Subject	Transportation Management
Specific subject area	Bus transit operations
Type of data	Tables and figure •Table 1: Network configuration, geometric design, and intersection signal timing plans (“DIB_Table 1 Network and signal timing data.xlsx”) •Table 2: Bus route operational parameters (“DIB_Table 2 Bus route operations data.xlsx”) •Table 3: Bus boarding and alighting counts and passenger lists by the route and stop (“DIB_Table 3 Bus route B A counts.xlsx”) •Table 4: Node classifications according to the distance from the outbreak point (“DIB_Table 4 Node classification data.xlsx”) •Table 5: The OD matrix of travelers using the bus transit routes in 5-min intervals of the hourly off-peak, adjacent-to-peak, and peak periods (“DIB_Table 5 OD Matrix.xlsx”) •Fig. 1: The geospatial layout of the Xi'an Xiaozhai CBD street network, including details of network nodes, urban street segments, bus routes, and route-specific properties (“DIB_Figure 1 Network.zip”)
How the data were acquired	The current study utilizes the Xi'an Xiaozhai central business district (CBD) street network, which comprises 33 major signalized intersections and 112 bus stops associated with 12 bus routes. The primary data items collected for this study include geospatial data on intersections and bus stops, geometric design of urban streets and intersections, intersection signal timing plans, bus route operational properties, bus-specific parameters, passenger ridership data, as well as travelers' origin and destination (O-D) locations, routes, and departure times. To gather the data details, various methods were employed, including searching government and organizational records, utilizing Alibaba Cloud's Amap platform, conducting onsite measurements, and conducting a field survey.
Data format	Raw
Description of data collection	Data on the latitude and longitude coordinates of intersections and bus stops, as well as the geometric design of urban street segments and intersections, were obtained from Alibaba Cloud's Amap Platform using its API interface and coordinate point function. Each intersection site was assigned a two-person team of graduate students to validate the data details. The field team also verified data on signal timing plans for all 33 intersections, which were obtained from government records. Data regarding bus route-specific operational properties and bus-specific parameters were extracted from the bus operations manual. A field survey was conducted to gather data on bus operations and ridership at each bus stop during off-peak, adjacent-to-peak, and peak periods of a typical weekday. The collected data included information on bus routes, bus IDs, arrival and departure times, as well as the number of boarding and alighting passengers. With the consent of participants, the survey crews also collected additional data on the O-D locations of travelers, the routes they selected, and their departure times while waiting to board. It is important to note that no personally identifiable information was collected during this process. Furthermore, the bus ventilation rate was determined by considering factors such as wind speed and the area of the air outlet within the bus's interior air conditioning system. In addition, geospatial data on the locations of intersections, bus stops, and a major hospital in the study area were utilized to identify the point of the epidemic outbreak.
Data source location	Institution: Chang'an University City/Town/Region: Xi'an Country: China
Data accessibility	Repository name: Dataset for developing optimal headway-based bus dispatching strategy during epidemic outbreaks DOI:10.17632/zc7cjr6532.2 Direct URL to data: http://dx.doi.org/10.17632/zc7cjr6532.2
Related research article	Huang, Y., Li, Z., Zhang, S., Zhou, B., Zhang, L. Optimal Headway-Based Bus Dispatching Strategy under the Influence of Epidemic Outbreaks. Sustain. Cities Soc., 92 (2023) 104468. https://doi.org/10.1016/j.scs.2023.104468.