A field operational test in China: Exploring the effect of an advanced driver assistance system on driving performance and braking behavior

Lyu, Nengchao; Deng, Chao; Xie, Lian; Wu, Chaozhong; Duan, Zhihcheng

doi:10.1016/j.trf.2018.01.003

Cited by 65 publications

(48 citation statements)

References 37 publications

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“…In the absence of such an action, a real crash may occur [19][20][21][22]. Therefore, previous studies presented different definitions for describing near-crashes.…”

Section: The Definition Of a Near-crash Eventmentioning

confidence: 99%

Evaluating the Driving Risk of Near-Crash Events Using a Mixed-Ordered Logit Model

et al. 2018

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Abstract:With the considerable increase in ownership of motor vehicles, traffic crashes have become a challenge. This paper presents a study of naturalistic driving conducted to collect driving data. The experiments were performed on different road types in the city of Wuhan in China. The collected driving data were used to develop a near-crash database, which covers driving behavior, near-crash factors, driving environment, time, demographics, and experience. A new definition of near-crash events is also proposed. The new definition considers potential risks in driving behavior, such as braking pressure, time headway, and deceleration. A clustering analysis was carried out through a K-means algorithm to classify near-crash events based on their risk level. In addition, a mixed-ordered logit model was used to examine the contributing factors associated with the driving risk of near-crash events. The results indicate that ten factors significantly affect the driving risk of near-crash events: deceleration average, vehicle kinetic energy, near-crash causes, congestion on roads, time of day, driving miles, road types, weekend, age, and experience. The findings may be used by transportation planners to understand the factors that influence driving risk and may provide valuable insights and helpful suggestions for improving transportation rules and reducing traffic collisions thus making roads safer.

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“…In the absence of such an action, a real crash may occur [19][20][21][22]. Therefore, previous studies presented different definitions for describing near-crashes.…”

Section: The Definition Of a Near-crash Eventmentioning

confidence: 99%

Evaluating the Driving Risk of Near-Crash Events Using a Mixed-Ordered Logit Model

et al. 2018

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“…In this trial, around 25% of forward collision warnings were found to be false positives. In China, a study was conducted by Lyu et al [20], in order to determine the effect that Mobileye M630 had on the driving performance and braking behaviour of 32 car drivers. The ADAS system was shown to have a significant effect on braking behaviour, with drivers tending to increase braking time and reducing relative speeds.…”

Section: Collision Warning Advanced Driver-assistance Systemsmentioning

confidence: 99%

Advanced Driver-Assistance Systems for City Bus Applications

Blades¹,

Douglas²,

Early³

et al. 2020

SAE Technical Paper Series

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The bus sector is currently lagging behind when it comes to implementing autonomous systems for improved vehicle safety. However, in cities such as London, public transport strategies are changing, with requirements being made for advanced driverassistance systems (ADAS) on buses. This study discusses the adoption of ADAS systems within the bus sector. A review of the onroad ADAS bus trials shows that passive forward collision warning (FCW) and intelligent speed assistance (ISA) systems have been successful in reducing the number of imminent pedestrian/vehicle collision events and improving speed limit compliance, respectively. Bus accident statistics for Great Britain have shown that pedestrians account for 82% of all fatalities, with three quarters occurring with frontal bus impacts. These statistics suggest that the bus forward collision warning system is a priority for inclusion in future vehicles to enhance the driver's direct vision, and to increase reaction time for earlier brake application. Almost 80% of bus occupant casualties occurred in non-impact situations, mainly during acceleration/deceleration events. Therefore, care must be taken in implementing autonomous braking in buses, to ensure that it does not cause an increased number of deceleration events beyond the safe stability limits for passengers. Real on-road drive cycle data has shown that while instances of unsafe braking events do not occur regularly, there are instances of braking events that would present a hazard to both seated and standing passengers, therefore systems that would mitigate these issues would have real benefits to both passenger comfort and safety. During tests to simulate the use of the vehicle retarder for an autonomous braking system, deceleration rates largely remained safely within standee and seated passenger stability limits, whereas an emergency stop test showed a peak deceleration 3.5 times the limit of a standee supported by a vertical handrail, and 4 times the limit for a forward/backward facing seated passenger.

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“…Driver's driving skills, driving habits, and their own qualities have a great impact on road traffic safety. 18,19 Usually, when a car is driving, the driver obtains information from the traffic environment through visual, auditory, and tactile organs. They then process this information through the brain, make reflections and judgments, and then manipulate the car to operate on the road according to the driver's will.…”

Section: Screening Of Factors That Affect Traffic Safetymentioning

confidence: 99%

Highway safety influencing factors in cold regions based on attribute recognition theory

Pei

Wang

et al. 2018

Advances in Mechanical Engineering

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To study the problem of highway traffic safety in cold regions, a thorough statistical analysis using traffic accident historical data is used to evaluate the influencing factors on highway traffic safety. A road traffic safety indicator system for cold regions is developed to evaluate the weight of these influence factors, such as driver performance, vehicle capacity, road condition, and general impact of the traffic environment. An index system of highway traffic safety influencing factors for cold regions is developed, and an evaluation model for traffic road safety influencing factors in cold regions based on attribute recognition theory is proposed. The weight of the model is determined using an analytic hierarchy process combined with expert scoring. The evaluation model is based on single-index attribute measure values and multi-index comprehensive attribute measurement values, using the confidence criterion to identify the influence of road traffic safety factors on road traffic safety in cold regions. In addition, the fuzzy comprehensive evaluation method is used for comparative evaluation, and the evaluation results were consistent and verified the correctness and feasibility of the attribute recognition model. Results showed that the evaluation system was in good agreement with actual traffic conditions in cold regions.

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A field operational test in China: Exploring the effect of an advanced driver assistance system on driving performance and braking behavior

Cited by 65 publications

References 37 publications

Evaluating the Driving Risk of Near-Crash Events Using a Mixed-Ordered Logit Model

Evaluating the Driving Risk of Near-Crash Events Using a Mixed-Ordered Logit Model

Advanced Driver-Assistance Systems for City Bus Applications

Highway safety influencing factors in cold regions based on attribute recognition theory

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