间的巨大差异？

答：VISSIM软件考虑了很多因素。因此，与纯理论推导相比，VISSIM更为实用。 问：如何解释交通流量2000万h / h的巨大变化。

答：两种收费站都有最大的容量。因此总的时间成本和时间推迟会有很大的变化。我们无法消除VISSUM与现实之间的错误，但这不会影响我们的分析。

5.1.2模拟结论

（1）蜂窝收费车流量敏感性分析

根据图1，与传统收费站相比，蜂窝收费站对车流不敏感，鲁棒性强。 适用于实际施工。

仿真结果表明，在0?2000的不同吞吐量下，平均通过时间约为11秒（单位：veh / h）。 我们可以推断出这个模型对交通流量变化不敏感，具有很强的鲁棒性，适用于实际建设。

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Figure 5.4 Traffic capacity changed with traffic flow Table 5.2 Honeycomb Tollbooths(All ETC)

Traffic flow (veh/h) Average time(s)

500 10.778 1000 10.900 2000 11.500 2100 11.567 2200 20.133 2500 22.878 3000 23.444 Car number (veh)

42.778 88.222 180.111 189.556 173.778 184.556 177.000 Delay time(s)

0.056 0.144 0.633 0.667 9.256 12.033 12.578 Stop time(s) 0.000 0.000 0.000 0.000 2.700 3.933 4.522

Stop number

0.000 0.000 0.006 0.001 0.541 0.621 0.723 Table 5.3 Traditional tollbooth(All ETC)

Traffic flow (veh/h) 500 1000 2000 2100 2200 2500 3000 Average time(s)

10.078 10.200 12.078 13.267 47.178 51.222 57.100 Car number

(veh) 43.000 88.444 174.556 179.667 146.889 145.000 151.333 Delay time(s)

0.056 0.100 1.911 3.078 36.422 40.444 46.933 Stop time(s)

0.000 0.000 0.767 1.378 22.567 24.367 30.878 Stop number

0.000 0.000 0.173 0.283 1.944 2.331 2.201

（2）When the toll station is all configured ETC, we can get:

①The throughput of the two toll stations is almost the same in light traffic.

②Honeycomb tollbooth is better than traditional tollbooth in heavy traffic, when traffic flow is 2500veh/h. The VISSIM simulation results show that the honeycomb tollbooth is 55% larger than the traditional tollbooth on total time cost, and about 70% on time delay.

③The simulation results are in good agreement with the results of queuing theory.

It is shown that the queuing theory model is very reasonable to measure the throughput of the honeycomb tollbooth.

（2）Two ETC and six MTC, we can get:

①The throughput of the two toll stations is almost the same in light traffic(<400veh/h) ②The traffic capacity of honeycomb tollbooths will decrease in heavy traffic(>900veh/h). ③The traffic flow between 400 veh/h and 900 veh/h honeycomb tollbooths is stronger than the traditional tollbooth.

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（2）收费站全部配置ETC时，可以得到：

①两个收费站的吞吐量在轻载情况下几乎相同。

②当交通流量为2500时/小时时，蜂窝式收费机在交通繁忙时比传统收费机好。 VISSIM仿真结果表明，蜂窝收费站在总时间成本上比传统收费站大55％，时间延迟约70％。 ③仿真结果与排队论结果吻合较好。

结果表明，排队论模型对蜂窝收费站吞吐量的测量非常合理。

（2）两个ETC和六个MTC，我们可以得到：

①两个收费站的吞吐量在轻载量（<400小时/小时）下几乎相同， ②交通繁忙（> 90000h / h），蜂窝收费站的通行能力下降。 ③400?900辆/ h蜂窝收费车间的车流比传统收费站强。