Congestion avoidance in city traffic

Kala, Rahul; Warwick, Kevin

doi:10.1002/atr.1290

Cited by 6 publications

(2 citation statements)

References 38 publications

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“…With known travel time on each edge, fastest route is determined using A-star graph traversal algorithm, commonly used in routing simulations [43]. However, velocities in the system change dynamically with agents movement, see equation (2), deprecating initially chosen paths.…”

Section: Agent Behaviour and Communicationmentioning

confidence: 99%

Multiagent Routing Simulation with Partial Smart Vehicles Penetration

Kamiński

Kraiński

Mashatan

et al. 2020

Journal of Advanced Transportation

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e invention and implementation of smart connected cars will change the way how the transportation networks in cities around the world operate. is technological shift will not happen instantaneously-for many years, both human-driven and smart connected vehicles will coexist. In this paper, using a multiagent simulation framework, we model a complex urban transportation system that involves heterogeneous participants. Vehicles are assigned into two groups: the first one consists of smart cars and the second one involves regular ones. Vehicles in the former group are capable of rerouting in response to changes in the observed traffic while regular ones rely on historical information only. e goal of the paper is to analyze the effect of changing smart cars penetration on system characteristics, in particular, the total travelling time. e smart car routing algorithm proposed in this paper reduced travelling time up to 30%. Analysis has shown that the behaviour of the system and optimal configuration of underlying algorithms change dynamically with smart vehicles penetration level.

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Section: Agent Behaviour and Communicationmentioning

confidence: 99%

Multiagent Routing Simulation with Partial Smart Vehicles Penetration

Kamiński

Kraiński

Mashatan

et al. 2020

Journal of Advanced Transportation

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“…The basic mechanism for a lane change is assumed to be an overtaking based lane change [23]. It is assumed that the traffic operates using a 'keep-left' rule and overtaking takes place on the right.…”

Section: Cooperative Lane Changesmentioning

confidence: 99%

Reaching destination on time with cooperative intelligent transportation systems

Kala

2015

J of Advced Transportation

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SUMMARYResearch on intelligent transportation systems is so far focussed on decreasing the travel time of vehicles and avoiding congestions. However, the importance of reaching on time is different for different vehicles and depends upon the purpose of the journey. In a human-operated queue, it is generally considered courteous to give priority to people running very late. They may be running late to catch a flight or may be in an emergency for a medical check-up. There is a very small discomfort to the other people as long as the number of people in an emergency and running late is low. However, such prioritization is an invaluable help to the people running late. In this paper the same behaviour is modelled, wherein the transportation system is made biased towards the vehicles on an important task and running late. The paper presents the mechanism by which a vehicle may judge its running status, decide whether to ask for cooperation and decide how much of cooperation to ask for. The vehicle lane changes and traffic lights operating policy are made cooperative. Experimental results show that such a cooperation leads to lesser number of important vehicles reaching their destinations late.

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