An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach

Muhammad Tanveer, Faizan Ahmad Kashmiri, Hassan Naeem, Huimin Yan, Xin Qi, Syed Muzammil Abbas Rizvi, Tianshi Wang and Huapu Lu
Additional contact information
Muhammad Tanveer: Department of Civil Engineering, Tsinghua University, Beijing 100084, China
Faizan Ahmad Kashmiri: Department of Civil Engineering, University of Management and Technology, Lahore 54770, Pakistan
Hassan Naeem: Lahore Transport Company (LTC), Lahore 54000, Pakistan
Huimin Yan: Department of Civil Engineering, Tsinghua University, Beijing 100084, China
Xin Qi: Department of Civil Engineering, Tsinghua University, Beijing 100084, China
Syed Muzammil Abbas Rizvi: School of Transportation, Southeast University, Nanjing 210096, China
Tianshi Wang: Department of Civil Engineering, Tsinghua University, Beijing 100084, China
Huapu Lu: Department of Civil Engineering, Tsinghua University, Beijing 100084, China

Sustainability, 2020, vol. 12, issue 7, 1-22

Abstract: Traffic congestion has become increasingly prevalent in many urban areas, and researchers are continuously looking into new ways to resolve this pertinent issue. Autonomous vehicles are one of the technologies expected to revolutionize transportation systems. To this very day, there are limited studies focused on the impact of autonomous vehicles in heterogeneous traffic flow in terms of different driving modes (manual and self-driving). Autonomous vehicles in the near future will be running parallel with manual vehicles, and drivers will have different characteristics and attributes. Previous studies that have focused on the impact of autonomous vehicles in these conditions are scarce. This paper proposes a new cellular automata model to address this issue, where different autonomous vehicles (cars and buses) and manual vehicles (cars and buses) are compared in terms of fundamental traffic parameters. Manual cars are further divided into subcategories on the basis of age groups and gender. Each category has its own distinct attributes, which make it different from the others. This is done in order to obtain a simulation as close as possible to a real-world scenario. Furthermore, different lane-changing behavior patterns have been modeled for autonomous and manual vehicles. Subsequently, different scenarios with different compositions are simulated to investigate the impact of autonomous vehicles on traffic flow in heterogeneous conditions. The results suggest that autonomous vehicles can raise the flow rate of any network considerably despite the running heterogeneous traffic flow.

Keywords: autonomous vehicle; age; gender; manual vehicle; cellular automata (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)

Downloads: (external link)
https://www.mdpi.com/2071-1050/12/7/2922/pdf (application/pdf)
https://www.mdpi.com/2071-1050/12/7/2922/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:12:y:2020:i:7:p:2922-:d:342135

Access Statistics for this article

Sustainability is currently edited by Ms. Alexandra Wu

More articles in Sustainability from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().