The authors would like to acknowledge the China Scholarship Council for partially funding this work was with the file No. 201506560015.

1. Preparation of the equipment
<ol>
	<li>Prepare two of each of the following devices to collect two-direction traffic flows: radars, laptops, batteries and cables for radars and laptops, cameras, and radar and camera tripods. 
	NOTE: The radar and its corresponding software are used to collect vehicle speed and trajectory, and this is more accurate than a speed gun. The radar is not the only choice if other equipment is available for collecting vehicle speed, trajectory, and volume. As radar signals can be easil...

<ol>
	<li>Tang, J. Q., Heinimann, H. R., Ma, X. L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+resilience-oriented+approach+for+quantitatively+assessing+recurrent+spatial-temporal+congestion+on+urban+roads.">A resilience-oriented approach for quantitatively assessing recurrent spatial-temporal congestion on urban roads.</a> PLoS ONE. 13 (1), e0190616 (2018).</li><li>Bared, J. G., Kaisar, E. 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J., Head, K., Yang, X. G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Optimal+Intersection+Operation+with+Median+U-Turn:+Lane-Based+Approach.">Optimal Intersection Operation with Median U-Turn: Lane-Based Approach.</a> Transportation Research Record. (2439), 71-82 (2014).</li><li>Hummer, J. E., Reid, J. E. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Unconventional+Left+Turn+Alternatives+for+Urban+and+Suburban+Arterials-An+Update.">Unconventional Left Turn Alternatives for Urban and Suburban Arterials-An Update.</a> Urban Street Symposium Conference Proceedings. , (1999).</li><li>Ram, J., Vanasse, H. 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B., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Safety+of+U-turns+at+Unsignalized+Median+Opening.">Safety of U-turns at Unsignalized Median Opening.</a> Transportation Research Board. , (2004).</li><li>Yang, X. K., Zhou, G. H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=CORSIM-Based+Simulation+Approach+to+Evaluation+of+Direct+Left+Turn+vs+Right+Rurn+Plus+U-Turn+from+Driveways.">CORSIM-Based Simulation Approach to Evaluation of Direct Left Turn vs Right Rurn Plus U-Turn from Driveways.</a> Journal of Transportation Engineering. 130 (1), 68-75 (2004).</li><li>Guo, Y. Y., Sayed, T., Zaki, M. 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The authors have nothing to disclose.

In this article, the procedure of solving a traffic problem at an intersection or short segment using simulation was discussed. Several points deserve special attention and are discussed in more detail here.
Field data collection is the first thing deserving attention. Some requirements for data collection location are as follows: 1) Finding a suitable location for data collection. The location should be similar to the road geometric shape in the study, which is the premise of data collection....

