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

Podsumowanie

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.

Streszczenie

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.

Wprowadzenie

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 technologies^1,2,3,4. 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 signalization^6,7, exclusive left turn lanes^8,9, and autonomous vehicles^10,11. 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 exists^16,17. 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 models^20,21, car following models^22,23, U-turn models⁴, and lane change models²¹. The accuracy of traffic flow simulations is widely accepted^16,24. 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.

Protokół

1. Preparation of the equipment

1. 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 easily blocked by large vehicles, videos shot by cameras can be used for vehicle counting. During the investigation, if the weather is rainy or sunny, protection of the equipment is needed. Especially on a sunny day, the equipment may reach a high temperature and shut down, so an umbrella or cooling equipment is needed for this situation.

2. Testing of the equipment

1. Ensure that all investigators are wearing reflective vests.
2. Prepare the radar tripod and extend it as tall as possible. Set the tripod taller than 2 m to avoid signals from being blocked on the roadside.
3. Install the radar on top of the tripod and lock the radar.
4. Set the radar about 0.5 m next to the roadside, adjust the radar vertically, and face the vehicle direction or opposite direction. Keep the angle between the road and radar as small as possible.
   NOTE: The radar can detect 200 m at most. If the radar is set too close to the lane, it may blow over the passing vehicles. Thus, 0.5−1.0 m is the usual distance to the lane.
5. Turn on the power battery and connect the laptop to the power battery. Plug in the radar power cable and plug in the radar data USB to the laptop. When all cables are connected, turn on the laptop.
6. Set the camera next to the radar to shoot the vehicle flow.
7. Opening the radar software
   1. Click Communication check, then select the radar ID number from the dropdown list. It will show Radar Detected with an ID number.
   2. Click Investigation setup. In the pop-up menu, click Read RLU time, and the Device time on the left will change. Then, click Set up RLU time, and PC current time on the left will also change.
   3. Click Start investigation, and the device working status will change from Data recording is not proceeding and No data in device to Data recording in proceeding and Data in device. Click Close to close this dialog box.
   4. Click the Realtime view to check the radar status. A new dialog box will show, and the radar data will be rolled quickly. This means that the radar is detecting the vehicles and works well. Keep this dialog box open until the collection is finished.
      NOTE: The vehicle can be captured by the radar when passing the radar.
   5. Click Close on the dialog box to finish the collection.
   6. Click Investigation setup | End investigation, and confirm in the dialog box. Click the Close button.
   7. Select Data download in the main menu. Click Browse to select a place to save the radar data. Input an individual name for the spreadsheet. Click the Start download button, a progress bar will show, and a dialog box will appear after downloading. Click Confirm to finish data collection.
   8. Click Investigation setup | Erase data record, and confirm it in the next dialog box to clear the internal memory of the radar.
      NOTE: A test of all equipment is needed before departure to the data collection location. Move all the equipment to the data collection location if all the parts work well.

3. Data collection

1. Selection of data collection location (Figure 3)
   1. Select a suitable location that is similar to the intersection type used in the research.
      NOTE: This is the key requirement in location selection. The shape of the location, traffic flow situation, traffic light control, and other controls are all needed in consideration. The more similar the study site, the more accurate the results. A U-turn median opening on the freeway is needed. A sufficiently long line of sight and clearance are required, which is necessary for radar and safety for investigators. Based on the detect distance of the radar and vehicle stop distance, the line of sight should be at least 200 m from the location to an upstream direction.
   2. Check the clearance of the radar direction. Make sure that there are no trees, shrubs, footbridges, traffic signs or streetlights in sight.
   3. Ensure that the location is a safe place for the equipment and investigators. Whether the equipment is set on the roadside or above the road depends on the terrain.
   4. Place the equipment in a secluded place to avoid gaining the driver's attention.
      NOTE: According to prior experience, some drivers may slow down if they see the investigation equipment, which will lead to errors. The data acquisition equipment can be regarded as a measuring device for traffic police to measure speeding vehicles.
2. Collection of traffic data
   1. Choose the collection time.
      1. Collect 3 h of data: 1 h in morning peak, 1 h at noon valley, and 1 h at evening peak.
      2. Check the accurate peak and valley time from the traffic research report, traffic police department, or traffic business companies^25,26 (Figure 4).
         NOTE: If there is no traffic report or analysis as reference, collect 3 h of data during the three periods mentioned above, and choose the highest data.
      3. Input the data with highest traffic volume over a 1 h period into the simulation model and analysis section. Use the remaining 2 h of data for verification at the end.
   2. Setup of the equipment
      1. Adjust the radar direction, and set the camera next to the radar where it can capture all lanes. Repeat the process of installing all equipment in section 2 on the pedestrian bridge.
         NOTE: The clearance before the radar should be as long and wide as possible to cover the whole range of U-turn movements. The EW (east to west) radar faces the traffic flow, and the WE (west to east) radar faces towards the vehicle tails due to road alignment (Figure 5). There are no differences between results from setting up the equipment on the inner vs. outer side of the lanes. The inner or outer side of the radar location only affects the coordinate system of trajectory figures with radar data. When the radar faces traffic flow, the detected running speed is negative and needs to be reversed during data processing. When the radar faces traffic flow, the detected running speed is positive and can be used directly.
      2. Set the radars and cameras so that they are slightly taller than the bridge railings to ensure clearance before the radars and cameras.
         NOTE: There is no need for the radars to be as tall as the roadside settlement.
   3. Ensure that the timing of the radars, laptops, and cameras are consistent with real-time.
   4. Start two radars and cameras simultaneously to schedule time.
   5. Check whether the radars and cameras work normally every 5 min during data collection to ensure that all parts work well.
   6. End the data collection and output the radar data as a spreadsheet with an identified name (Table 1).

