The Social Force Model of pedestrian dynamics is formulated in a way that a) most of its parameters do not have an immediate interpretation, b) often one single parameter has an impact on many aspects of walking behavior and c) a certain aspect of walking behavior results from the values of more than one parameter. This makes calibration difficult. The aim of this paper is to give practitioners an indication of how to proceed in the calibration process. For this by analytical transformations the parameters of the Social Force Model are related to real properties that have a clear and immediate meaning and which are also highly relevant result properties of a simulation: extent and clearance time of a queue, respectively maximum density and capacity flow. The theory for this is presented as well. As a side effect it can give a deeper understanding of the model for everyone interested in theoretical aspects.

The introduction of automated vehicles is expected to affect traffic performance. Microscopic traffic simulation offers good possibilities to investigate the potential effects of the introduction of automated vehicles. However, current microscopic traffic simulation models are designed for modelling human-driven vehicles. Thus, modelling the behaviour of automated vehicles requires further development. There are several possible ways to extend the models, but independent of approach a large problem is that the information available on how automated vehicles will behave is limited to today’s partly automated vehicles. How future generations of automated vehicles will behave will be unknown for some time. There are also large uncertainties related to what automation functions are technically feasible, allowed, and actually activated by the users, for different road environments and at different stages of the transition from 0 to 100% of automated vehicles. This article presents an approach for handling several of these uncertainties by introducing conceptual descriptions of four different types of driving behaviour of automated vehicles (Rail-safe, Cautious, Normal, and All-knowing) and presents how these driving logics can be implemented in a commonly used traffic simulation program. The driving logics are also linked to assumptions on which logic that could operate in which environment at which part of the transition period. Simulation results for four different types of road facilities are also presented to illustrate potential effects on traffic performance of the driving logics. The simulation results show large variations in throughput, from large decreases to large increases, depending on driving logic and penetration rate.

Although the future era of autonomous driving is seen as a solution for many of the current problems in traffic; the introductory phase, with low penetration rates of connected-autonomous vehicles (CAVs), might lead to lower capacities. This forecast is based on certain assumptions that the CAVs can operate more efficiently when communicating and cooperating—already proved in real tests—therefore in practice, they can keep smaller following headways. However, it is envisioned that they might keep larger headways to other conventional vehicles for safety reasons. Lower connected-autonomous vehicle (CAV) penetration rates lead to a reduction in the overall vehicle throughput, then with increasing penetration rates, throughput is recovered and eventually improved. Simulations demonstrate that the impact on vehicle throughput depends on the car following headway and penetration rate. Based on this potential reduction in the maximum throughput for low penetration rates, the aim of this paper is the mitigation of this phenomenon at urban intersections through a possible managing solution to sort CAVs and a pre-set green-time start. A microsimulation model has been calibrated using PTV Vissim to reflect this operating solution, using new possibilities as leading vehicle class dependent headway settings and formula-based routing for sorting vehicles at a two-lane intersection entry. This approach allows the formation of platoons at intersections and uses their effectiveness even at low CAV penetration rates. The tested scenario is simplified to through traffic without turnings maneuvers and the results show that the potential loss in throughput is canceled and reductions in the control delay can reach 17% for oversaturated conditions.

It has been argued that the speed-density digram of pedestrian movement has an inflection point. This inflection point was found empirically in investigations of closed-loop single-file pedestrian movement. The reduced complexity of single-file movement does not only allow a higher precision for the evaluation of empirical data, but it occasionally also allows analytical considerations for micosimulation models. In this way it will be shown that certain (common) variants of the Social Force Model (SFM) do not produce an inflection point in the speed-density diagram if infinitely many pedestrians contribute to the force computed for one pedestrian. We propose a modified Social Force Model that produces the inflection point.

It has been argued that the speed-density diagram of pedestrian movement has an inflection point [1] (p. 3, "Domain I: ... At low densities there is a small and increasing decline of the velocity ... Domain III: ... For growing density the velocity remains nearly constant."). This inflection point was found empirically in investigations of closed-loop single-file pedestrian movement.The reduced complexity of single-file movement does not only allow a higher precision for the evaluation of empirical data, but it also significantly simplifies analytical considerations. This is especially true if one assumes homogeneous conditions, i.e. neglects temporal variations (consider time averages, neglect stop-and-go waves), individual differences of pedestrians (all simulated pedestrians have identical parameters) and investigates only steady-state (not the initial phase). As will be shown in this contribution one then can make a transition from the microscopic to a continuous and macroscopic perspective.Building on that it will be shown that certain (common) variants of the Social Force Model (SFM) do not produce an inflection point in the speed-density diagram if -assuming periodic boundary conditions -infinitely many pedestrians contribute to the force computed for one pedestrian. It will furthermore be shown that if -in said 1d movement situation -one only considers nearest neighbors for the computation of the interpedestrian forces the Social Force Model in the continuous description results in the so called Kladek formula for the speed-density relation. Since the Kladek formula exhibits the desired inflection point this observation is used as a motivation for an extension of the Social Force Model which allows to transform the continuous description of the SFM continuously to the Kladek formula and which also exhibits the inflection point in the speed density relation. It will be shown then, that this extended SFM yields astonishingly similar speed density relations as the original SFM when only a fixed limited number of (nearest) pedestrians are considered in the computation of the inter-pedestrian force. Finally it will be discussed, if also the description of the speed-density diagram for (motorized, four-wheel) vehicular and/or bicycle traffic could benefit from these measures.