Development and testing of a fully Adaptive Cruise Control system

Bifulco, Gennaro Nicola; Pariota, Luigi; Simonelli, Fulvio; Pace, Roberta Di

doi:10.1016/j.trc.2011.07.001

Cited by 78 publications

(50 citation statements)

References 20 publications

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“…The most efficient algorithm for this aim is the recursive least 1 squares (RLS) algorithm, which can also be applied at run-time, during data collection. Calibration and validation tests 2 carried out in previous works have shown good agreement between simulated and observed trajectories, with typical 3 errors never exceeding 77%, less than 20% in 60% of cases and in 40% of cases less than 10% (Bifulco et al, 2013a). 4 Interestingly, the model is not restricted to the equilibrium car-following condition and does not require identification of 5 the equilibrium spacing.…”

Section: ) 11mentioning

confidence: 79%

Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK

Pariota

Bifulco

Galante

et al. 2016

Accident Analysis & Prevention

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5This paper analyses driving behaviour in car-following conditions, based on extensive individual vehicle data collected 6 during experimental field surveys carried out in Italy and the UK. The aim is to contribute to identify simple evidence to 7 be exploited in the ongoing process of driving assistance and automation which, in turn, would reduce rear-end crashes. 8In particular, identification of differences and similarities in observed car-following behaviours for different samples of 9 drivers could justify common tuning, at a European or worldwide level, of a technological solution aimed at active 10 safety, or, in the event of differences, could suggest the most critical aspects to be taken into account for localisation or 11 customisation of driving assistance solutions. Without intending to be exhaustive, this paper moves one step in this 12 direction. Indeed, driving behaviour and human errors are considered to be among the main crash contributory factors, 13 and a promising approach for safety improvement is the progressive introduction of increasing levels of driving 14 automation in next-generation vehicles, according to the active/preventive safety approach. However, the more 15 advanced the system, the more complex will be the integration in the vehicle, and the interaction with the driver may 16 sometimes become unproductive, or risky, should the driver be removed from the driving control loop. Thus, 17 implementation of these systems will require the interaction of human driving logics with automation logics and then an 18 enhanced ability in modelling drivers' behaviour. This will allow both higher active-safety levels and higher user 19 acceptance to be achieved, thus ensuring that the driver is always in the control loop, even if his/her role is limited to 20 supervising the automatic logic. Currently, the driving mode most targeted by driving assistance systems is longitudinal 21 driving. This is required in various driving conditions, among which car-following assumes key importance because of 22 the huge number of rear-end crashes. 23The increased availability of lower-cost information and communication technologies (ICTs) has enhanced the 24 possibility of collecting copious and reliable car-following individual vehicle data. In this work, data collected from 25 three different experiments, two carried out in Italy and one in the UK, are analysed and compared. The experiments 26 involved 146 drivers (105 Italian drivers and 41 UK drivers). Data were collected by two instrumented vehicles. 27Our analysis focused on inter-vehicular spacing in equilibrium car-following conditions. We observed that (i) the 28 adopted equilibrium spacing can be fitted using lognormal distributions, (ii) the adopted equilibrium spacing increases 29 with speed, and (iii) the dispersion between drivers increases with speed. In addition, according to different headway 30 thresholds (up to 1 second) a significant number of potentially dangerous behaviours is observed. 31Three different car-following paradig...

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Section: ) 11mentioning

confidence: 79%

Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK

Pariota

Bifulco

Galante

et al. 2016

Accident Analysis & Prevention

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“…The system presented in [24], is composed by four modelling layers. The first modelling layer (the modeller) is obtained by learning driver's preferences and is responsible for the main ACC control logic.…”

Section: Application Case Study: Parameter Tuning For An Ecologimentioning

confidence: 99%

“…Earlier examples of Eco-ACC can be found in [22,23]. The analysed system has been presented in [24], and its peculiarity is the human-like characteristic. This means that the control logic is not only focused on kinematic and physical considerations aimed at ensuring safety, but it is also mimic of personal driver's behaviours.…”

Section: Introductionmentioning

confidence: 99%

Modelling components for the fuel consumption investigation in Model In the Loop environment: Parameter tuning for an ecological fully-adaptive cruise control system

Pariota

Pastore

Timpone

2016

2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)

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“…There are several measures which may be implemented by different kinds of decision-makers (such as local administrations, public transport operators and car manufacturers) to optimise the use of transportation systems, for instance by implementing pricing policies [1][2][3], by establishing restricted traffic zones [4], adopting ITS technologies to rationalise private car use [5,6], improving public transport quality [7,8] or implementing energy-saving strategies [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

The use of microsimulation models for the planning and management of metro systems

Placido¹,

D’Acierno²,

Montella³

2014

WIT Transactions on the Built Environment

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The management of public transport for rebalancing the use of transportation systems is a useful tool for reducing negative externalities without excessively affecting zone accessibility. In this context, a rail or metro system can be a key element for producing a high-quality supply of public transport. Obviously, due to the great vulnerability of rail technology to system failures, it is necessary to develop suitable tools to identify rapidly, even with off-line procedures, the best operational strategies which minimise user discomfort produced by such failures. Hence, our proposal is to extend previous models proposed in the literature by considering travel demand as an outcome of a random variable and not only in terms of average values. The proposed approach is applied in the case of a real dimension metro network, considering a wider class of failure contexts.

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Development and testing of a fully Adaptive Cruise Control system

Cited by 78 publications

References 20 publications

Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK

Longitudinal control behaviour: Analysis and modelling based on experimental surveys in Italy and the UK

Modelling components for the fuel consumption investigation in Model In the Loop environment: Parameter tuning for an ecological fully-adaptive cruise control system

The use of microsimulation models for the planning and management of metro systems

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