3 research outputs found

    Longitudinal jerk and celeration as measures of safety in bus rapid transit drivers in Tehran

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    Traditionally, analysis of individual differences in road traffic crash risk has relied on after the fact crash data. Nowadays with the help of technologies like GPS, new measures are developed to assess driving risk, inferred from naturalistic driving behavior of drivers. In this study, two main ways of modelling driver behavior in naturalistic driving research were discussed and compared to each other. For this purpose, 176 Bus Rapid Transit (BRT) drivers were investigated during their normal driving on Tehran BRT routes. Their speed was continuously recorded by a smart phone app from which was derived deceleration, jerk, and celeration measures. Analysis showed that all of the proposed measures had positive correlations with culpable crashes and that one of the jerk variables yielded the highest correlation. Measurements of speed derivatives like jerk and celeration can help to identify dangerous driving styles in public transportation and reduce the number of crashes. Although the results of this study are encouraging, further studies for longer periods are needed to improve the reliability of the measures

    A Decentralized Smartphone Based Traffic Information System

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    Location-Based Services (LBSs) are information or entertainment services where the request, the response and served contents depend on the physical position of the requesting device. LBS are frequently used to implement Traffic Information Systems (TIS), which are increasingly based on user-contributed information. In this paper we present the first prototype of our solution for a decentralized, smartphone-based TIS, called D4V, that allows each participant vehicle to efficiently discover data or services located near any chosen geographic position. The experimental evaluation has shown that D4V could be effectively used on the road to reduce the number of drivers involved in traffic jams, as well as to disseminate alert messages about potentially dangerous road stretches, thus allowing drivers to reduce risks and nuisances along their paths
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