Does surrounding traffic benefit from an assisted driver with traffic light assistance system?

Preuk, Katharina; Stemmler, Eric; Jipp, Meike

doi:10.1016/j.trf.2016.09.008

Cited by 12 publications

(5 citation statements)

References 19 publications

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“…The simulation results indicated that using SPaT data predictions can reduce fuel and CO 2 emissions up to 47% and 56% respectively while driving through nine controlled intersections. Another example of positive behavioral adaptation was observed in a study by Preuk et al (2016) [16] where vehicles showed smoother speed trajectories and less deviation in speed with less waiting time when provided with assisted driving. It is important to note that all of these benefits are associated with an accurate prediction of traffic signal state information and possible inaccuracies might lead to a very different result.…”

Section: Advisory Traffic Signal Systemsmentioning

confidence: 89%

A methodology for prediction accuracy assessment of intelligent traffic signal control algorithms with SPaT messages

Soni

Calvert

2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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Section: Advisory Traffic Signal Systemsmentioning

confidence: 89%

A methodology for prediction accuracy assessment of intelligent traffic signal control algorithms with SPaT messages

Soni

Calvert

2020

2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC)

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“…This can potentially result in safety benefits, greater energy efficiency, and a decrease in CO2 emissions. Drivers not equipped with C-ITS systems may also potentially benefit from its effects, by experiencing fewer unnecessary changes in speed, or a reduction in start-up delays at junctions (Preuk et al, 2016). Conversely, non-equipped drivers may also be disturbed by 'out-of-the-ordinary' behaviour of equipped vehicles in certain circumstances, e.g.…”

Section: Background To C-itsmentioning

confidence: 99%

Quantifying the impact of a real world cooperative-ITS deployment across multiple cities

Edwards

Hill

Goodman

et al. 2018

Transportation Research Part A: Policy and Practice

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Cooperative Intelligent Transport Systems (C-ITS) -Connected Vehicle Technology in the USA -where vehicle and roadside infrastructure communicates to deliver more intelligent traffic management, is one of a range of ITS technologies emerging as a key component in pursuit of the wider objectives of improved urban mobility. This paper presents the Compass4D project, which deployed a C-ITS system in seven European cities and coordinated the common evaluation of the technology for three services focusing specifically on safety and environmental objectives under real-world driving conditions. The significance of the Compass4D deployments and results provides some of the first evidence of the effectiveness of C-ITS in real world conditions. Both light and heavy vehicles showed efficiency savings of 2-6%. Equipped buses exhibited a variety of results with one pilot site showing a reduction of greater than 200gCO2 per bus route per trip whilst other buses showed an increase in total emissions. The paper presents results from both field trials and microscopic simulation studies (to understand the network-or city-wide impacts of the technology). It discusses the results in detail before outlining the system's potential for further deployment in terms of its impact on energy efficiency and environmental objectives. Government and road operators will benefit from the results to gain an understanding of the potential impact of services given specific deployment characteristics.

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“…Using multidriver simulator experiments, Preuk and colleagues reported that unequipped vehicles’ drivers (UVDs) changed their behavior when a lead vehicle was equipped with traffic light assistance systems ( Preuk et al, 2016 , 2018 ). When a lead vehicle was assisted by traffic light assistance systems, participants (i.e., UVDs) more smoothly passed through intersections despite receiving no prior information about the lead vehicle’s system ( Preuk et al, 2016 ). Even when UVDs received detailed information about the lead vehicle’s system, positive behavioral adaptation was still observed ( Preuk et al, 2018 ).…”

Section: Introductionmentioning

confidence: 99%

Trusting Other Vehicles’ Automatic Emergency Braking Decreases Self-Protective Driving

2020

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Objective We focused on drivers in close proximity to vehicles with advanced driver assistance systems (ADAS). We examined whether the belief that an approaching vehicle is equipped with automatic emergency braking (AEB) influences behavior of those drivers. Background In addition to benefits of ADAS, previous studies have demonstrated negative behavioral adaptation, that is, behavioral changes after introduction of ADAS, by its users. However, little is known about whether negative behavioral adaptation can occur for nonusers in close proximity to vehicles with ADAS. Method Experienced (Experiment 1) and novice (Experiment 2) drivers drove a simulator vehicle without ADAS and tried to pass through intersections. We manipulated participants’ belief about whether an approaching vehicle had AEB and time-to-arrival of the approaching vehicle. Participants kept constant speed or pressed the brake pedal before entering each intersection. In Experiment 2, participants rated their trust in AEB by a questionnaire after driving. Results In both experiments, belief about the approaching vehicle’s AEB did not influence braking probability; however, belief delayed initiation of braking. The effect of belief on braking latency was only observed when trust in AEB was higher in Experiment 2. Conclusion Negative behavioral adaptation can occur for nonusers in close proximity to users of AEB, and trust in AEB plays an important role. Application When evaluating the effect of ADAS, the possible behavioral change of surrounding nonusers as well as users should be taken into account. To establish consumers’ trust accurately, advertisements (e.g., TV commercials) must carefully consider their messages.

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Does surrounding traffic benefit from an assisted driver with traffic light assistance system?

Cited by 12 publications

References 19 publications

A methodology for prediction accuracy assessment of intelligent traffic signal control algorithms with SPaT messages

A methodology for prediction accuracy assessment of intelligent traffic signal control algorithms with SPaT messages

Quantifying the impact of a real world cooperative-ITS deployment across multiple cities

Trusting Other Vehicles’ Automatic Emergency Braking Decreases Self-Protective Driving

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