Effect of the car-following combinations on the instability of heterogeneous traffic flow

Abstract

Heterogeneous traffic flow contains the mixed operation of the different vehicle classes such as cars, trucks and buses. Previous study has indicated that the overall stability of the heterogeneous traffic flow is governed by a weighted mean of stability parameters corresponding to each vehicle class and is not affected by the order in which a vehicle class is put into the system, for example either car or truck. However, it has been recently reported that the effect of mixed composition on traffic flow dynamics is also determined by the car-following vehicle type, that is either car following a car or car following a truck. This paper aims at investigating analytically how different car-following combinations (i.e. the following type) influence the overall stability of heterogeneous traffic flow dynamics. More specifically, we will consider the four types of car-following behaviour such as car-car, car-truck, truck-car, and trucktruck. The effect of such car-following types on the overall linear stability condition of the heterogeneous traffic flow will be studied using a generalised multi-class car-following model in which the optimal speed function is not only dependent on the the space headway between two consecutive vehicles as in previous study of Mason and Woods [1997. "Car-following Model of Multispecies Systems of Road Traffic." Physical Review E: 2203-2214] but also on the and the relative speed between those two consecutive vehicles.

A multiclass microscopic model for heterogeneous platoon with vehicle-to-vehicle communication

“…Specifically, four types of car-following combinations in such a typical heterogeneous platoon will be taken into account: CA-following-CA (CC), CAfollowing-human (CH), human-following-CA (HC) and human-following-human (HH). Note that the effect of different car-follow combinations on (human-driven) heterogeneous traffic flow has been theoretically studied in (Ngoduy 2015a) in which the function governing the vehicle dynamics is identical, i.e. f i (.)…”

Platoon based cooperative driving model with consideration of realistic inter-vehicle communication

“…Another important issue is the heterogeneity of vehicle dynamics in CDS, such as the effect of intelligent vehicles on the multi-class traffic flow stability (Ngoduy, 2012(Ngoduy, , 2013a, the mixed operation of the different vehicle classes (e.g. trucks and cars) on the stability of traffic flow (Ngoduy, 2015), the impact of heterogeneous parasitic time delays and lags on ACC-equipped vehicle longitudinal dynamics (Ling and Gao, 2011), etc. Specifically, due to the natural limitations and uncertainties in practical vehicular networking, such as transmission range, packet loss, and probabilistic transmission delay, substantial work has been concerning how to design the CDS under such communication constraints and uncertainties (Ghasemi et al, 2013, Hao and Barooah, 2012, Jin and Orosz, 2014, Kesting et al, 2010b, Middleton and Braslavsky, 2012, Oncu et al, 2011, Ploeg et al, 2013.…”

Traffic responsive intersection control algorithm using GPS data

“…In this paper, connected vehicles (CVs) are those which transmit and receive information from vehicles and infrastructure equipped with communication systems. Having multiple classes of vehicles has been shown to have negative effects on the resulting traffic flow [10], [11], and is taken into account.…”