4. Data analysis

1. Using calculation software to extract the radar data and draw operating speed and trajectories figures from the spreadsheet.
   NOTE: X/Y coordinates and X/Y speed are in the spreadsheet.
2. Delete obviously discrete points in the figures. These points are radar errors.
   NOTE: The radar detects a large range of area, so the data may contain target vehicles, opposite vehicles, and non-motor vehicles in non-motor vehicle lanes. When plotting all data as figures, the three-lane target vehicles are obvious, and the remaining points are "obviously discrete points". The detection areas are straight in Figure 3, the width of the three lanes is known, and the "obviously discrete points" can be deleted in the software. Plot the necessary points as shown in Figure 6b,d.
3. Replay the traffic videos and count manually to obtain the traffic volume and types.
   NOTE: Vehicles can be divided into cars and trucks according to size. All cars, taxies, and small trucks within 6 m are classified here as cars. All large trucks and buses are classified as trucks.
4. Select the highest traffic volume group as representative data and input it into the simulation described in section 5.
   NOTE: Only one group of data is needed in the simulation and sensitivity analysis. Data from the other two groups will be simulated as verification.

5. Building the simulation model

1. Building of the road
   1. Open the simulation software. Click Map button at the top of the interface and zoom in the map to find the data collection location.
   2. Click Links on the left, then move the cursor to the start location of the link, and right-click. Select Add New Link, input the link name and number of lanes, and click OK. Drag the cursor to draw the link on the map.
   3. Right click the link and select Add Point. Add points and drag points to make the link smoother with real road alignment in the map.
   4. Repeat steps 5.1.2 and 5.1.3 3x to build four segments, except for the U-turn median opening.
   5. Hold the right button of the mouse and Ctrl button on the keyboard, then drag the endpoint of one link to the adjacent link to connect the links. This part is called the "connector" and can be smoother as more points are added.
   6. Repeat step 5.1.5 to connect all links and U-turn routes.
2. Input of the desired speed
   1. Select Base Data from the top bar, then select Distributions | Desired speed.
   2. Click the green-cross Add button at the bottom to add a new desired speed, then name it.
   3. In the Desired Speed Distributions dialog box, input the maximum speed collected from the representative data as the maximum desired speed, then input the average speed calculated from the representative data as the minimum desired speed. Delete the default data.
   4. Input a name for this desired speed, which is usually named using a direction.
   5. Repeat steps 5.2.3 and 5.2.4 to build all desired speeds (WE, EW, WW U-turn, and EE U-turn).
3. Vehicle composition
   1. Select the Lists button from the top bar, then click Private Transport | Vehicle Compositions.
   2. Click the green-cross Add button at the bottom to add a new vehicle composition. Select the desired speed built in step 5.2 as Car.
   3. Click the green-cross Add button to add the vehicle type bus/truck as HGV. Select the same desired speed as done in step 5.3.2.
   4. Input the volume of cars and trucks at RelFlow from the representative data.
   5. Repeat steps 5.3.2-5.3.5 to build all vehicle compositions (WE, EW, WW U-turn, and EE U-turn).
4. Vehicle routes
   1. Select Vehicle Route from the left menu bar.
   2. Move the cursor to the upstream of one link as the start point, right-click, then select Add New Static Vehicle Routing Decision.
   3. Drag the blue cursor representing the vehicle routes in data collection. Repeat this step 4x in WE, EW, WW U-turn, and EE U-turn to draw all vehicle routes.
5. Reduced speed areas
   1. Select Reduced Speed Areas from the left menu bar.
   2. Right-click at the upstream of U-turn opening, then select Add New Reduced Speed Area.
      NOTE: The length of the area depends on the representative data and speed change length.
   3. Build this area in both directions.
6. Conflict areas
   1. Select Conflict Areas from the left menu bar. Four yellow conflict areas will be shown in the median opening section.
   2. Right-click one yellow conflict area and select Set Status to Undetermined as the realistic situation and conflict areas turn red.
   3. Repeat step 5.6.2 for all four conflict areas.
7. Travel time measurement
   1. Select Vehicle Travel Times from the left menu bar.
   2. Right-click at the beginning of one link and select Add New Vehicle Travel Time Measurement.
   3. Drag the cursor to the end of the link to build the one vehicle travel time measurement. Repeat this step for all vehicle routes (WE, EW, WW U-turn, and EE U-turn).
   4. Name each travel time measurement with the corresponding direction.
      NOTE: To compare the operating situations with improvement designs, the length of the travel time measurements needs to be the same in both simulation models.
8. Vehicle input
   1. Select Vehicle Inputs from the left menu bar. Click the starting point of one link and right click to add new vehicle input.
   2. Move the mouse to left bottom and input volume from representative data. Repeat this step for all links.
9. Build another ESUL simulation model as comparison, only the U-turn opening part needs to be modified (Figure 7 and Table 2).
10. Click the blue play button at the top of the interface, and the simulation will start. Drag the scale at the left of the play button, which can adjust the simulation speed.
    NOTE: The instrument button Quick mode can make the simulation speed to the maximum.
11. When the simulation ends, all results will be shown at the bottom of the interface. Copy the results into a new spreadsheet. Here, travel time, delay, and the number of stops are evaluated in the analysis²⁷.

