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Monitoring drivers’ perception of risk within a smart city environment
Published in Symeon E. Christodoulou, Raimar Scherer, eWork and eBusiness in Architecture, Engineering and Construction, 2017
In order to prevent a collision the distance between two consecutive vehicles should be such as the following vehicle will have the appropriate distance to safely stop in the case of a sudden break of the leading vehicle or if any other hazardous situation occurs in the network. Rear end collisions are significantly featured in road-crash statistics; it has been reported that around 28% of all road accidents are rear-end collisions. Research focused on driving behaviour in different states of traffic, has shown that a major contributor to rear-end collisions is a short headway, which does not allow for the following vehicle to react in an appropriate manner in the case of a sudden break of the leading vehicle (Taieb-Maimon and Shinar, 2001). As such, monitoring the distance between consecutive vehicles in real-time situations could be valuable in the identification of near-crash phenomena and crash prediction.
Precast segmental bridge construction in seismic zones
Published in Fabio Biondini, Dan M. Frangopol, Bridge Maintenance, Safety, Management, Resilience and Sustainability, 2012
Fabio Biondini, Dan M. Frangopol
Recent studies of the behaviour of drivers in congested flow show that, although widely scattered, the average time headways display little variation with respect to speed, flow or density through most of the congested flow regimes and therefore are considered as a ‘constant’ feature of driver behaviour in congested flow (Daganzo, 2002; Banks, 2003). However, the average time headways at all speeds in congested flow vary significantly from site to site. The nature of these variations in behaviour may be due to the differences in driver populations, physical features of the sites or other functions involved (Banks, 2003). The purpose of this analysis is to determine the effects (if any) of these specific features of driver behaviour on the formation of traffic load models under congested regimes. This requires the development of traffic micro-simulation scenarios to explain driver behaviour at a micro- level, the main element of which is lane changing. The latter is highly significant in influencing the formation of platoons of trucks in the slow lane which is important for the load effects in the bridge decks supporting this lane.
Mixed traffic driver behavioral modeling at urban merge section: an experimental study
Published in Transportation Letters, 2022
Bhargav Naidu Matcha, Sivakumar Sivanesan, K. C. Ng, Se Yong eh noum
Space headway can be defined as the distance between same points of two consecutive vehicles following each other. The dynamic parameters such as speeds of different vehicles varied as high as 15 m/s to as low as 9 m/s, showing varied maneuvering capabilities of each vehicle type. Also, due to their wide range of difference in static characteristics like the size, they exhibit their own acceleration capabilities. Hence, in order to determine the longitudinal movements of different vehicles, the space headways of different vehicle pairs are shown in Table 4 and Figure 9 (a), (b), and (c). From the analyzed data, it can be suggested that the vehicle-following nature exists, since the mean and standard deviation of vehicle pairs are quite close. However, the mean space headway varied for different vehicle pairs. The following mean headway in case of motorcycles are comparatively less than other vehicle types, showing high manoeuvrability due to their small size. Hence, these results show the presence of the following behavior but varies for different vehicle pairs.
Multiclass multilane model for freeway traffic mixed with connected automated vehicles and regular human-piloted vehicles
Published in Transportmetrica A: Transport Science, 2021
Tianlu Pan, William H. K. Lam, Agachai Sumalee, Renxin Zhong
Headway, defined as the time/space between the same positions of two consecutive vehicles, is an important measure of traffic flow characteristics, and thus it is essential for studying traffic flow. Because CAVs have significantly different operating characteristics compared to RHVs, it is deemed that CAVs can significantly reduce the headway between vehicles and hence increase the roadway capacity (Chen et al. 2017; Levin and Boyles 2016b). Therefore, it is necessary to define a headway distribution law to model the capacity enhancement with the introduction of CAVs and to enable minimum headway control for the mixed traffic.