Some traffic problems, such as traffic congestion at an intersection or short segment, can be solved or improved by optimizing the road design, change signal timing, traffic management measurements, and other transportation technologies1,2,3,4. These improvements either have a positive or negative effect on traffic flow operations compared to the original situations. The changes in traffic operations can be compared in traffic simulation software rather than in actual reconstruction of the intersection or segment. The traffic simulation method is a quick and cheap option when one or more improvement plans are proposed, especially when comparing different improvement plans or evaluating the effectiveness of improvements. This article introduces the process of solving a traffic problem with simulation by evaluating traffic flow operational features of an exclusive spur dike U-turn lane design5.
U-turn movement is a widespread traffic demand that requires a U-turn median opening on the road, but this has been debated. Designing a U-turn opening can cause traffic congestion, while closing the U-turn opening can cause detours for the U-turn vehicles. Two movements, U-turn vehicles and direct left-turn vehicles, require a U-turn opening and cause traffic delays, stops, or even accidents. Some technologies have been proposed to solve the disadvantages of U-turn movements, such as signalization6,7, exclusive left turn lanes8,9, and autonomous vehicles10,11. Improvement potential still exists on U-turn issues, due to the above solutions having restrictive applications. A new U-turn design may be a better solution under certain conditions and be able to address existing problems.
The most popular U-turn design is the median U-turn intersection (MUTI)12,13,14,15, as shown in Figure 1. A significant limitation of the MUTI is that it cannot distinguish U-turn vehicles from passing vehicles and that traffic conflict still exists16,17. A modified U-turn design called the exclusive spur dike U-turn lane (ESUL; Figure 2) is proposed here and aims to diminish traffic congestion by introducing an exclusive U-turn lane on both sides of a median. The ESUL can significantly reduce travel time, delays, and the number of stops due to its channelization of the two flows.
To prove that the ESUL is more efficient than the normal MUTI, a rigorous protocol is needed. The ESUL cannot be actually constructed before a theoretical model; thus, simulation is needed18. Using traffic flow parameters, some key models have been used in simulation research19, such as driving behavior models20,21, car following models22,23, U-turn models4, and lane change models21. The accuracy of traffic flow simulations is widely accepted16,24. In this study, both the MUTI and ESUL are simulated with collected data to compare improvements made by the ESUL. To guarantee accuracy, a sensitive analysis of the ESUL is also simulated, which can apply to many different traffic situations.
This protocol presents experimental procedures for solving real traffic problems. The methods for traffic data collection, data analysis, and analysis of overall efficiency of traffic improvements are proposed. The procedure can be summarized in five steps: 1) traffic data collection, 2) data analysis, 3) simulation model build, 4) calibration of simulation model, and 5) sensitivity analysis of operational performance. If any one of these requirements in the five steps is not met, the process is incomplete and insufficient to prove effectiveness.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Battery</td>
			<td>Beijing Aozeer Technology Company</td>
			<td>LPB-568S</td>
			<td>Capacity: 3.7v/50000mAh. Two ports, DC 1 out:19v/5A (max), for one laptop. DC 2 out:12v/3A (max), for one radar.</td>
		</tr>
		<tr>
			<td>Battery Cable</td>
			<td>Beijing Aozeer Technology Company</td>
			<td>No Catalog Number</td>
			<td>Connect one battery with one laptop.</td>
		</tr>
		<tr>
			<td>Camera</td>
			<td>SONY</td>
			<td>a6000/as50r</td>
			<td>The videos shot by the cameras were 1080p, which means the resolution is 1920*1080.</td>
		</tr>
		<tr>
			<td>Camera Tripod</td>
			<td>WEI FENG</td>
			<td>3560/3130</td>
			<td>The camera tripod height is 1.4m.</td>
		</tr>
		<tr>
			<td>Laptop</td>
			<td>Dell</td>
			<td>C2H2L82</td>
			<td>Operate Windows 7 basic system.</td>
		</tr>
		<tr>
			<td>Matlab Software</td>
			<td>MathWorks</td>
			<td>R2016a</td>
			<td></td>
		</tr>
		<tr>
			<td>Radar</td>
			<td>Beijing Aozeer Technology Company</td>
			<td>SD/D CADX-0037</td>
			<td></td>
		</tr>
		<tr>
			<td>Radar Software</td>
			<td>Beijing Aozeer Technology Company</td>
			<td>Datalogger</td>
			<td></td>
		</tr>
		<tr>
			<td>Radar Tripod</td>
			<td>Beijing Aozeer Technology Company</td>
			<td>No Catalog Number</td>
			<td>Corresponding tripods which could connect with radars, the height is 2m at most.</td>
		</tr>
		<tr>
			<td>Reflective Vest</td>
			<td>Customized</td>
			<td>No Catalog Number</td>
			<td></td>
		</tr>
		<tr>
			<td>VISSIM Software</td>
			<td>PTV AG group</td>
			<td>PTV vissim 10.00-07 student version</td>
			<td></td>
		</tr>
	</tbody>
</table>

evaluation of an exclusive spur dike u-turn design with radar-collected data and simulation