6. Simulation model calibration

1. Input the traffic volume of the representative data into simulation software and perform the simulation (Figure 8a).
2. Compare the traffic volume from the simulation results with the collected data volume.
3. Calculate the capacity using Equation 1 below:
   (1)
   where C denotes the ideal capacity (veh/h) and h_t denotes the average minimum headway (s).
4. Using the capacity, estimate the simulation error as the mean absolute percent error (MAPE) following Equation 2:
   (2)
   where n denotes the four different flows in this study, Cⁱ_v is the capacity simulated in the simulation model (veh/h), and Cⁱ_f is the capacity of the investigation (veh/h). The calculated MAPE is presented in Table 3.
   NOTE: The simulation model can be used if the MAPE is small^28,29,30.
5. Modify the parameters (i.e., random seed, car follow model type, lane change rule, etc.) based on instructions of the simulation software, or check all steps described above when building the simulation model^31,32,33,34.

7. Sensitivity analysis

NOTE: Sensitivity analysis process is shown in Figure 8b. The collected data can only reflect its own performance (Figure 9, Table 4, Table 5, and Table 6). To prove the effectiveness under all situations, all possible traffic situations and different combinations were input into the simulation model to ensure that all situations are covered between the MUTI and ESUL (Figure 10 and Table 7).

1. Select the car/truck (bus) ratio and operating speed of the representative data. Maintain these parameters.
2. Set the U-turn ratio from ~0.03-0.15 in the sensitivity analysis with an increase of 0.03, which means five U-turn ratios in the sensitivity analysis.
   NOTE: According to the representative data in Table 1, the range of the U-turn rate is 0.04-0.15.
3. Set traffic volume from ~0.2-1.0 V/C with an increase of 693 veh/h (0.1 V/C; Table 7), which means nine volumes in the sensitivity analysis.
   NOTE: The maximum traffic volume is 6,930 veh/h in an urban freeway with a three-lane segment, corresponding to service level E according to the AASHTO's Highway Capacity Manual³⁵ when the design speed is 80 km/h.
4. Simulate all 45 situations and save the results in both the present situation (MUTI) and improved situation (ESUL).
5. Verify improvements in travel time and delays by calculating the ratio = (MUTI - ESUL)/MUTI x 100%. Verify improvements in the number of stops by calculating reduced time = MUTI - ESUL.
   NOTE: In the final results (Figure 10), a positive (>0) result means that the ESUL improved the traffic situation, while a negative (<0) result in sensitivity represents the opposite.

Wyniki

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.

Dyskusje

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....

Materiały

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