Capacity Analysis of Traffic Flow Over a Single-Lane Automated Highway System⋆

Michael, James Bret; Godbole, Datta N.; Lygeros, John; Sengupta, Raja

doi:10.1080/10248079808903736

Cited by 59 publications

(45 citation statements)

References 4 publications

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“…Finally, the assumed sensor arrangement is realistic for current technology. The calculations presented here easily generalize to vehicle models with sensing and actuation delays, lags, and small additive noise [42]. We assume that the sensor ranges are large enough to maintain safety.…”

Section: B Vehicle Modelmentioning

confidence: 99%

“…8 (case ). With minimal changes the estimate can be refined to allow for sensing and actuation delays, safety margins, and different information structures (e.g., vehicles estimating on line) [42]. The results of our calculations can also directly be used in more elaborate throughput estimates that take into account lateral flow (see [44]).…”

Section: Autonomous Vehicle Throughputmentioning

confidence: 99%

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Verified hybrid controllers for automated vehicles

Lygeros¹,

Godbole

Sastry

1998

IEEE Trans. Automat. Contr.

254

120

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Abstract-The objective of an Automated Highway System (AHS) is to increase the safety and throughput of the existing highway infrastructure by introducing traffic automation. AHS is an example of a large scale, multiagent complex dynamical system and is ideally suited for a hierarchical hybrid controller. We discuss the design of safe and efficient hybrid controllers for regulation of vehicles on an AHS. We use game theoretic techniques to deal with the multiagent and multiobjective nature of the problem. The result is a hybrid controller that by design guarantees safety, without the need for further verification. The calculations also provide an upper bound on the performance that can be expected in terms of throughput at various levels of centralization.

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Section: B Vehicle Modelmentioning

confidence: 99%

Section: Autonomous Vehicle Throughputmentioning

confidence: 99%

Verified hybrid controllers for automated vehicles

Lygeros¹,

Godbole

Sastry

1998

IEEE Trans. Automat. Contr.

254

120

View full text Add to dashboard Cite

show abstract

“…With on-board sensors, a judgement of emergency deceleration of the preceding vehicle is based on filtering of the detected speed profile, thus response delay can take up to 0.3 s. With a vehicle-vehicle communication-based system, a clear message of emergency braking can be transmitted from the leading vehicle to its following vehicles, thus response delays can be reduced to a level of 0.1 s (Choi and Hedrick, 1995;Gerdes and Hedrick, 1995;Carbaugh et al, 1998;Michael et al, 1998).…”

Section: Cooperative Systemsmentioning

confidence: 99%

“…Vehicle-vehicle communication was one of the technologies recommended for ACC to ensure string stability (Sheikholeslam and Desoer, 1990). With sensor-based systems, sensor delay can take up to 100 ms, but with a vehicle-vehicle communication-based system, communication delay is normally at a level of 20 ms (Carbaugh et al, 1998;Michael et al, 1998). Bareket et al (2003) studied the string stability impacts of sensor-based ACC using a combination of experiments, models and simulations.…”

Section: Potential Impacts On Capacity and String Stabilitymentioning

confidence: 99%

Advanced Driver Assistance Systems from Autonomous to Cooperative Approach

2008

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“…A white paper [2] 'Capacity Analysis of Traffic Flow over a Single-Lane Automated Highway System', analyses the impact of self-driving vehicles on road capacity. It indicates that if we systematically apply to the leading car, a maximum braking capacity factor lower than the worst car in the platoon, there will be no intra-collision.…”

Section: Road Throughputmentioning

confidence: 99%

Will electric driverless cars kill bus and light train operations?

Themsche¹

2017

Int. J. TDI

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Private transport is associated with conventional cars. Cars pollute, run empty during peak hours, stay idle 95% of the time and are privately owned. Fifteen years from now, the first driverless cars will start hitting the road in large numbers. By then most cars will be electric. If the service-oriented business model takes on momentum, a fleet of unmanned taxis will compete directly with buses and light trains. At that point in time, differences between public and private transport will only be semantic. After all, metro, buses and cars will all be unmanned, electric and managed by a fleet operator. As a consequence, city developers will have problems, justifying subsidies to bus and light vehicle operations. Without these subsidies, buses and light trains will have problems, competing with car transport. Unmanned taxis will cut journey cost by around 60% to 80%. New taxi apps allowing for car sharing will slash cost even further, making unmanned taxi fares unbeatable. Furthermore, driverless taxis will provide better services, picking up and dropping off passengers where they want to rather than stopping at each station. So if unmanned taxis are cheaper and provide better service, what selling arguments are left for buses and light metros? Transport capacity? Not really! In fact, a fleet of unmanned taxis using platooning technology (cars following each other at one-metre distance) and car sharing apps would achieve around 15.000 PPHPD per lane, more than a bus and equal to light train operations.

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Capacity Analysis of Traffic Flow Over a Single-Lane Automated Highway System⋆

Cited by 59 publications

References 4 publications

Verified hybrid controllers for automated vehicles

Verified hybrid controllers for automated vehicles

Advanced Driver Assistance Systems from Autonomous to Cooperative Approach

Will electric driverless cars kill bus and light train operations?

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