Traditional U-turn designs can improve operational features obviously, while U-turn diversions and merge segments still cause traffic congestion, conflicts, and delays. An exclusive spur dike U-turn lane design (ESUL) is proposed here to solve the disadvantages of traditional U-turn designs. To evaluate the operation performance of ESUL, a traffic simulation protocol is needed. The whole simulation process includes five steps: data collection, data analysis, simulation model build, simulation calibration, and sensitive analysis. Data collection and simulation model build are two critical steps and are described later in greater detail. Three indexes (travel time, delay, and number of stops) are commonly used in the evaluation, and other parameters can be measured from the simulation according to experimental needs. The results show that the ESUL significantly diminishes the disadvantages of traditional U-turn designs. The simulation can be applied to solve microscopic traffic problems, such as in single or several adjacent intersections or short segments. This method is not suitable for larger scale road networks or evaluations without data collection.

Figure 2 shows the illustration of the ESUL for U-turn median opening. WENS mean four cardinal directions. The main road has six lanes with two directions. Greenbelts divide non-motorized lane on both sides and divide the two directions in the middle. Flow 1 is the east to west through traffic, flow 2 is east to east U-turn flow, flow 3 is west to east through traffic, and flow 4 is west to west U-turn traffic.
<p class="jove_content" fo:keep-together.wit...

Watch this Scientific Journal Video about Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation at JoVE.com

Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation

This protocol describes the process of solving a microscopic traffic problem with simulation. The whole process contains a detailed description of data collection, data analysis, simulation model build, simulation calibration, and sensitive analysis. Modifications and troubleshooting of the method are also discussed.

Traditional U-turn designs can improve operational features obviously, while U-turn diversions and merge segments still cause traffic congestion, ...

