A collision avoidance scheme for autonomous vehicles inspired by human social norms

Riaz, Farhan; Jabbar, Sohail; Sajid, Muhammad; Ahmad, Mudassar; Naseer, Kashif; Ali, Nouman

doi:10.1016/j.compeleceng.2018.02.011

Cited by 45 publications

(29 citation statements)

References 12 publications

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“…In the area of transportation management, ABM has been used by Gao et al [62] for evaluating the carrying capacity of a high speed railway and based on the simulations it has been determined that using an adjustment strategy based on the delay times of each train, the carrying capacity of the considered route, namely Beijing-Shanghai, can be increased from 55 to 77 trains per day. Riaz et al [63] have proposed a collision avoidance scheme for autonomous vehicles inspired by human social norms which has underlined the advantages brought by the use of an autopilot. Also, related to the car movement in a parking lot, Vo et al [64] have proposed an ABM in NetLogo and have concluded that pedestrians, drivers' experience and expectations, parking location, speed limit, and maximum parking duration have direct effects on the parking efficiency and safety.…”

Section: Examples Of Agent-based Modeling Applicationsmentioning

confidence: 99%

Modeling the Consumers Opinion Influence in Online Social Media in the Case of Eco-friendly Products

et al. 2019

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Social influence has a positive impact on the purchase intention for eco-friendly products along with other subjective and objective aspects related to environmental attitude, product attitude, and subjective and objective knowledge. Also, exposure to media has been proven to have a significant positive affect on environmental attitude, with effect on the purchase intention. Several recent studies have shown the importance of consumers’ influence in online social networks, underlying the role played by the online environments over consumers’ attitude. As a result, the current research tries to analyze the influence exerted on consumers’ decision to purchase eco-friendly products by their activity in online social environments. Using a questionnaire, filled-in by 409 respondents, a series of variables have been extracted with regard to the eco-friendly products. An agent-based model has been created, fed with the values of the variables extracted from the questionnaire, and used for simulations. As a result, it has been observed that an increase in online media exposure can have a high positive impact on the eco-friendly product adoption. Depending on the type of product—soft or durable good—different times for the eco-friendly product adoption have been determined relatively to the considered variables. Last, the possible limitations of using an agent-based modeling approach are discussed, along with possible extensions and improvements.

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Section: Examples Of Agent-based Modeling Applicationsmentioning

confidence: 99%

Modeling the Consumers Opinion Influence in Online Social Media in the Case of Eco-friendly Products

et al. 2019

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“…Choosing the agent-based modeling (ABM) as a tool for presenting and analyzing the human behavior has been the first choice for a series of researches in the field of transportation [37,38], emergency situations behavior and crowd movements [39,40], healthcare research [41,42], environmental sciences [43,44], social sciences [45], etc. As for the agent-based modeling tools, all the previously mentioned researches have used NetLogo (https://ccl.northwestern.edu/netlogo/), as it provides a comprehensive interface, real-time visualization of agents' actions, a good documentation, basic programming skills, integrated geographic information system (GIS) functionality, integrated graphics, and a good execution speed [46].…”

Section: Agent-based Modeling In Netlogomentioning

confidence: 99%

A Two-Door Airplane Boarding Approach When Using Apron Buses

et al. 2018

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Boarding is one of the major processes of airplane turnaround time, with a direct influence on the airline companies’ costs. From a sustainable point of view, a faster completion of the boarding process has impact not only on the airline company’s long-term performance, but also on customers’ satisfaction and on the airport’s possibility of offering more services without additional investments in new infrastructure. Considering the airplane boarding strategies literature, it can be observed that the latest papers are dealing with developing faster boarding strategies, most of them considering boarding using just one-door of the aircraft. Even though boarding on one-door might be feasible for the airports having the needed infrastructure and sufficient jet-bridges, the situation is different in European airports, as the use of apron buses is fairly common. Moreover, some of the airline companies have adapted their boarding pass in order to reflect which door one should board once they get down from the bus. While using these buses, the boarding strategies developed in the literature are hard to find their applicability. Thus, a new method for boarding on two-door airplanes when apron buses are used is proposed and tested against the actual boarding method. A model is created in NetLogo 6.0.4, taking advantages of the agent-based modeling and used for simulations. The results show a boarding time reduction of 8.91%.

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“…Vehicular safety applications, in addition to helping accident prevention, increase traffic law compliance, improve incident management, and facilitate crash investigations. Other than safe driving, applications which benefit from accurate vehicle positioning include autonomous vehicles, entertainment, traffic light con- 10 trol, assisted driving and detection of accidents [1,2,3,4,5,6]. Vehicle safety applications specifically require accurate positioning systems to improve vehicular navigation.…”

Section: Introductionmentioning

confidence: 99%

“…Vehicle safety applications specifically require accurate positioning systems to improve vehicular navigation. This is the case of lane-level positioning and collision avoidance systems [7,8,9,10]. Nevertheless, the accuracy of GNSS receivers is often not enough.…”

Section: Introductionmentioning

confidence: 99%