Automated Crowd Management in Bus Transport Service

Meghana, Achanta V; Sarode, Vedant; Tambade, Dhananjay; Marathe, Abhidnya; Charniya, Nadir N.

doi:10.1109/icesc48915.2020.9155692

“…An imageprocessing technique based on a modified Hough transform is proposed in [104], aimed at detecting the contour features of heads and estimating accordingly the number of passengers and their flow in a bus. Many recent approaches are based on CNNs, such as the passenger counting system proposed in [107], which also exploits the spatio-temporal properties of video sequences acquired on a PT bus in China, or the solution proposed in [108], where crowd density inside a bus is detected and classified in 5 different levels (from very low to very high), to be displayed by LCD screens installed at the bus stops. A deeply-recursive CNN-based solution is proposed in [109] and tested on a dataset of images taken at the Bus Rapid Transit (BRT) in Bejing, China.…”

Section: Optical Camerasmentioning

confidence: 99%

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Darsena

¹

,

Gelli

²

,

Iudice

³

et al. 2023

View full text Add to dashboard Cite

Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus/tram stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs); (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus/tram stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.

show abstract

“…An image-processing technique based on a modified Hough transform is proposed in [93], aimed at detecting the contour features of heads and estimating accordingly the number of passengers and their flow in a bus. Many recent approaches are based on convolutional neural networks (CNNs), such as the passenger counting system proposed in [96], which also exploits the spatio-temporal properties of video sequences acquired on a PT bus in China, or the solution proposed in [97], where crowd density inside a bus is detected and classified in 5 different levels (from very low to very high), to be displayed by LCD screens installed at the bus stops. A deeply-recursive CNNbased solution is proposed in [98] and tested on a dataset of images taken at the Bus Rapid Transit (BRT) in Bejing, China.…”

Section: Optical Camerasmentioning

confidence: 99%

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Darsena¹,

Gelli²,

Iudice³

et al. 2022

Preprint

0

View full text Add to dashboard Cite

<p>Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs); (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.</p>

show abstract

“…An imageprocessing technique based on a modified Hough transform is proposed in [104], aimed at detecting the contour features of heads and estimating accordingly the number of passengers and their flow in a bus. Many recent approaches are based on convolutional neural networks (CNNs), such as the passenger counting system proposed in [107], which also exploits the spatio-temporal properties of video sequences acquired on a PT bus in China, or the solution proposed in [108], where crowd density inside a bus is detected and classified in 5 different levels (from very low to very high), to be displayed by LCD screens installed at the bus stops. A deeply-recursive CNN-based solution is proposed in [109] and tested on a dataset of images taken at the Bus Rapid Transit (BRT) in Bejing, China.…”

Section: Optical Camerasmentioning

confidence: 99%

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Darsena¹,

Gelli²,

Iudice³

et al. 2022

Preprint

0

View full text Add to dashboard Cite

<p>Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with COVID-19 limitations. This paper presents a taxonomy and review of sensing technologies based on Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICT) in order to: (i) monitor and predict crowding events; (ii) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs); (iii) inform in real-time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus stops/stations, and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as, e.g., on-line ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning.</p>

show abstract

Automated Crowd Management in Bus Transport Service

Cited by 8 publications

References 9 publications

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Contact Info

Product

Resources

About