Chemotaxis and autochemotaxis play an important role in many essential biological processes. We present a self-propelling artificial swimmer system that exhibits chemotaxis as well as negative autochemotaxis. Oil droplets in an aqueous surfactant solution are driven by interfacial Marangoni flows induced by micellar solubilization of the oil phase. We demonstrate that chemotaxis along micellar surfactant gradients can guide these swimmers through a microfluidic maze. Similarly, a depletion of empty micelles in the wake of a droplet swimmer causes negative autochemotaxis and thereby trail avoidance. We studied autochemotaxis quantitatively in a microfluidic device of bifurcating channels: Branch choices of consecutive swimmers are anticorrelated, an effect decaying over time due to trail dispersion. We modeled this process by a simple one-dimensional diffusion process and stochastic Langevin dynamics. Our results are consistent with a linear surfactant gradient force and diffusion constants appropriate for micellar diffusion and provide a measure of autochemotactic feedback strength vs. stochastic forces. This assay is readily adaptable for quantitative studies of both artificial and biological autochemotactic systems.artificial swimmers | chemotaxis | autochemotaxis | microfluidics L ocomotion of living bacteria or cells can be random or oriented. Oriented motion comprises the various "taxis" strategies by which bacteria or cells react to changes in their environment (1). Among these, chemotaxis is one of the best-studied examples (2, 3): Cells and microorganisms are able to sense certain chemicals (chemoattractants or chemorepellents) and move toward or away from them. This is an essential function in many biological processes, e.g., wound healing, fertilization, pathogenic species invading a host, or colonization dynamics (4, 5). When the chemoattractant or chemorepellent is produced by the microorganisms themselves, the system exhibits positive or negative autochemotaxis. Thus, chemotaxis provides a mechanism of interindividual communication. Modeling such communication strategies is key to understanding the collective behavior of microorganisms (6-8) as well as flocks of animals like fire ants (9, 10).To model the swimming motion of microorganisms, various self-propelling artificial swimmer systems have been developed based on different mechanisms. Generally, there are two classes of swimmers: systems driven by and aligning with external fields (11-14), including chemotactic gradients, and selfpropelled swimmers, which move autonomously in homogeneous environments (15-21). Many autonomous swimmers additionally react to external fields, e.g., phototactic gradients (22).Biological autochemotactic systems exhibit very complex behaviors (23,24), where physical effects are intermingling with effects from various bioprocesses such as cell migration, metabolism, and division. To untangle these effects, there have been some design proposals for artificial systems, such as in ref.25, and simulations on the dynamics o...