An Assessment of Age and Gender Characteristics of Mixed Traffic with Autonomous and Manual Vehicles: A Cellular Automata Approach
Open Access
- 7 April 2020
- journal article
- research article
- Published by MDPI AG in Sustainability
- Vol. 12 (7), 2922
- https://doi.org/10.3390/su12072922
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
This publication has 40 references indexed in Scilit:
- Socioeconomic status and risk of car crash injury, independent of place of residence and driving exposure: results from the DRIVE StudyJournal of Epidemiology and Community Health, 2009
- Novice Drivers' Risky Driving Behavior, Risk Perception, and Crash Risk: Findings From the DRIVE StudyAmerican Journal of Public Health, 2009
- Risks older drivers pose to themselves and to other road usersJournal of Safety Research, 2008
- Cellular automata models of road trafficPhysics Reports, 2005
- Reaction Time, Age, and Cognitive Ability: Longitudinal Findings from Age 16 to 63 Years in Representative Population SamplesAging, Neuropsychology, and Cognition, 2005
- Sex difference in brain nerve conduction velocity in normal humansNeuropsychologia, 2004
- Statistical physics of vehicular traffic and some related systemsPhysics Reports, 2000
- New Modeling Approach for Mixed-Traffic Streams with Nonmotorized VehiclesTransportation Research Record: Journal of the Transportation Research Board, 2000
- Lane change manoeuvres and safety marginsTransportation Research Part F: Traffic Psychology and Behaviour, 1999
- Adult visual choice‐reaction time, age, sex and preparedness: A test of Welford's problem in a large population sampleScandinavian Journal of Psychology, 1985