This video is aiming to show the process of collecting traffic data by radars and evaluation by simulation model. Every time we're passing a U-turn median opening, I have found a way for cars to slow down and even stop. So we want to design a special U-turn lane to make the through and the U-turn vehicles apart, and to reduce the traffic problem caused by the U-turn vehicles.We use radars to collect real traffic data, and use WaSiM simulation software to evaluate the improvement of these close area U-turn lane. Two radars should be used at the same time for both directions of vehicles. Traffic operating situation of morning peak.Meanwhile an evening peak our data should all be collected. Traffic data collection needs two direction data at least. The all necessary equipment needed are as follows:Two radars, laptops, batteries, cables, cameras and corresponding tripods for radars and cameras, a reflective vest is also needed for everyone for safety.Wear the reflective vests for everyone in the beginning. Prepare the radar tripods, extend the tripods as tall as possible. Install the radar on the top of the tripod and lock it.Set a radar next to the roadside, about half a meter. Adjust the radar vertically, and facing the vehicle direction or the opposite direction. Turn on the power battery.Connect laptop to the power battery. Plug in the radar power cable, and plug the radar data USB with the laptop. Then all cables are connected well.Turn on laptop. Set camera next to radar to shot the vehicle flow. Now all equipment installation is done.Open radar software. Click Communication check"Select the radar ID number, and it will show Radar detected"with ID number. Click Investigation set up"Click Read RLU time"and set RLU time successively.Then click Start investigation"and close dialogue box. Click Realtime view"to check the radar status. When the vehicle is passing the radar location, the data will be captured by the radar.That means all parts work well. Close the realtime check window and click Investigation setup"Select End investigation"and confirm it, then close the dialogue box. Select Data download"Browse desktop to save the data and input a name for the file.Click Start download"button. Click Confirm"to finish data collection. Click Investigation setup"and then click Erase data record"and confirm it in the next dialogue box to clear the internal memory of radar.The location must similar to the intersection type in the research. A U-turn median opening on the freeway is needed, long enough line of sight and clearance is required which is necessary for radar and safety for investigators. The location must have enough and safe place for equipment and investigators.Adjust the radar direction. Set the camera next to the radar, where it could capture all lanes. Repeat the process of installing all equipment on the pedestrian bridge.Keep checking all equipment work well during data collection. Extract trajectories and speed from radar data file, and get the traffic volume from videos. Select the highest traffic volume group as a representative data.Open simulation software. Click Internal map"button and zoom in the map to find the data location. Click Links"on left, then move cursor to the start location of the link and right click.Select a new link. Input link name, number of lanes, and then click Ok"Drag the cursor to draw the link on the map. Right click the link, and select Add point"Add points and direct points to make the link smoother with real route alignments in the map.Repeat this step three times to build four segments except the U-turn median opening. Put right button on mouse, and control button on keyboard. Drag the end point of one link to the adjacent link to connect the links.Repeat this step to connect all links and U-turn routes. Select Base data"from top bar. Select Distributions"and click Desired speed"Click ring cross end button at the bottom to add a new desired speed and name it.Input max speed collected from representative data, as high as our speed, and every speed calculated as the minimum desired speed. Delete default data in this desired speed. Select Lists"button from top bar.Click Private transport"then click Vehicle compositions"Click ring cross add button to add a new vehicle composition. Then select Desired speed belt"in last step for cars, and click Add"button to add another vehicle type truck. Input volume of cars and trucks and real flow from representative data.Select Vehicle route"from left menu bar. Move the cursor to upstream the one link as start point. Right click and select Add new static vehicle routing decision"Drag the blue cursor to draw all vehicle routes on the map as real routes.Select Reduced speed areas"from left menu bar. Right click an off route of U-turn opening, then select a new reduced speed area. The length of the area depends on the representative data.Speed change length and build this area for both directions. Select Conflict areas"from left menu bar. Four yellow conflict areas will show at the median opening section.Right click at the yellow area and select Set status"to undetermined as real situation. Select Vehicle travel times"from left. Right click at the beginning of one link, and select Add new vehicle travel time measurement"Drag the cursor to the end of link to build the one vehicle travel time measurement.Repeat this step for all vehicle routes. Select Vehicle inputs"from left, then click start point of one link and right click Add new vehicle input"Then move the mouse to left bottom and input volume from representative data. Repeat this step for all links.Building another ESUL simulation model as comparison. Only the U-turn opening parts need to be modified. Click the blue play button at the top of interface and the simulation will start.Drag the scale at the left of the play button to adjust simulation speed. And the instrument button quick mode can make the simulation speed to the max. When simulation ends, all results will be shown at the bottom of interface.The results will be analyzed in the next step. Input collected data into simulation model. Run the simulation and get the simulation result.Simulation volumes can be generated from the result, then compare with collected volume. The difference between the collected volume and simulated volume is called the mean absolute percent error. The simulation accuracy is acceptable when the MAPE is small.Representative data concludes three groups data:U-turn ratio, volume, and other parameters. Divide U-turn ratio into five categories, divide volume into nine categories, and keep other parameters stable in following situations. So, 45 simulations which covered all situations.All these simulation results verify the effectiveness and improvement of ESUL. Four direction traffic flows are shown in the result with three indexes:Travel time, delay, and the number of stops. The result show the significant improvement of ESUL under all traffic situations.Travel time, delay and the number of stops are three indexes needed in the WaSiM simulation. With the collected data and the simulation result, the improvement of the exclusive U-turn design is all else. We want to solve a realistic problem with an easy method that could be applied into engineering.This method could be used in a single intersection or short segment. The key step in this measure is real traffic data collection and the simulation model built.

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Research

JoVE Journal

Engineering

20.1K Görüntüleme.  Chang'an University. Bu video radarlar ve simülasyon modeli ile değerlendirme trafik verilerinin toplama sürecini göstermek için hedefliyor. Ne zaman U dönüşü ortanca bir açıklığı geçsek, arabaların yavaşlaması ve hatta durması için bir yol buldum. Bu yüzden, u dönüşü araçları birbirinden ayırmak ve U dönüşü araçların neden olduğu trafik sorununu azaltmak için özel bir U dönüşü şeridi tasarlamak istiyoruz.Gerçek trafik verilerini toplamak için radarlar kullanıyo...