Evaluation of an Exclusive Spur Dike U-Turn Design with Radar-Collected Data and Simulation
February 1st, 2020
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.
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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Overview
This protocol outlines a method for addressing microscopic traffic issues through simulation. It includes detailed steps for data collection, analysis, model building, calibration, and sensitivity analysis.
Key Study Components
Area of Science
- Traffic simulation
- Data analysis
- Microscopic traffic problems
Background
- Traffic congestion can be exacerbated by U-turn vehicles.
- Radars are used to collect real-time traffic data.
- Simulation models help evaluate traffic improvements.
- Understanding traffic flow dynamics is crucial for urban planning.
Purpose of Study
- To design a U-turn lane that minimizes traffic disruptions.
- To analyze the impact of U-turn vehicles on traffic flow.
- To utilize simulation software for traffic evaluation.
Methods Used
- Data collection using radars for traffic monitoring.
- Simulation modeling with WaSiM software.
- Calibration of simulation models based on collected data.
- Sensitivity analysis to assess model reliability.
Main Results
- Identification of optimal U-turn lane design.
- Demonstrated effectiveness of radar data in traffic analysis.
- Simulation results indicate potential traffic flow improvements.
- Recommendations for future traffic management strategies.
Conclusions
- Simulation is a valuable tool for traffic problem-solving.
- Effective U-turn lane design can enhance traffic safety.
- Real-time data collection is essential for accurate analysis.
Frequently Asked Questions
Executive Industry Relevance
This traffic simulation protocol provides a structured approach to evaluating infrastructure interventions using real-world data collection and modeling. The methodology supports data-driven decision-making in urban planning and transportation engineering by enabling quantitative assessment of design changes before implementation. It offers a replicable framework for assessing localized traffic improvements in controlled environments.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Enables hypothesis testing of infrastructure interventions through controlled simulation environments.
- Operational Value: Supports iterative design evaluation by comparing baseline and modified configurations.
- Predictive Value: Generates quantitative outputs (travel time, delay, stops) to assess functional impact of design changes.
Screening & Assay Development
- Scientific Value: Produces standardized, reproducible traffic performance metrics under defined conditions.
- Operational Value: Establishes calibrated simulation models that reflect real-world data inputs.
- Scalability: Enables repeated testing across multiple scenarios (e.g., peak hours, vehicle mixes) using representative datasets.
Translational & Preclinical Research
- Translational Continuity: Bridges field data collection with computational modeling to validate design efficacy.
- Risk Mitigation: Allows evaluation of design modifications in virtual space prior to physical implementation.
- Decision Support: Provides measurable endpoints to inform go/no-go decisions on infrastructure changes.
Pipeline & Workflow Integration
The method fits within a discovery-to-validation workflow where empirical data informs model development, which in turn enables predictive testing of design alternatives.
- Discovery Biology: Uses radar-based traffic data collection to capture real-world behavioral patterns as baseline observations.
- Screening: Develops simulation models that replicate geometric and operational features for controlled intervention testing.
- Analytics: Derives travel time, delay, and stop frequency as quantitative endpoints to compare design performance.
- Translational Research: Translates field-collected data into simulation inputs to ensure model fidelity and predictive relevance.
- Enterprise Reuse: Establishes a standardized protocol for evaluating localized traffic designs applicable to similar intersection or corridor challenges.
Operational & Enterprise Impact
- Scientific Value: Enables objective, quantitative assessment of design modifications using empirical data-driven models.
- Operational Value: Promotes standardization in data collection, model building, and calibration across evaluation studies.
- Strategic Value: Reduces uncertainty in infrastructure planning by simulating outcomes before physical implementation.
- Portfolio Impact: Supports prioritization of design options based on measurable improvements in traffic flow efficiency.
Implementation Considerations
- Requires expertise in traffic data collection using radar systems and video extraction techniques.
- Dependent on simulation software (WaSiM) and associated infrastructure for model development and execution.
- Necessitates cross-functional coordination between field data collection teams and modeling analysts.
- Requires site-specific conditions including adequate line of sight, equipment placement zones, and safety access.
- Limited to microscopic traffic applications (single intersections or short segments); not scalable to network-level evaluations without additional data.
