How is the era of information, communication technology and big data changing the way we use various sensors to monitor roadway traffic?
Sensors equipped in vehicles are providing various Vehicle Sensor Data (VSD) including location-based data (LB-VSD) such as location, speed and moving direction, and surrounding traffic data (ST-VSD) under Connected and Automated Vehicles (CAV) environment.
LB-VSD is often referred to as floating car data or probe vehicle data due to the operation mode that the sensor-equipped vehicles travel on roads as regular vehicles. Passengers’ mobile phones and GPS on taxis/buses are continuously producing a gigantic amount of such data, which makes LB-VSD become widely available. In terms of making better use of the data, one could trace driver/passenger’s route (or activity chain); collect link or trip travel time; estimate traffic state; and model/optimize car-hailing services. Moreover, LB-VSD could provide data support for various traffic control and management systems.
ST-VSD is provided by the on-board sensors that can monitor adjacent traffic conditions. It includes, but is not limited to, radar data, Light Detection And Ranging (LIDAR) data, Controller Area Network (CAN) bus data, and the data transmitted via Dedicated Short Range Communication (DSRC) or cellular network. The data provides opportunities to explicitly model traffic flow and design comfortable and environmentally friendly CAV driving strategy, or to develop advanced traffic management and control strategies in CAV environment.
There are strong needs and advantages of utilizing emerging VSD-based big data – advanced tools and innovative ideas/applications of utilizing VSD which could deepen our understanding of traffic congestion and traveler’s behavior, as well as improve the efficiency and capability of traffic control and management. This special issue is thus focused on the recent advances in various transportation research by taking advantage of the widely existing VSD. Potential topics include, but are not limited to, the following:
- VSD-based activity chain identification and modelling
- VSD-based travel time estimation
- VSD-based (day-to-day) route choice dynamics modelling
- VSD-based human/driver mobility characteristics and modelling
- VSD-based incident detection and management
- VSD-based road map inference
- VSD-based traffic congestion identification, estimation, and prediction
- VSD-based intersection/ramp signal control and management
- VSD-based operation monitoring of public transit
- VSD-based analysis and modelling of taxi and car-hailing services
- VSD-based driving safety and accident analysis
- VSD-based CAV driving strategy: efficient, comfortable, environmentally friendly
If you have any questions or would like more information on submitting a paper to the Journal of Intelligent Transportation Systems you can find many of the answers here.
If you have any further questions feel free to contact any of the editorial team below.
- Guest Editor: Zhengbing He, School of Traffic and Transportation, Beijing Jiaotong University (email@example.com)
- Guest Editor: Jia Hu, Federal Highway Administration, U.S. Department of Transportation Turner-Fairbank Highway Research Center (firstname.lastname@example.org)
- Guest Editor: Byungkyu Brian Park, Dept. of Civil and Environmental Engineering, University of Virginia (email@example.com)
- Guest Editor: Michael W. Levin, Department of Civil, Environmental, and Geo-Engineering (firstname.lastname@example.org)