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<!DOCTYPE html>
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<title>Reinforcement Learning for Traffic Signal Control</title>
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<h2><font color="white">Benchmark dataset</font></h2>
<p class="lead mb-10"><font color="white"><strong><p>The performance of traffic signal control strategies could be largely influenced by simulation environment, road network setting and traffic flow setting. Hence, we provide benchmark datasets including road network and traffic flow data, and provide benchmarking results for referecence. </strong></font></p>
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<h2>Methods for Traffic Signal Control</h2>
<p class="breadcrumb-custom"><a href="index.html">Home</a> <span class="mx-2">></span> <span>Get Started</span> <span class="mx-2">></span> <span>Data Description</span> </p>
<p class="lead mb-5">Here we present a survey about traffic signal control, including introductions on several conventional transportation approaches and comprehensive coverage on RL-based traffic signal control approaches. </p>
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<h2 class="mb-5">List of datasets</h2>
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<div class="caption-content">
<p>We provide different traffic datasets, each includes both road network (roadnet.json) and traffic flow file (flow.json), whose formats are defined in <a href="https://cityflow.readthedocs.io/en/latest/roadnet.html">Roadnet File Format</a> and <a href="https://cityflow.readthedocs.io/en/latest/flow.html">Flow File Format</a> respectively.</p>
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<table class="table">
<caption>*All methods are measured in <a href="https://traffic-signal-control.github.io/TSCC2019/evaluation.html"> Average Travel Time</a> (in seconds) under <a href="https://cityflow-project.github.io/"> CityFlow</a> simulator.</caption>
<!-- <caption>List of method.</caption>-->
<thead>
<tr>
<th>#</th>
<th>Dataset name</th>
<th><br>Number of<br>Intersections<br></th>
<th>Time Span<br>(Seconds)</th>
<th>Description</th>
<th>Referred result*</th>
<th>Referred method</th>
</tr>
</thead>
<tbody>
<tr>
<td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_bc-tyc_18041607_1h"><span>hangzhou_1x1_bc-tyc_18041607_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td rowspan="11">These datasets are based on camera data in Hangzhou. <br>Due to the lack of records about turning vehicles, the turning ratios of each dataset are fixed, with 10% as turning left, 60% as going straight, and 30% as turning right. The turning-right vehicles are discarded since they are not under the control of traffic lights. <br> There are one left-turn lane and one straight lane in each direction in each roadnet.</td>
<td >221.03</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_bc-tyc_18041608_1h"><span>hangzhou_1x1_bc-tyc_18041608_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >334.72</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td>
<a href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_bc-tyc_18041610_1h"><span >hangzhou_1x1_bc-tyc_18041610_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >213.20</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_kn-hz_18041607_1h"><span>hangzhou_1x1_kn-hz_18041607_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >72.48</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_kn-hz_18041608_1h"><span>hangzhou_1x1_kn-hz_18041608_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >64.10</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_qc-yn_18041607_1h"><span>hangzhou_1x1_qc-yn_18041607_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >117.24</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_qc-yn_18041608_1h"><span>hangzhou_1x1_qc-yn_18041608_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >131.99</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_sb-sx_18041607_1h"><span>hangzhou_1x1_sb-sx_18041607_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >173.85</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_sb-sx_18041608_1h"><span>hangzhou_1x1_sb-sx_18041608_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >290.00</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_tms-xy_18041607_1h"><span>hangzhou_1x1_tms-xy_18041607_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >214.77 </td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_1x1_tms-xy_18041608_1h"><span>hangzhou_1x1_tms-xy_18041608_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >325.32</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/syn_1x1_uniform_200_1h"><span>syn_1x1_uniform_200_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td rowspan="3">These datasets are generated artificially. The vehicles enter the road network uniformly with a fixed entering ratio chosen from 200, 400 and 600 vehicles per hour.</td>
<td > 61.44</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/syn_1x1_uniform_400_1h"><span>syn_1x1_uniform_400_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >133.40</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/syn_1x1_uniform_600_1h"><span>syn_1x1_uniform_600_1h</span></a></td>
<td>1</td>
<td>3600</td>
<td >189.11</td>
<td ><a class="nav-link js-scroll-trigger" href="code.html#methods">SOTL</a></td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/hangzhou_4x4_gudang_18010207_1h"><span>hangzhou_4x4_gudang_18010207_1h</span></a></td>
<td>16</td>
<td>3600</td>
<td > The road network contains 16 intersections in a 4x4 grid. Each intersection has four incoming approaches and four outgping approaches, and each approach has three lanes (left-turn, through and right-turn respectively).
<br>The traffic flow data is based on camera data in Hangzhou. Necessary simplification is done due to the low quality of the real-world data.
<br> • Traffic volume: the traffic volume is derived from camera data at Hangzhou. <br> • Turning ratio: 10% (turning left), 60%(going straight) and 30% (turning right). This is synthesized from the statistics of taxi GPS data.
</td>
<td >240.97</td>
<td >MaxPressure</td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/syn_1x3_gaussian_500_1h"><span>syn_1x3_gaussian_500_1h</span></a></td>
<td>3</td>
<td>3600</td>
<td rowspan="4">The road network contains 16 intersections in a 4x4 grid. Each intersection has four incoming approaches and four outgping approaches, and each approach has three lanes (left-turn, through and right-turn respectively).
<br>
• Traffic volume: All the vehicles enter and leave the network from the rim edges.For each entering edge, the number of the vehicles generated is sampled from a Gaussian distribution with mean as 500 vehicles/hour/lane. <br>
• Turning ratio: 10% (turning left), 60%(going straight) and 30% (turning right)
</td>
<td >422.95</td>
<td >MaxPressure</td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/syn_2x2_gaussian_500_1h"><span>syn_2x2_gaussian_500_1h</span></a></td>
<td>4</td>
<td>3600</td>
<td >477.71</td>
<td >MaxPressure</td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/syn_3x3_gaussian_500_1h"><span>syn_3x3_gaussian_500_1h</span></a></td>
<td>9</td>
<td>3600</td>
<td >631.75</td>
<td >MaxPressure</td>
</tr>
<tr height=30 ><td ></td>
<td><a
href="https://github.com/traffic-signal-control/sample-code/tree/master/data/syn_4x4_gaussian_500_1h"><span>syn_4x4_gaussian_500_1h</span></a></td>
<td>16</td>
<td>3600</td>
<td >689.68</td>
<td >MaxPressure</td>
</tr>
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